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The Development of the Application of a Data Warehouse at PT Jkl

One rapidly evolving technology today is information technology, which can help decision-making in an organization or a company. The data warehouse is one form of information technology that supports those needs, as one of the right solutions for companies in decision-making. The objective of this research is the development of a data warehouse at PT JKL in order to support executives in analyzing the organization and support the decision-making process. Methodology of this research is conducting interview with related units, literature study and document examination. This research also used the Nine Step Methodology developed by Kimball to design the data warehouse. The results obtained is an application that can summarize the data warehouse, integrating and presenting historical data in multidimensional. The conclusion from this research is the data warehouse can help companies to analyze data in a flexible, fast, and effective data access.

INTRODUCTION
A variety of science and technology aspects is always experiencing progress, in accordance with the development of the way human beings think and the suitability of the times. One of the rapidly developing technologies today is information technology, which can help decision-making in an organization or a company. The data warehouse is one form of information technology that supports those needs, as one of the right solutions for companies in decisionmaking. With the data warehouse, allowing the data that consists of a recording of an incident in a certain period of time and consists of a variety of aspects or point of views can be proceeded and served more HIIHFWLYHO\ ÀH[LEOH DQG IDVW 5HI > @ VWDWHG WKDW GDWD warehouse system is connected with different data resources (heterogeneous) and is used by the decision makers to analyze the condition and the development of organizations.
5HI > @ H[SODLQHG WKDW WKH UROH RI WHFKQRORJ\ in daily life is more important at this moment of time. Yet the lack of dynamically presented information and cross time often becomes a problem in analyzing the conditions of companies. The recorded data, which is getting more and more abundant, can cause focus-loss in analyzing data, and also need to take quite a long time to help decision-making. The data warehouse, as one of the information technology aspects, is the right solution for companies in decision-making. With the data warehouse, all the data which are related with GHFLVLRQ PDNLQJ FDQ EH VWRUHG LQ VXI¿FLHQW FURVV time, and also can produce a complete, dynamic, and fast media presentation of information. The analysis is conducted on the condition of companies, the analysis of the strength, weakness, opportunity, and WKUHDW VR WKDW FRPSDQLHV ¶ QHHGV FRXOG EH LGHQWL¿HG PT JKL, as a joint venture company with Manufacturer Hanover Leasing Corporation, United States of America which established in 1982, is one of the oldest funding companies in Indonesia. PT -./ ZDV VSUHDGLQJ ZLQJV LQ WKH ¿HOGV RI OHDVLQJ FRQVXPHU ¿QDQFLQJ DQG IDFWRULQJ DQG WKHQ EHFDPH LQGHSHQGHQW PXOWL ¿QDQFH FRPSDQ\ ZLWK WKH KLJKHVW UDQNLQJ LQ ,QGRQHVLD DQG UHÀHFWHG VWURQJ ¿QDQFLDO performance, experienced management team, high capital, and various competitive advantage as one RI WKH ELJJHVW GRPHVWLF PXOWL ¿QDQFH FRPSDQ\ LQ Indonesia, which make the company continuously hold against economic cycle and the volatility of the market. As the growth of the transaction, historical GDWD WKDW LV SURGXFHG LV JHWWLQJ PRUH GLI¿FXOW WR EH analyzed using static format of the report as current presented.
It takes quite a long time to gather many reports from various period of printing to help the leadership make decisions. Analyzing from various point of views also needs a very long time, so that the decision-making at PT JKL needs a tool that help presenting information faster, complete, and dynamic. The availability of the application of data warehouse at PT JKL is expected to help meeting the needs of the application of data warehouse, so it can help the process of decision-making. The objective of this research is to be able to analyze the needs at PT JKL with the support of the application of data warehouse, so the decision makers can obtain information faster, complete, accurate and dynamic.

Literary Review
7KH GH¿QLWLRQ RI GDWD ZDUHKRXVH DFFRUGLQJ WR UHI > @ LV D FROOHFWLRQ RI GDWD WKDW LV RULHQWHG RQ the subject, integrated, time variant, and a collection of data had not changed that supports the decision making process management. Moreover, it can be used for multiple purposes, including the need for XQNQRZQ IXWXUH 5HIHUULQJ WR UHI > @ GDWD ZDUHKRXVH has four main characteristics, which are subject oriented, integrated, non-volatile, and time variant.
$FFRUGLQJ WR UHI > @ 2QOLQH $QDO\WLFDO Processing (OLAP) is a dynamic blended analysis and a combination of a large amount of multidimensional GDWD $FFRUGLQJ WR UHI > @ 'DVKERDUG LV D FRPSRQHQW that generally has the Performance Management Systems, Performance Measurement Systems, BPM Suites, and BI Platforms. A dashboard provides a visual display from important information that is combined and managed in a single screen, so the information can be understood enough with all see, and also to be explored.

Inventory, Asset, Credit, Contract, and Report
5HI > @ VWDWHG WKDW DVVHWV DUH WKH YDOXH RI something possessed by the company. One which is LQFOXGHG DV DQ DVVHW LV D EXLOGLQJ RU HGL¿FH WKDW LV possessed by the company. So, if a company has a building worth one billion rupiah, the assets which are FRXQWHG LV WKDW RQH ELOOLRQ UXSLDK 5HI > @ VWDWHG WKDW D credit-sale transaction, if the order of a customer has been completed with shipping goods or the delivery of service, for a period of a certain time, the company has an account receivable to customers.
A contract is an event where a company or an individual that make a mutual promise to do a thing based on mutual agreement. The form of that agreement is a series of words that contains the spoken or written promises and agreements. According to 5HI > @ D UHSRUW LV WKH ¿QDO UHVXOW RI D SURFHVV ZKLFK contains information that is out of a system. A report can be computer printed and a presentation on a computer screen monitor.

