ALGORITMA K-MEANS DAN K-MEDOIDS UNTUK PENGELOMPOKAN KECAMATAN PENERIMA BANTUAN SOSIAL DI KABUPATEN BOJONEGORO

Sri Rahayu, Alif Yuanita Kartini

Abstract


Sosial assistance is assistance that is temporary or not forever distributed to underprivileged communities with the aim of improving people's lives well. The types of sosial assistance provided by the government include the Central Non-Cash Food Assistance (BPNTP), Regional Non-Cash Food Assistance (BPNTD), Sosial Assistance for Orphans and the Family Hope Program. The data available at the Office of Sosial Affairs is data on the number of beneficiaries based on the type of sosial assistance in each sub-district. The data has not been grouped into whether it is included in the sub-districts that receive many types of sosial assistance or not. For this reason, in this study, sub-districts in Bojonegoro district were grouped based on the number of recipients of sosial assistance using the K-Means and K-Medoids Algorithms. The data used in this study was obtained from the Bojonegoro Regency Sosial Service in 2019 in the form of the number of BPNTP recipients in each sub-district, the number of BPNTD recipients in each sub-district, and the number of orphans in each sub-district. From this study, it was found that the results of grouping using the K-Means and K-Medoids algorithms obtained three clusters, hereinafter referred to as high clusters, medium clusters and low clusters. In the k-means grouping, the best results were obtained with members of each cluster, namely for the high cluster consisting of 6 sub-districts, the medium cluster consisting of 10 sub-districts, and the low cluster consisting of 12 sub-districts. Meanwhile, with k-medoids, it is obtained for the high cluster consisting of 6 sub-districts, the medium cluster consisting of 16 sub-districts and for the low cluster consisting of 6 sub-districts. From the results of the analysis, it was found that the k-means algorithm was the most suitable for classifying sub-districts receiving sosial assistance in Bojonegoro district because it had a precision value of 63 percent, where this value was higher than the precision value for k-medoids

Keywords


Sosial assistance, Classification, K-Means Algorithm, K-Medoids Algorithm

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References


Badan Pusat Statistika. (2020). Statistik Indonesia 2020 Statistical Yearbook of Indonesia 2020. Statistical Yearbook of Indonesia, April, 192.

Budiman, S. A. D., Safitri, D., & Ispriyanti, D. (2016). Perbandingan metode k-means dan metode DBSCAN pada pengelompokan rumah kost mahasiswa di kelurahan Tembalang Semarang. Jurnal Gaussian, 5(4), 757–762.

Dika Amir Pratama, W. (2016). Evaluasi Manajemen Pemberdayaan Masyarakat. In J+Plus Unesa (Vol. 5, Issue 1).

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis 6th Edition. Pearson Prentice Hall. New Jersey. Humans: Critique and Reformulation. Journal of Abnormal Psychology, 87, 49–74.

Jimmy Daniel Berlianto Oley. (2020). Urgensi untuk Memperbaiki Sistem Bantuan Sosial di Tengah Pandemi COVID-19. Semeru Research Institute, 1–12.

Kamila, I., Khairunnisa, U., Studi, P., Informasi, S., Sains, F., Sultan, U. I. N., & Kasim, S. (2019). Perbandingan Algoritma K-Means dan K-Medoids untuk Pengelompokan Data Transaksi Bongkar Muat di Provinsi Riau. 5(1), 119–125.

Kelly, T. P. M. F. (2020). Kebijakan Pemberian Bantuan Sosial Bagi Keluarga Miskin. Angewandte Chemie International Edition, 6(11), 951–952.

Kusumah, R. D., Warsito, B., & Mukid, M. A. (2017). Perbandingan metode k–means dan self organizing map (Studi kasus: pengelompokan kabupaten/kota di jawa tengah berdasarkan indikator indeks pembangunan manusia 2015). Jurnal Gaussian, 6(3), 429–437.

Mail. (2021). Program Bantuan Sosial Untuk Rakyat. Humas Kom.

Mertler, C. A., Vannatta, R. A., & LaVenia, K. N. (2021). Advanced and multivariate statistical methods: Practical application and interpretation. Routledge.

Ningrum, H., Irawan, E., & Lubis, M. R. (2021). Implementasi Metode K-Medoids Clustering Dalam Pengelompokan Data Penyakit Alergi Pada Anak. Jurasik (Jurnal Riset Sistem Informasi Dan Teknik Informatika), 6(1), 130–139.

Nugroho. (2020). Tahun Pandemi, Angka Kemiskinan di Bojonegoro Meningkat. Https://Www.Suarabanyuurip.Com.

Pramesti, D. F., Furqon, M. T., & Dewi, C. (2017). Implementasi Metode K-Medoids Clustering Untuk Pengelompokan Data Potensi Kebakaran Hutan/Lahan Berdasarkan Persebaran Titik Panas (Hotspot). Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer E-ISSN, 2548, 964X.

Purba, L., Saifullah, S., & Dewi, R. (2019). Pengelompokan Kasus Penyakit Aids Berdasarkan Provinsi Dengan Data Mining K-Medoids Clustering. KOMIK (Konferensi Nasional Teknologi Informasi Dan Komputer), 3(1).

Setyo Nugroho, K. (2019). Confusion Matrix untuk Evaluasi Model pada Supervised Learning. Medium, 1–14.

Sindi, S., Ningse, W. R. O., Sihombing, I. A., Ilmi R.H.Zer, F., & Hartama, D. (2020). Analisis algoritma K-Medoids clustering dalam pengelompokan penyebaran Covid-19 di Indonesia. Jti (Jurnal Teknologi Informasi), 4(1), 166–173.

Supriyanto, R. W., Ramdhani, E. R., & Rahmadan, E. (2014). Sosial protection in Indonesia: Challenges and Future. In Bappenas.

Suryanto, J. (2017). Analisa Perbandingan Pengelompokkan Curah Hujan 15 Harian Provinsi Diy Menggunakan Fuzzy Clustering Dan K-Means Clustering. Jurnal AGRIFOR Volume XVI Nomor.

Susanto, W. E., & Riana, D. (2016). Komparasi Algoritma. Jurnal Speed, 8(3), 18–27.

Talakua, M. W., Leleury, Z. A., & Talluta, A. W. (2017). Acluster Analysis By Using K-Means Method for Grouping of District/City in Maluku Province Industrial Based on Indicators of Maluku Development Index in 2014. Barekeng : Jurnal Ilmu Matematika Dan Terapan, 11(2), 119–128.

Tan, P.-N., Steinbach, M., & Kumar, V. (2006). Data mining introduction. People’s Posts and Telecommunications Publishing House, Beijing.

Yunita, F. (2018). Penerapan Data Mining Menggunkan Algoritma K-Means Clustring Pada Penerimaan Mahasiswa Baru. Sistemasi, 7(3), 238. https://doi.org/10.32520/stmsi.v7i3.388




DOI: https://doi.org/10.33758/mbi.v16i5.1582

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