JOURNAL OF SCIENCE AND SOCIAL RESEARCH
Vol 7, No 3 (2024): August 2024

PENERAPAN DATA MINING UNTUK CLUSTERING KELAYAKAN PENERIMA BPNT MENGGUNAKAN ALGORITMA K-MEANS BERBASIS WEB

Putri Lubis, Dina Amalia (Unknown)
Putri, Raissa Amanda (Unknown)
Harahap, Aninda Muliani (Unknown)



Article Info

Publish Date
17 Aug 2024

Abstract

Abstract: Data mining is a method that has a function to collect data into new information that becomes a reference in decision making. The Medan City Social Service has the task of assisting the government in the social sector, one of which handles the implementation of the distribution of Non-Cash Food Assistance (BPNT). Problems arising in the distribution of this assistance ranging from the number of beneficiary quotas to the difficulty in determining the eligibility of prospective beneficiaries. Overcoming these problems, the clustering process in data mining is very appropriate to use. The algorithm used in clustering the eligibility of BPNT recipients in this study is the K-Means algorithm. The data mining system using the web-based k-means clustering algorithm using the PHP programming language, Codeigniter framework, and MySQL database will classify community data on prospective BPNT recipients in the categories of eligible, considered and ineligible. With this system, it can help the Social Service in determining the eligibility of BPNT recipients effectively and efficiently. Keywords: data mining, k-means clustering, bpnt, website Abstrak: Data mining merupakan suatu metode yang memiliki fungsi untuk pengumpulan data menjadi sebuah informasi baru yang menjadi acuan dalam pengambilan keputusan. Dinas Sosial Kota Medan mempunyai tugas membantu pemerintah dalam bidang sosial salah satunya menangani pelaksanaan penyaluran Bantuan Pangan Non Tunai (BPNT). Permasalahan yang ditimbulkan dalam penyaluran bantuan tersebut mulai dari jumlah kuota penerima bantuan hingga kesulitan dalam menentukan kelayakan dari calon penerima bantuan. Mengatasi permasalahan tersebut proses clustering dalam data mining sangat tepat digunakan. Algoritma yang digunakan dalam klasterisasi kelayakan penerima BPNT pada penelitian ini adalah algoritma K-Means. Sistem data mining menggunakan algoritma k-means clustering berbasis web menggunakan bahasa pemrograman PHP, framework Codeigniter, dan database MySQL akan mengelompokkan data masyarakat calon penerima BPNT dalam kategori layak, dipertimbangkan serta tidak layak. Dengan adanya sistem ini dapat membantu pihak Dinas Sosial dalam menentukan kelayakan penerima BPNT secara efektif dan efisien. Kata kunci: data mining, k-means clustering, bpnt, website

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Journal Info

Abbrev

JSSR

Publisher

Subject

Computer Science & IT Economics, Econometrics & Finance Education Social Sciences

Description

Journal of Science and Social Research is accepts research works from academicians in their respective expertise of studies. Journal of Science and Social Research is platform to disclose the research abilities and promote quality and excellence of young researchers and experienced thoughts towards ...