METHOD
$FFRUGLQJ WR UHI > @ WKH FRQVWUXFWLRQ RI GDWD warehouse has nine stages as it is considered to be a reference in data warehouse development at PT JKL. Firstly, the selection process, which is the right selection process will refer to a certain basic data mart. What is done in this stage is the selection of the subject of problems that is faced from the data warehouse that is going to be made, then continued ZLWK LGHQWL¿FDWLRQ EXVLQHVV SURFHVV DQG WKH QHHG WKDW is related with that subject of the problem. Based on the analysis result of the process of business and the necessity of PT JKL, there are three process that includes the snapshot of the contract agreement, the supervision on the assets, and the snapshot of the assets.
The second stage is grain selection, which determines all the things that are going to be shown in the table of fact. When choosing the grain for the WDEOH RI IDFW WKH WDEOH RI GLPHQVLRQ FDQ EH LGHQWL¿HG for example, in the process of supervising the asset, WKH ¿QDQFH WR UHSRVVHVV DVVHW PXVW EH VKRZQ EDVHG on time. Time can be used as the table of time dimension to determine the calculation of the cost for UHSRVVHVV DVVHW 7KH WKLUG VWDJH LV LGHQWL¿FDWLRQ DQG dimensional adjustment, which is based on the user's needs. Dimension sets the context to give a statement about facts in the table of fact. Doing the analysis of relation with the measurement of grains that had been determined to the information needed.
The fourth stage is the selection of facts that are going to be used for data mart. All the facts should be expressed at the level proposed by the grain, which are the fact of contract agreement's snapshot, the fact of the asset, and the fact of the asset's snapshot. The ¿IWK VWDJH LV WKH VWRUDJH RI SUH FDOFXODWLRQ LQ WKH table of fact. Once the table of fact is chosen, each of those tables of facts should be considered a remake to determine whether there is still a chance to do a calculation or pre-calculations, which is the need to save a calculation of the total cost of installment, and also the interest loan, the total cost to repossess and et cetera.
The sixth stage is the installation of table of dimension. In this stage, returning to the table of dimension and adding as much description texts as possible into the table of dimension. Then, completing the table of dimension which has been determined in accordance with the need. The seventh stage is the selection of duration from the database. The duration measures how long and how far to return to the table of fact. The data that comes to the data warehouse is ¿YH \HDUV KLVWRULFDO GDWD The eighth stage is the determination of the need to slowly keep track of the change of dimension. The change of dimension can occur along with the time passing in the table of dimension. The change which referred to is the addition of the data or the change of the data. There are three kinds of slowly changing dimensions, which are the attribute of the changing dimension is re-written, the attribute of the changing dimension causes a new dimension record is made, the attribute of the changing dimension causes an alternative attribute is made so that both of them can be accessed on the same dimension record.
The ninth stage is the determination if physical design. In this stage, we are going to discuss the problems of physical design. The most crucial DQG LQÀXHQWLDO SK\VLFDO GHVLJQ IRU HQG XVHU WR WKH data mart is the physical order from the table of fact to the disk, and the presence of stored pre-store or aggregations. Other that those problems, there are problems of physical design that affecting the administration, back up, indexing performance and safety. The design of the data warehouse by using this Kimball's method is going to be explained in the next section which is the design of the data warehouse.

RESULTS AND DISCUSSION
According to the stages that had been done and referring to the methodology that had been used, the image of business model and data warehouse are obtained at PT JKL as it was explained below.

Vision and Misision
37 -./ KDV D YLVLRQ WR EHFRPH D ¿QDQFLDO solution partner which also contributes to the improvement of the public living standard by focusing on providing a trustworthy and effective ¿QDQFLDO VROXWLRQ IRU WKH FRQVXPHUV 5HDFKLQJ D JUHDW rate of the returning capital and creating a positive image in the capital market, providing a workplace that is conducive, fair, and challenging, that is going to encourage the best potential of the employees. Establishing a long term partnership relations. Giving a positive contribution for the community where we are operating.

SWOT Analysis
According to SWOT (Strength, Weakness, Opportunity, Threat) analysis, PT JKL has the strength as one of the major role in the biggest industry that stands alone, providing the funding of heavy equipment and four-wheeled vehicles which owns GLYHUVL¿HV DQG RWKHU NLQG RI YHKLFOHV 7KH ZHDNQHVV ZKLFK LV LGHQWL¿HG UHODWHV WR WKH GLI¿FXOWLHV WR DQDO\]H the data because the provided data is still in a form of detail data, so that it takes a long time in the process of decision-making. The opportunity, that is owned, is the new market segments, including international market, and the opportunity because the competitors cannot satisfy the customer's demand. The threat, that is faced, is a new competitors in the same area and the busniess activity that is competing.

Critical factors
Based on the factor's result, that has an important role for the company's development to decide the business' strategy, some factors can be LGHQWL¿HG 7KH GHYHORSPHQW RI KXPDQ UHVRXUFHV to run the company's operational activites. (2) Increasing the best services will attract many FRQVXPHUV WR JLYH WKHLU WUXVWV IRU WKH FRPSDQ\ Increasing the number of customers to gain more SUR¿WV 7KH H[SDQVLRQ RI WKH XQGHUWDNLQJ EXVLQHVV WR EUDQFKHV DV WKH FRPSDQ\ ¶V ¿UVW VWHS RI H[SDQGLQJ the area in Indonesia.

