Prediksi Jumlah APBD Kota Payakumbuh dengan metode K-Means
Rahayu Mayang Sari(1*), Virdyra Tasril(2), Yori Apridonal M(3)
(1) Universitas Pembangunan Panca Budi Medan
(2) Universitas Pembangunan Panca Budi Medan
(3) STMIK Royal Kisaran
(*) Corresponding Author
Abstract
The government system in the Republic of Indonesia is divided into two parts, namely centralized and regional autonomy. Where both systems have the functions, duties, responsibilities and authority of each. Payakumbuh City's Office of Financial and Asset Management (DPKA) has not been effective in managing APBD data because there is still so much data, as a result of difficulties in grouping data, especially financial data. Nowadays a lot of various kinds of people use data mining because it is able to convert data in many sizes into useful knowledge. The results of the data extraction can be used for various aspects such as sales pattern analysis, crime detection and much more. K-Means algorithm, is a logic grouping or can create data groups in the center (center) closest to the data source. From the test results using the Tanagra application, two clusters in the Payakumbuh City Budget data are large and not large
Keywords
Data Mining, K-Means, Clustering, APBD, Tanagra
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