International Journal of Engineering and Emerging Technology
Vol 2 No 1 (2017): January - June

Data Mining for Clustering Revenue Plan Expense Area (APBD) by using K-Means Algorithm

Wahyudin Wahyudin (Unknown)
I Putu Ari Wijaya (Unknown)
Ida Bagus Alit Swamardika (Unknown)



Article Info

Publish Date
23 Sep 2017

Abstract

APBD is a systematic detailed list of receipts, expenditures and local spending within a certain period ( 1 year ) arranged in Permendagri No. 16 of 2006, so that the data APBD can be used as guidelines for governments and local expenditures in carrying out activities to raise revenue to maintain economic stability and to avoid inflation and deflation. Government financial institutions in areas such as DPKA kota Bima, experienced difficulties in identifying the relevance of each archive data on a APBD that so much, that results in a data warehouse, in addition to the administration, APBD in the government of Kota Bima have not been effective. To minimize the difficulty in identifying heap data archive APBD, then the data warehouse can be used to produce a knowledge that by using the techniques of Data Mining ( DM ), the method used is clustering and forecasting, clusterisasi performed using the K-Means Algorithm while for forecasting with multiple linear regression. With this method intended to classify and identify the data in the budget that have certain characteristics in common, and can predict the value of APBD in the future.

Copyrights © 2017






Journal Info

Abbrev

ijeet

Publisher

Subject

Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Mechanical Engineering

Description

International Journal of Engineering and Emerging Technology is the biannual official publication of the Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University. The journal is open to submission from scholars and experts in the wide areas of engineering, such as civil ...