Data Subejct
The data subject is a collection of datas, that can be used to show some information that are required for the executives. The data subject at PT JKL can be seen in the following table:

Business Function
Based on the running system analysis result at PT JKL, a busniess function is obtained as the following table: The business strategy of the company The manager and the stokeholder 7KH PDQDJHU RI ¿QDQFLDO LQIRUPDWLRQ PDQDJHU The customer's data analysis The unpaid credit management The bill's check in accordance of maturity The supervision and the manager of the assets The process of the income goods into the inventory The improvement of inventory goods The auction of inventory goods

Matrix
Matirx is used as the explanatory entanglement or the relation between two aspects in the ongoing system. It is made in a form of table that contains the value of 'x', which means do have a relation, meanwhile '-', which means do not have a relation. The organization has the right and authority of business function. I : Involve in the function The organization gets involved in business function, but it is not responsible/does not have authority of the business function. E : Technical Expertise The organization gets involved and has technical skill that is required by business function. W : Actual Execution of the Work The organization that can do patnership activities according to the bunsiness function. R : Read, the readable data subject in doing the business function. C : Create, the data subject that can be made in doing the business function. U : Update, the data subject that can be changed in doing the business function. D : Delete, the data subject that can be erased in doing the business function.

R : Direct Management Responsibility
The organization is responsible to business function.

A : Execution/Policy Making Authority
The organization has the right and authority of business function. I : Involve in the function The organization gets involved in business function, but it is not responsible / does not have authority of the business function. E : Technical Expertise The organization gets involved and has technical skill that is required by business function. W : Actual Execution of the Work The organization that can do patnership activities according to the bunsiness function. Descriptions: R : Read, the readable data subject in doing the business function. C : Create, the data subject that can be made in doing the business function. U : Update, the data subject that can be changed in doing the business function. D : Delete, the data subject that can be erased in doing the business function.

The need of information
To support the executives in decision-making, informations are needed about the percentage of the instalments, the cost of inventory, the cost of repossess, the quality of contract agreement that had been operating can be seen based on year, quarter, and month.

The problems
Based on the analysis that has been done at PT JKL, its is found several problems that is faced by on the ongoing systems, including the application that is used right now still does not have display format that LV ÀH[LEOH VR WKH LQIRUPDWLRQ WKDW LV OLPLWHG VKRZHG the operationa data, and relation on the company's OLTP table has a high complexity so the process of PDQDJLQJ WKH GDWD LV OHVV HIIHFWLYH DQG HI¿FLHQW WKDW can affect the performance when the data is being accessed. It takes a long time to provide the report that is summarized and multidimensional which is required by the executives in helping to make a decision.

The architecture design
The architecture design of data warehouse that is proposed using the architecture of the centralized data warehouse. The components of the centralized data warehouse's architecture that is proposed is including data sources, data transformation, ETL manager, warehouse manager, the application for users, and meta data. The architecture has the components inclusing data sources that is obtained IURP WKH &R¿QV,0 GDWDEDVH 7KH VHFRQG FRPSRQHQW is the data transformation, functioning to transform the data from data sources to data warehouse. The third component is the ETL manager that manages several activities or all the applications that are related with the data ETL into data warehouse. The fourth component is the warehouse manager, handling all the operations that are related to the data management in the data warehouse. The last component is the access device, that is used by the user of data warehouse to access the content of data warehouse. To see more detail of the architecture that is proposed as seen in WKH IROORZLQJ ¿JXUH

The Deisgn of a scheme of stars
Data warehouse that is proposed, designed with the scheme of stars consists of several tables that are functioned as facts followed with several tables that are functioned as dimensions. There are three schemes of stars including the stars' schemes of SS Agreement, SS Asset, and Asset.

The Structure of Application Menu
As for the illustration to the process of accessing the dashboard is as follows: )LJ 7KH +LHUDUFK\ WR WKH 3URFHVV RI $FFHVVLQJ 'DVKERDUG

The Design of the Application's Display
The display of the application which provides information in a shape of report graphic. Each of the reports provide the information which is required by the managers to help them in making the right decision. The process of providing the data into Fig. 6: The Design of Report Dashboard various forms of bar chart, pie chart and line chart, has already been adjusted with the need of the company in order to be able to analyze the data according to the information that is obtained from the report. Here is the report displays from the result of data analysis obtained from the data warehouse: )LJ 7KH 'HVLJQ RI 5HSRUW 'DVKERDUG The Plan of Implementation To implement this data warehouse application, the hardware and the related software support are QHHGHG WKDW FDQ VXSSRUW 7KH VSHFL¿FDWLRQ RI WKH hardware includes the server component, a minimum 3& ZLWK SURFHVVRU ,QWHOŠ ;(21Š &38 ( # *+] *+] D *% PHPRU\ D *% KDUG disk. The next component is the client, a minimum PC with 2 processor Intel Core 2,6 GHz, a 4 GB memory, Fig. 9: Dashboard OS Asset Unit subject area Collection a 198 GB hard disk. The third component is Network Interface Card (NIC), a card which is functioned as a bridge from a computer to a computer network. The fourth component is the Switch/Hub, which is used to connect the client to the server. From the software, DBMS Microsoft SQL Server 2012 is needed, and the Program of Data Warehouse Application. And it also needs a Microsoft Window 8 64-bit operating system, x64-based processor.

Evaluation
After the design and the implementation of data warehouse application at PT JKL is done, the evaluation result is obtained by doing an interview on the general manager which is the presentation of the report in forms of chart, graphic, and table that has been described based on the user's needs. Moreover, it is also supported by several menus so the manager of the executive can use the dashboard easily. The selection and combination of the display's colors has been compatible with the executives. However, there are several contents that has not been managed well.

