Penerapan Metode K-Nearest Neighbor untuk Klasifikasi Penerima Dana Program Bedah Rumah

Prakoso, Aditya (2019) Penerapan Metode K-Nearest Neighbor untuk Klasifikasi Penerima Dana Program Bedah Rumah. Tugas Akhir thesis, University of Technology Yogyakarta.

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The need for a clean, orderly decent house with sufficient facilities and infrastructure is the right of every citizen. It has been clearly regulated in Law Number (No). 6 of 2014, also known as the Village Law and Regional Regulation Number (No). 5 of 2016 concerning village fund allocation. In an effort to improve public welfare, the government established a program called Self-Help Housing Stimulant Assistance (BSPS) or better known as the slum upgrading program. Determination for recipients of BSPS is still done conventionally based on the assessment of the local government team, to obtain a candidate's eligibility decision. Data on the results of the assessment of prospective applicants for submission is limited to estimates from the village officials team. By designing and implementing K-Nearest Neighbor method it hopefully can determine the recipient of BSPS for people who don’t have decent house. The system uses the K-Nearest Neighbor method to classify not livable house, so that the funds can be given to the right persons. In this research there are 110 data with 8 attributes. The collected data were tested twice with K = 3. In the first test conducted with 100 training data and 10 test data, the value of accuracy was 100%. In the second testing with 55 training data and 55 test data the accuracy value of the entire test data was 78%. Keywords: System, BSPS, Classification, K–Nearest Neighbor.

Item Type: Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir)
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Teknologi Informasi dan Elektro > S1 Informatika
Depositing User: Kaprodi S1 Informatika UTY
Date Deposited: 05 Apr 2019 04:52
Last Modified: 05 Apr 2019 04:52

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