Penerapan Fuzzy C-Means Pada Klasterisasi Penerima Bantuan Pangan Non Tunai
DOI:
https://doi.org/10.30865/klik.v4i1.988Keywords:
BPNT; Cluster; Fuzzy C-Means; Silhouette CoefficientAbstract
One of the social assistance programs routinely provided by the government to Beneficiary Families (KPM) to overcome poverty problems in Indonesia at this time is Non-Cash Food Assistance (BPNT). The Pekanbaru City Social Service itself in distributing BPNT still experiences obstacles, such as the provision of assistance that is less targeted due to the absence of a system that is able to determine the recipient of aid appropriately. This research applies the Fuzzy C-Means Clustering method to analyze KPM data using MATLAB tools. This algorithm allows overlap between data groups and classifies KPM based on their characteristic patterns. This algorithm takes into account the membership level of each data in each group, thus providing more flexible results and not categorizing data rigidly. The results of the application of the FCM Clustering method in this study form two clusters, where the first cluster contains 331 data while in the second cluster there are 351 data. Testing the results of FCM clustering conducted using the Silhouette Coefficient method produces an average coefficient value of 0.426653079. Based on the value of the test results that have been carried out, the FCM algorithm is considered capable of forming clusters on BPNT data
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D. M. Hasimi, “Analisis Program Bantuan Pangan Non Tunai (Bpnt) Guna Meningkatkan Kesejahteraan Masyarakat Dalam Perspektif Ekonomi Islam,” REVENUE: Jurnal Manajemen Bisnis Islam, vol. 1, no. 01, hlm. 61–72, Jan 2020, doi: 10.24042/revenue.v1i01.5762.
M. Usna dan T. Maemunaty, “Implementation Of Non-Cash Food Assistance Program (Bpnt) Pekanbaru City Social Service In Tackling Poverty In The Maharatu Sub-District Of Peaceful Marpoyan Sub-District,” 2019.
H. Gultom, P. Kindangen, dan G. M. V Kawung, “Analisis Pengaruh Program Bantuan Pangan Non Tunai (Bpnt) Dan Program Keluarga Harapan (Pkh) Terhadap Kemiskinan Di Kabupaten Minahasa Tenggara,” 2020.
N. Ikhsan, S. Kurnia Gusti, Yusra, F. Insani, dan F. Wulandari, “Implementasi Penerima Bantuan Pangan Non Tunai (Bpnt) Dengan Meggunakan Metode Genetic Modified K-Nearest Neighbori (GMKNN),” Jurnal Sains dan Informatika, vol. 8, no. 2, Des 2022, doi: 10.34128/jsi.v8i2.526.
S. Dwididanti dan D. A. Anggoro, “Analisis Perbandingan Algoritma Bisecting K-Means dan Fuzzy C-Means pada Data Pengguna Kartu Kredit,” Emitor: Jurnal Teknik Elektro, vol. 22, no. 2, hlm. 110–117, Agu 2022, doi: 10.23917/emitor.v22i2.15677.
S. Kurniawan, A. M. Siregar, dan H. Y. Novita, “Penerapan Algoritma K-Means dan Fuzzy C-Means Dalam Mengelompokan Prestasi Siswa Berdasarkan Nilai Akademik,” Scientific Student Journal for Information, Technology and Science, vol. IV, no. 1, 2023.
B. Christian dan L. Hakim, “Penerapan Algoritma Fuzzy C-Means Pada Penentuan Lokasi Gudang Pendukung PT. XYZ,” AITI: Jurnal Teknologi Informasi, vol. 16, no. Februari, hlm. 31–48, 2019.
V. Herlinda dan D. Darwis, “Analisis Clustering Untuk Recredesialing Fasilitas Kesehatan Menggunakan Metode Fuzzy C-Means,” Darwis, Dartono, vol. 2, no. 2, hlm. 94–99, 2021, [Daring]. Tersedia pada: http://jim.teknokrat.ac.id/index.php/JTSI
Aji Setiawan dan J. N. Akbar, “Implementation Fuzzy C-Means on Decision Support System BPNT (Bantuan Pangan Non-Tunai) Ministry of Social Affairs Indonesia,” EMITTER International Journal of Engineering Technology, vol. 7, no. 2, Des 2019, doi: 10.24003/emitter.v7i2.444.