CONCLUSION
With the available of this data warehouse, the executives who needs a support to make a decision, get the information that is obtained more completely related to the business function, the format of data which is provided in varies and a lot easier to be understood because the data, that is processed, is VXPPDUL]HG GDWD VR WKDW LW EHFRPHV PRUH HI¿FLHQW and effective to predict the need of the company. Through the dashboard application, the executives can see the report which is required quickly with PRUH ÀH[LEOH GLVSOD\


Analysis of Environmental Complexities and the Associated Dynamics for Development of SME Sector in Pakistan

The primary objective of this research is to explore the complex and dynamic behavior of the business environment for small and medium enterprises. While investigating into the complexities and dynamism of the business environment, this research would also attempt to suggest some guidelines for the development and growth of SME sector in Pakistan. Cluster sampling technique has been used for this research. For the purpose of data collection semi structured interviews have be conducted from eighty entrepreneurs from four SME clusters. This research work concludes that the business environment in Pakistan is relatively more complex in nature than other developing countries. To develop the SME sector in Pakistan it is necessary to understand and manage the environmental complexities with in-depth environmental analysis.

Introduction
Negative effects of environmental complexities and dynamism on business organizations has long been a major area of investigation for many researchers and theorists. In particular, since the seminal work of Emery & Trist (1965) and its followers from Thomson (1967), Duncan (1972) to Post Modern researchers as if Anderson (1999) and Boyne & Meier (2009) it has been well documented that environmental complexities and dynamism create an unfavorable environment for business development. The study of the Dess & Deard (1984) was one of the pioneering studies on the concepts of dynamism and complexities, which synthesized the already existing models and frameworks by intellectually defining the dimensions of task environment. In spite of the growing literature on the dynamics of organizational environment, there are still two fundamental areas that deserve in-depth studies. First, the complexities and behavior of the organizational environment of developing countries like Pakistan are still under explored as most of the research outcomes, available literature, units of analysis, and conceptual models are related with the context of the developed nations. The same arguments are available in the studies of Farjoun (2007). Second, as noted by Elmaraghy (2011), that most of the research studies whether it is conducted in developed countries or in the developing context concentrated on large-scale businesses and manufacturing units. Very marginal studies are available where researchers especially focus on the effects of dynamism and complexity of the business environment on small and medium enterprises. Small and medium enterprises are one of the major contributors in the economy of Pakistan in terms of its exports, employment and gross domestic products. SME sector in Pakistan is currently facing drastic situation due to number of environmental complexities. This context dependent study initially analyzes the environment of Pakistan to clearly understand its complex and dynamic situation, then would focused on the environment of SME sector to clearly outline the state of complex environment that are currently facing by the small and medium enterprises. This research would not only study the behavior of environmental variables, but also focused to improve our understanding about the rate of changes in environmental variables, absence of pattern and unpredictability of the business environment for small and medium enterprises in Pakistan. Lastly, this study would attempt to suggest guidelines that would hopefully help the entrepreneurs in Pakistan to analyze the business environment and develop their enterprises up to the maximum potential.

