Abstract

The Indonesian government launched an entrepreneurial program to encourage economic growth, one of which is MSME(micro, small and medium enterprises). The constraints commonly faced by MSME are limited enterprises capital. The government has also tried to provide assistance financing for MSMEs in the form of CSR (Corporate Social Responsibility), KUR (Credit People's Enterprises) and KTA (Unsecured Credit). For this type of financing or credit determined based on the type of enterprises accompanied by criteria including number of assets, turnover annually, number of employees, current enterprises period and net income. Based on background behind this research aims to help provide recommendations on types MSME capital financing based on assets, turnover, number of employees, enterprises period and net income of a MSME. This research uses data from MSME in the Semarang City, which has been registered with the Semarang City Cooperatives and MSME Office. K-Means Clustering Method is used to cluster net profit criteria. Then the Analytical Hierarchy Process (AHP) method is used to search recommendations on the types of MSME financing based on each weighted criteria. The results of this application are recommendations for types of capital financing MSME is based on assets, turnover, number of employees, enterprises period and every net profit of MSME. For testing of the system being built, it is carried out by means of a blackbox test. From the test results obtained show that the actual results are appropriate with the expected results so that the functional system is running well. Suggestions from this research, it is necessary to develop further systems regarding grouping data to be more specific.

Highlights

  • Taking a decision involves intelligence, wisdom and creativity to help humans solve problems in meeting needs or for survival [1]

  • There are several models that can be used for build a Decision Support System (DSS) one of which is Analytical Hierarchy Process (AHP)

  • The closest distance to the value is chosen the smallest is the position of the net profit of an MSME in a cluster

Read more

Summary

Introduction

Taking a decision involves intelligence, wisdom and creativity to help humans solve problems in meeting needs or for survival [1]. The decision support system (DSS) is interactive computer-based system, which helps decision makers utilize data and models of solving problems that are not structured and semi-structured [2]. There are several models that can be used for build a Decision Support System (DSS) one of which is Analytical Hierarchy Process (AHP). AHP can be used in retrieval multicriteria decisions and good enough to solve problems customer funding identification that requires many criteria. This method combining predictive power and the logic involved in various problem, and synthesize various considerations into matching results which intuitively estimates as presented at the consideration has been made [3]. Cluster analysis is one multivariate analysis used to group objects in such a way that objects in one cluster that is very similar and objects in various clusters are quite different [6]

Objectives
Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call