K. V. Rajkumar, A. Yesubabu, dan K. Subrahmanyam, “Fuzzy clustering and Fuzzy C-Means partition cluster analysis and validation studies on a subset of CiteScore dataset,” International Journal of Electrical and Computer Engineering, vol. 9, no. 4, hlm. 2760–2770, Agu 2019, doi: 10.11591/ijece.v9i4.pp2760-2770.
I. Purnama Sari dan I. Hanif Batubara, “Cluster Analysis Using K-Means Algorithm and Fuzzy C-Means Clustering for Grouping Students’ Abilities in Online Learning Process,” Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE), vol. 2, no. 1, hlm. 139–144, 2021, doi: 10.30596/jcositte.v2i1.6504.
A. Chusyairi dan P. R. N. Saputra, “Fuzzy C-Means Clustering Algorithm For Grouping Health Care Centers On Diarrhea Disease,” International Journal of Artificial Intelligence Research, vol. 5, no. 1, Jan 2021, doi: 10.29099/ijair.v5i1.191.
J. Hutagulung, D. Nofriansyah, dan M. A. Syahidan, “Implementasi Algoritma Fuzzy C-Means Clustering Sistem Crowdfunding pada Sektor Industri Kreatif Berbasis Web,” JEPIN (Jurnal Edukasi dan Penelitian Informatika), vol. Vol.6 No.2, 2020.
J. Hutagalung, D. Nofriansyah, dan M. A. Syahdian, “Penerimaan Bantuan Pangan Non Tunai (BPNT) Menggunakan Metode ARAS,” JURNAL MEDIA INFORMATIKA BUDIDARMA, vol. 6, no. 1, hlm. 198, Jan 2022, doi: 10.30865/mib.v6i1.3478.
N. Persada, R. B. Sinuhaji, I. M. Sarkis, M. Yohanna, dan H. Artikel, “Implementasi Fuzzy C-Means Program Bantuan Langsung Tunai Pada Dinas Sosial Kabupaten Deli Serdang Distribusi Kecamatan Pancur Batu,” 2021. [Daring]. Tersedia pada: http://ojs.fikom-methodist.net/index.php/METHOSISFO
Y. Hidayat, A. Nazir, R. M. Candra, S. Sanjaya, dan F. Syafria, “Clustering Vaksinasi Penyakit Mulut dan Kuku Menggunakan Algoritma Fuzzy C-Means,” Journal of Computer System and Informatics (JoSYC), 2023, doi: 10.47065/josyc.v4i3.3416.
A. Aziz, A. Mutoi Siregar, dan C. Zonyfar, “Penerapan Algoritma K-Means dan Fuzzy C-Means ‘untuk Pengelompokan’Kabupaten Kota Berdasarkan Produksi Padi‘di’Provinsi Jawa Barat,” Scientific Student Journal for Information, Technology and Science, 2022.
A. Syaifudin, P. Purwanto, H. Himawan, dan M. A. Soeleman, “Customer Segmentation with RFM Model using Fuzzy C-Means and Genetic Programming,” MATRIK?: Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer, vol. 22, no. 2, hlm. 239–248, Mar 2023, doi: 10.30812/matrik.v22i2.2408.
P. Dauni dan R. Tri Prasetio, “Pemetaan Keberlangsungan Hidup Umkm Guna Optimalisasi Bantuan Kredit Menggunakan Algoritma Fuzzy C-Means,” JURNAL RESPONSIF, vol. 5, no. 1, hlm. 61–69, 2023, [Daring]. Tersedia pada: https://ejurnal.ars.ac.id/index.php/jti
S. J. A. Sumarauw, M. G. Maukar, M. Grace Maukar, U. Negeri, dan M. Abstrak, “Fuzzy c-Means Clustering untuk Pengenalan Pola Studi kasus Data Saham Fuzzy c-Means Clustering for Pattern Recognition on Case Studies in Holdings Data,” Jurnal Axioma?: Jurnal Matematika dan Pembelajaran, vol. 7, no. 2, 2022.
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