Complexity and Dynamism:
Complexity and the complex system are two important variables that have been discussed heavily by the organizational researchers during the last fifty years. In the available literature, the main purpose of analyzing the complexity as well as complex system is to develop better understanding of the organizational environment. The preliminary researchers in the field of complexity include Emery & Trist (1965), Thomson (1967) and Duncan (1972). Their early contributions added considerably in the field of contingency theory (Osborn & Hunt, 1974). Complexity can be defined as the number of factors and heterogeneity amongst these factors in environment (Duncan, 1972). In complex system, each part is interconnected with the other part (Cunha, Miguel & Rego, 2010). Dess and Beard (1984) associated complexity with the number, diversity and interrelationship of variables. In the available literature, researchers have classified complexity in various ways e.g. internal complexity and external complexity (Duncan, 1972), vertical, horizontal and spatial (Daft, 1992), unintentional complexity (Ashkenas, 2007) and allot of other complexities like technical complexities, operational complexities etc. There is one confusing and interchangeable term in organizational literature for complex system is complicated system. Most of the practitioners interchange these two concepts and considered complication and complexity as a same thing. Cilliers (1998) who is one of the postmodern organizational researchers in the field of complexity remarkably differentiated between complex and complicated systems. Cilliers (1998) differentiated complex system and complicated system in the following words: "Important distinction and one that is equally difficult to maintain consistently, is the one between complex and complicated. Some systems have a very large number of components and perform sophisticated tasks, but in a way that can be analysed (in the full sense of the word) accurately. Such a system is complicated. Other systems are constituted by such intricate sets of non-linear relationships and feedback loops that only certain aspects of them can be analysed at a time. Moreover, these analyses would always cause distortions. Systems of this kind are complex. I have heard it said (by someone from France, of course) that a jumbo jet is complicated, but that a mayonnaise is complex (P. 3)". Cilliers (1998) also described ten characteristics of complex system. These characteristics include:  Complex system consists of large number of elements. If the elements are small in number then the behaviour of elements of system is complex in nature;  Elements of the complex systems must interact with each other. The interaction should be dynamic;  The numbers of interactions of the elements of a complex system are not equal. Some elements are more active in interaction while others are less;  The interaction of the elements should be non-linear. It means that output would not directly proportion to the input;  The interaction usually have a short range i.e. interactions usually take place with the immediate neighbours;  The effect of the interaction of any element may eventually reflect back on itself, sometimes directly and sometimes indirectly. The feedback can be positive or negative;  Complex systems are usually open systems and difficult to define its boundaries;  Complex system is not in equilibrium state;  Complex systems have a history. Its past behaviours are also responsible for its current behaviours and interactions;  Each element of the complex system has imperfect information about the behaviour of the whole system, it responds only to information that is available locally.
On the other hand, dynamism according to Dess & Beard (1984) refers to the rate of change, absence of pattern and unpredictability of the environment. These unpredictable changes create uncertainties for the organization. They viewed these complexities to be characterized with heterogeneity and the range of organizational activities within the organizational environment. Dess and Beard also contend that highly complex environment generates greater uncertainty for the managers than lesser complex environment. While explaining the environmental complexity, Dess and Beard presented it as a dimension of task environment, but most of the earlier researchers like Child (1972) and Duncan (1972) consider complexity as a characteristic of organizational environment. The relationship between environmental complexity and dynamism with business performance is negative, as elaborated by Fariborz (1996), who states that; "the more complex and dynamic environment, the higher is the level of business failure (p. 696)." In complexity theory, the negative relationship of complexity with organizational performance and its positive relationship with business failure and negative growth are supported by a wide range of research studies including Fernandez (2005) and Heinrich & Fournier (2004). This research is specifically analyzes the business environment of SME sector, therefore it is necessary to understand the basic notion of small and medium enterprises. The huge problem in this regard is the fundamental definition of small and medium enterprises. Every country has adopted its own created definition of SME e.g. any organization with less than 100 employees is considered as SME in Australia, Indonesia, Thailand and China (Witoon, 1999). In USA, any organization having less than 500 employees, and in Japan with less than 200 employees with total assets up to 100 million dollars is considered as small and medium enterprises (Hall, 2002). Any firm that is indexed in Russel Indices (Russel 2500 and Russel Midcap) is also considered as SME in United States. In European Union, any firm that have 50 to 250 employees with annual turnover between 7 to 40 million Euros having total assets less than 27 million Euros and which more than 75 percent ownership is in the hand of small corporation is considered as SME.
In Pakistan, various entities have adopted their own definitions of SME. According to Small and Medium Enterprises Development Authority any organization with paid up capital of 25 million rupees and less than 250 employees are considered as SME (SMEDA, 2007), while SME bank categorized the organization with respect to their total assets. According to SME bank, any organization with less than 20 million of total assets is considered as SME. State Bank of Pakistan in its prudential regulation (2011) of small and medium enterprises defined SME in the following word "an entity, ideally not a public limited company, which does not employ more than 250 persons (if it is manufacturing /service concern) and 50 persons (if it is trading concern) and also fulfils the following criteria of either 'a' and 'c' or 'b' and 'c' as relevant:  A trading/service concern with total assets at cost excluding land and building up to Rs 50 million.  A manufacturing concern with total assets at cost excluding land and building up to Rs 100 million.  Any concern (trading, service or manufacturing) with net sales not exceeding Rs 300 million as per latest financial statements. An Individual, if he or she meets the above criteria, can also be categorized as an SME (p. 05)".

Analysis of the Research Context
Pakistan is a developing country. Economy of Pakistan consists of three major sectors i.e. the agriculture, the industry, and the services (Ministry of Finance, 2012). Agriculture and industrial sectors are jointly called the commodity-producing sector (CPS). The economy of Pakistan, at present, is facing a number of challenges that have the potential to adversely affect its performance. The fiscal year 2011-12 has witnessed a continuous downfall in most of the economic indicators (Pakistan Bureau of Statistics, 2012). There are four major challenges that economy of Pakistan is currently facing, these are political instability, war against terrorism, energy crisis and unfavorable law and order situation. The economy had to suffer heavy losses due to these challenges during FY 2011-12. In this period, the real GDP growth rate was recorded at 3.7 percent, which is the one of the lowest figure since 1992-93. The growth rate in manufacturing sector was around 3.0 percent as compared to the 20 percent during the financial year 2004-05. The negative growth has also been recorded in its exports while total import items increased by 15 percent. The official inflation rate during 2011-12 was 12 percent while it is more than 20 percent according to nongovernmental statistics. Similar situation has been observed in all the stock exchanges of Pakistan including Karachi Stock Exchange, Lahore Stock Exchange, and Islamabad Stock Exchange. As far as SME sector is concerned, about 99 percent of business organizations in Pakistan can be considered as small and medium enterprises in which 53 percent are operating in trade, 20 percent are manufacturing, 22 percent are services and 5 percent are other SMEs (SMEDA, 2007). In the last financial year i.e. 2011-12 the marginal growth of 5.0 percent has been recorded in this sector.

Methodology
This research is a unique opportunity to examine the complexities and dynamism of the business environment related with SME sector. Besides, this research would also attempt to provide procedures and guidelines for entrepreneurs to understand the changes taking place in the business environment of Pakistan, that would hopefully help them to keep align their small as well as medium enterprises with environmental changes and concentrate on the achievements of targets for sustainable business development. Cluster sampling technique has been used for this research. Data was collected through semi-structured interviews from eighty entrepreneurs from four SME clusters included: Fan manufacturing cluster Gujranwala (20); Light engineering cluster Gujranwala (20); Cotton ginning cluster Bahawalpur and Multan (20) and Electrical fitting industrial cluster Sargodha (20). Each of the four selected SME clusters were independent, non-diversified and less than 100 employees. The de jure sample was 80 while de facto sample was 73. These four SME clusters are the selected based on their proper organizational structure, contribution in economy as well as providing the employment opportunities. Development of SME sector in Pakistan is taken as dependent variable with two independent variables: environmental complexities and dynamism. Initially the pilot study was conducted, and content analysis technique was used for the identification of variables from the collected data. Pilot study was conducted on eight entrepreneurs of eight firms from four different clusters that were not included in the final sample. After identification of external variables, further data was collected on the selected variables through semi-structured interviews.

Results and Discussion
SME is a major sector that has a potential to contribute heavily in the development of Pakistan. In the current scenario when the survival is a major issue for most of the production units, it is still a question mark on the future of small and medium enterprises in Pakistan. After analyzing the data from four SME clusters various complex variables have been identified. The percentage of responses against each complex variable is presented in the table below. In the table-1, variables are arranged in descending order with respect to percentage of responses.

Table 1: Complex Environmental Variables
The above table reveals that there are nine major environmental variables that negatively affect the SME sector in Pakistan. There are many other variables that also have adverse effects on the development of SME sector, but adopting the parsimonious approach the scope of this research is limited to the abovementioned nine variables. In the following paragraphs, we will discuss each variable one by one. Energy crisis is currently a major reason behind the fall of SME sector in Pakistan. Currently Pakistan is facing a shortfall of 6000MW per day of electricity. Due to this huge shortfall, most of the production units remain nonoperational for average 17-18 hours per day. The major problem for small and medium enterprises is that they cannot afford the alternate sources of energy like power generators or LPG etc. therefore there output is continuously decreasing since last five years. Terrorism is one of the other major reasons behind the continuous decline of the SME sector in Pakistan. The easy targets for terrorists are small enterprises, retail markets, and community centers because of the lack of facilities available for the security purposes. Therefore, due to terrorist activities the small and medium enterprises suffered huge lose (financial as well as nonfinancial) during the last ten years. The terrorist attacks not only destroys the business community but also damaged the infrastructures facilities in a specific regions. The terrorism is also one of the major reasons that foreign donor agencies and private equity partners are reluctant to invest in Pakistan and their contributions are continuously decreasing since last many years. Shortage of financial resources is another major problem for SME sector in Pakistan. Equity financing is the major source of finance in most of the small and medium enterprises. The financial institutions ask for huge collateral against the loans, therefore it is the major reason that 70 percent of the SME finances comes from equity financing. On the other hand the interest rate charged by various financial institutions is very high i.e. 12 percent. These financial complexities create very drastic situations for SME development. In that prevailing situation, Government of Pakistan remained ineffective in the development of any policy for the development of SME sector. In the last decade, Government of Pakistan paid its full attentions to handle other strategic non-developmental issues like terrorism, law and order, corruption, nepotism and judiciary etc. Therefore, all the respondents of the survey have similar opinion that government did not help the SME sector to resolve its problem.

Complexities
In favor % Another most important issue for the SME sector development is the lack of research and development activities. As we discussed earlier that SME sector is facing the immense shortfall of financial resources and in that situation, it is impossible for the small enterprises to allocate the funds for research and development. The lack of research activities is also a major reason that most of the enterprises are using old and outdated machinery for their production purposes. Seventy percent of the respondents responded that their production machinery is more than 15 to 20 years old. About seventy percent of the respondents are in the favor of the argument that that there is no research activities in SME sector and they are unaware about the latest development in their respective fields. In the current global scenario, the world is moving toward collaboration instead of competition. All the major businesses in the world have adopted various types of collaboration by minimizing the competition in international market. In SME sector of Pakistan, most of the enterprises are working individually. There is marginal evidence that small and medium enterprises have made any type of consortiums or virtual organization to exploit temporary market opportunities or to cope with the current market conditions. Fifty percent respondents responded that there is no collaboration between the enterprises. In some SME clusters e.g. garments etc. there is some evidence of coordination that some organization made a consortium to collaborate with each other and capture the market demand. But one or two cases in whole of the economy have no effect on the whole sector or even specific cluster development. Another major problem for SME sector is the absence of the marketing activities. The small and medium enterprises in Pakistan do not market their products properly in local as well as in international market. Therefore, the local and international buyers have little information about the products of SME sector in Pakistan. That would be the major reason that the graph of annual sale of SME sector is continuously decreasing. In Pakistan, there are very few institutions that are providing training to the workforce of SME sector in Pakistan. These institutions include Pakistan Institute of Management Sciences (PIMS), Technical Training and Vocational Authority (TEVTA), Provincial Vocational Training Councils, Skill Development Council etc. These institutions initiated various programs for human resource development, but their contributions in SME sector are heavily questionable. Forty percent of the respondents have the opinion that there is shortage of skilled labor force in SME sector while sixty percent of the respondents are against them. Most of the workers are trained through on the job training process.
To cope with the current situation, it is necessary to manage all these environmental complexities holistically. All the stakeholders including government of Pakistan play their role to minimize the effects of these variables. To develop the SME sector it, is necessary to provide the continuous energy for manufacturing purposes. Government of Pakistan should facilitate the SME sector by exploring the alternate sources of energy like coal, wind, and solar energy etc. Pakistan has huge resources of coal, especially in Thar. It is expected that the proposed Thar project would generate 1000 MW electricity per year. On the other hand, wind energy if exploited only in the coastal areas of Sindh and Baluchistan has the potential to generate about 50000 MW of electricity per year. Pakistan can also benefit from the solar energy, which is a huge and non-delectable source of energy (Alternate Energy Development Board, 2010). These potential sources of energy have not so far been utilized. To resolve the energy crisis in the country, the Government of Pakistan may start the projects sooner to exploit these energy reserves.
Beside the arrangements of alternate sources of energy, the Government of Pakistan may decrease the electricity and gas tariffs to facilitate the SME sector. As far as terrorism is concerned, it is beyond the capacities or direct domain of SME sector to control it. Therefore, the Government of Pakistan may develop a comprehensive policy on terrorism with the help of international partners to control and minimize its effects on the economy of Pakistan. To solve the financial problems and deal with the high interest rates, financial institution should provide loans to SME sector with reasonable collateral on subsidized interest rates and Government of Pakistan should play its role in this regard. Besides all these, there is a strong need to enhance the research and development activities in various dimensions of SME sector like production, marketing and human resource development. It will not only identify the weak areas but also suggest guidelines to make improvements accordingly.

Conclusion
Business environment in Pakistan is complex in nature. The basic characteristics of its environment include larger number of variables with unpredictable changes. The unique behavior of the Pakistani environment is the unpredictable behavior of the variables comprising the business environment that create drastic situation for the manager to make appropriate decisions. This research work has attempted to identify the complex variables that affect most of the enterprises in SME sector of Pakistan. The intensity of these variables is high enough that survival is a major challenge for most of the small and medium enterprises. In the current scenario when most of the entrepreneurs are incapable (due to the lack of education, proper training as well as deficiency of financial resources) to understand the intensity of variables change this study would hopefully help them to understand their business environment. But just understanding is not enough to cope with the current situation. SME sector requires a broad base and long-term policy for its survival and development and the role of the Government of Pakistan is very important in this regard. All the players (including entrepreneurs, government of Pakistan, financial institutions and regulatory agencies) of SME sector have to develop a holistic policy, in which each player is not only responsible for his job but also cooperate with other players to achieve the desired results. Without doing this, it would be practically impossible for SME sector to survive and long term growth.


Detecting Movie Segments Using Gaussian Mixture Models for VOD Lectures with Japanese Subtitles

A search system for VOD (video on demand) lectures is useful if it can be applied beyond searches of only text. To facilitate better searching for movie segments to be used in VOD lectures with Japanese subtitles, we propose a method using subtitles and a solving maximum likelihood estimation from a mixture of Gaussian distributions. The detection was performed by a statistical method by using the expectation-maximization algorithm. This allows for the detecting of movie segments and determining their number. In addition to improving evaluation of movie segments, we provide movie segment rankings. Movie segment rankings are computed for each movie segment using a method that removes one Gaussian distribution from a mixture of Gaussian distributions.

Introduction
In recent years, e-learning systems have proliferated on both the Internet and organizational intranets. Elearning systems such as video on demands (VOD) and web-based training systems are used in many universities. In Okayama University of Science, e-learning systems that employ VOD have been used since 2004 (1) . Many students are attending lectures that are delivered using the VOD service.
Many VOD lectures use learning management systems for delivering and managing student's education and the systems are currently under intensive research. The sharable content object reference model (SCORM) (2) is a common standard format used for e-learning contents. In addition to delivering and managing education, consideration should be given to supports for students in understanding VOD lectures. Further, it is necessary to develop a self-learning system which can be used after attending lectures. In particular, the following features are needed: (a) summary outlining lectures; (b) topic searching including location by relevance to homework and the learner's interest; (c) providing other information on the relationship to previous lectures.
As fundamental research for topic searching, we focus on the detection of movie segments from VOD lectures using search words. To achieve this aim, we proposed a method for detecting movie segments by adopting quadratic functions to generate a histogram containing the frequency distribution of a search word in Japanese subtitles (3) . However, this method cannot determine the correct number of movie segments. Therefore, we propose a method to determine the correct number of movie segments by adapting a Gaussian mixture model for VOD lectures with Japanese subtitles. A statistical expectation-maximization (EM) algorithm (4)(5)(6) can be used to estimate the parameters of the model. This algorithm fits the frequency distribution of a search word with a Gaussian mixture model and detects a movie segment from each Gaussian distribution (normal distribution). In particular, the characteristic of this research is to use the subtitles to estimate the number of movie segments. In addition, we provide movie segment rankings by an evaluation method that removes one normal distribution from a mixture of Gaussian distributions.

E-Learning and Search Systems
In Figure 1, we show a screenshot of a VOD system. It displays a movie of a lecturer on the upper left of the screen, the list of contents on the lower left side, and a slide on the right side. Each lecture consists of three sections. The period of one section varies from about 20 to 30 min. Furthermore, homework regarding the contents of the lecture is given at the end of each lecture. Homework provides a way to test the student's understanding of the lecture. In this research, we have added a new search system based on the histogram of the search word frequency in each interval, as shown on the right side of Figure 1. This search system also displays the movie segments and their rankings based on the search words.

Estimation of Word Frequency Distribution
In this research, we suppose that one simple histogram peak corresponds to one topic of a movie segment and several simple curves synthesize an approximate curve for a histogram. For example, we use the search word " (advertisement)" in the 14th lecture of the database in the cyber campus at Okayama University of Science. The keyword is used in the 14th homework assignment: "In the business model on the Internet, please discuss the advantages of the keyword advertisement. In addition, please think about how to get revenue". The graph of the word frequency histogram and the approximate curve are shown in Figure  2. The horizontal shows the movie length. The histogram has a bin width of 1 min. Thus, the vertical axis shows the frequency of words once every minute. As shown in the figure, we can consider that the histogram is synthesized by four distinct peaks.

Detection of Movie Segments by a Mixture of Gaussian Distributions
Accordingly, we consider that the approximate curve is synthesized by a mixture of Gaussian distributions from the histogram of a search word. The parameter estimation of a Gaussian mixture model is determined using an EM algorithm. Because it is a linear combination of Gaussian distributions (normal distributions), it is possible to estimate a movie segment from the estimated mixture of Gaussian distributions. The definition of the appearance-time of a search word, the Gaussian distribution and the mixture of Gaussian distributions are as follows.
(1) Let n be the number of search words and Xϭ{x 1 , … , x n } be a set of appearance times. (2) The Gaussian distribution (normal distribution) is given as: (3) The mixture of Gaussian distributions is then given as: The number of component Gaussian distributions of the Gaussian mixture model is shown by lϭ1, … , m and the parameters of the component Gaussian distributions are q m ϭ{m 1 , … , m m , s 2 1 , … , s 2 m }, where the weight of the l th Gaussian distribution is w l , the average of the l th Gaussian distribution is m l , and the variance of the l th Gaussian distribution is s 2 l .

Algorithm for the detection of movie segments 4.1.1 EM algorithm
Parameters of the Gaussian mixtures are estimated by the EM algorithm.
(1-1) Initial step: Let m l be the midpoint which divides movie times in l, s 2 l ,ϭ1 and w l ϭ1.  (1-3) M-Step

Detection of movie segments
The Gaussian mixture model of the word frequency distribution which comprises the appearance time for the word is approximated by the EM algorithm. In our VOD lecture, because each section of the lecture is anywhere between 20 and 30 min, we assume that there is a maximum of five movie segments.
These are approximated with the superposition of m, mϭ1, … 5, kinds of Gaussian distributions. From each component's Gaussian distribution of the Gaussian mixture model, we estimate the movie segment using a standard deviation of Ϯs l width from the average m l , which covers 68.26%.

Example of detected movie segments
As an example of detected movie segments, we show an example using the search word " (advertisement)". Table 1 shows movie segments detected a mixture of four Gaussian distributions. The best fitting one is the Akaike's information criterion (AIC) (6) . Table  2 shows the topics and the movie segments of the actual VOD movie. We detect four movie segments (Table 1), but the actual movie consisted of five topics. From Table  2, we conclude that Segments 1 and 2 correspond to Topic numbers 1 and 2, respectively. In addition, Segments 3 and 4 correspond to Topic Numbers 4 and 5, respectively. However, we cannot detect the movie segment corresponding to Topic number 3.

Computation of Movie Segment Rankings
In this research, we consider some evaluation methods to rank movie segments. The main point of the distribution, which removes the th Gaussian distribution from m kinds of Gaussian distributions, is defined by the following formula.

An approximation of the word frequency by kernel density estimation
Initially, we use the kernel density estimation with the Gaussian kernel function. The definitions of kernel   density are as follows.
(1) b is the bandwidth. In this research, we use the bandwidth bϭ0.75, which is the width distribution in 1.5 min.

Ranking of a movie segment
The evaluation of each movie segment computes the influence of the removed distribution on the entire distribution during the movie time tϭmϪs, … , mϩs. In this research, we propose three evaluations.

Gaussian distributions
The characteristic of EV1 is the average of the Kullback-Leibler divergence (6) , which is the difference of the two density functions from the mutual function. .     EV2 evaluates the average of two totals squared. The first term is the difference between the kernel density function and the mixture of the Gaussian distributions. The second term is the difference of the distribution which removes the kth Gaussian distribution and the mixture of the Gaussian distributions.

DETECTING MOVIE SEGMENTS USING GAUSSIAN MIXTURE MODELS FOR VOD LECTURES WITH JAPANESE SUBTITLES 42
EV3: Difference of Kullback-Leibler divergence EV3 computes the Kullback-Leibler divergence of the movie segments every second.

An example of ranking by evaluations
We show an example of experimental evaluation as an estimation of movie segments of the search word " (advertisement)".

The approximation using the Gaussian mixture model
The appearance time of the search word " (ad-

Detecting movie segments by each Gaussian distribution
The movie segments are estimated by the average and variance of each Gaussian distribution of the Gaussian distributions. The detected movie segments of each use of the word " (advertisement)" are shown as a function and the mixture of the Gaussian distributions and the total of the square of the difference of the distribution which removes the k th Gaussian distribution and the mixture of the Gaussian distributions (Table  3). Table 4 shows the movie segments obtained using the quadratic functions (3) . The results of the ranks with-   Table 5. The proposed method is effective for detecting movie segments. The Gaussian distributions and the ranking by each evaluation of movie segments are shown in  Each rank by the evaluation of movie segments is shown by the circled numbers.

Experimental results
We computed the difference between the evaluations of five search words and that by human judgment of the 14th lecture from the database. The averages and variances of the results are shown in Table 6 and Figures 3-5. EV2 and EV3 have a similar rank, whereas EV1 has a different trend. EV2 and EV3 use the difference from the sample kernel density. From the experimental results, we consider that EV1 offers the best evaluation and EV2 gives the worst one. In addition, EV1 tends to choose large segments; EV2 and EV3 tend to choose small segments.

Evaluation of Movie Segment Detection by Users
We evaluated the ranking by EV1 from the viewpoint of users. As a preliminary evaluation, we examined the top five movie segments obtained with the search words "access" , "site" , "search engine" , "keyword" and "advertisement" . The subjects were five students in the graduate school of informatics.
The results of the questionnaires are summarized in Table 7. We observe that the best fit for the detected movie segments tends to have many word frequencies.
The frequencies have a significant influence on the evaluation. In the detection of similar movie segments, the frequencies tend to be more divided. These results are in line with our expectations.

Conclusions and Future Work
In this research, we proposed a method to detect movie segments from VOD lectures with Japanese sub-titles. This method applies an EM algorithm for the search word frequency and makes an approximation using a Gaussian mixture model. Therefore, we provide information for self-learning and homework tips to students after they attend a lecture. Although this research is just a first step in the development of topic searches, we believe that the proposed method provides the learner with effective information about search words. The distribution of a search word and movie segments of the topic may be effective in understanding the topics. As future tasks, we will consider using information from electronic presentations or slides to obtain a more precise detection of movie segments, and we will develop a search system by related words for movie segments. These will support in achieving our goal of providing better support to students for understanding lectures.