Klasifikasi Tingkat Kepuasan Masyarakat Penggunaan BPJS Kesehatan di Kota Binjai Menggunakan K-Means Clustering

Nadila Rahmawati; Relita Buaton; Indah Ambarita

doi:10.62951/switch.v2i4.188

Authors

Nadila Rahmawati STMIK Kaputama Binjai
Relita Buaton STMIK Kaputama Binjai
Indah Ambarita STMIK Kaputama Binjai

DOI:

https://doi.org/10.62951/switch.v2i4.188

Keywords:

BPJS Health, satisfaction level, K-Means Clustering, Matlab r2014a

Abstract

The health Social Security Administering Agency (BPJS) is a legal entity specifically assigned by the government to administer social security. Seen in the vision and mission of the Long Term Develompment Plan For the Health Sector 2005-2025, namely that the community is expacted to have the ability to access quality health services and also obtain heald insurance, namely that the community gets protection in meeting their basic health needs. Especially for the people of Binjai city, to see the level of satisfaction of peolbe using BPJS Health in the city of Binjai, it is necessary to build a clustering that can group the level of satisfaction in each domicile. Data Mining Grouping using the K-Menas Clustering algoritma metdhod, which is a process of processing quite large amounts of data using statistical methods, this producing a group of data. It is hoped that clustering can complete the grouping of satisfaction levels of BPJS user commuites in the city of Binjai. There are 400 data from correspondent responses from the community regarding the level of satisfaction in using BPJS Health in the city of Binjai. From the results of trials with 400 data carried out with MATLAB, it was found that group 3, cluster 1, had 244 data, cluster 2 had 69 data, cluster 3 had 87 data, group 4 cluster 1 has 78 data, cluster 2 68 data, cluster 3 has 109 data, group 5 cluster 1 has 63 data, cluster 2 has 63 data, cluster 3 has 145 data, cluster 4 has 24 data, cluster 5 has 100 data.

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References

Alfina, Tahta, and Budi Santosa. “Analisa Perbandingan Metode Hierarchical Clustering, K-Means Dan Gabugan Keduanya Dalam Membentuk Cluster Data (Studi Kasus : Problem Kerja Praktek Jurusan Teknik Industri ITS).” Analisa PerbandinganMetode Hierarchical Clustering, K-Means Dan Gabungan Keduanya Dalam Cluster Data, vol. 1, no. 1, 2012, pp. 1–5.

Ariska, Dedek, et al. Clustering Untuk Pemberian. no. November, 2023, pp. 112–30.

Burelia, Ulfhi, et al. Mengukur Tingkat Kepuasan Masyarakat Pada Pelayanan Resor (POLRES) Dumai Menggunakan Algoritma K-Means Clustering. no. 1, 2022.

Ekawati, Ratna, and Nada Nurhalimah. “Kualitas Pelayanan Bagi Peserta BPJS Kesehatan Dan Non BPJS Kesehatan.” Prosiding FRIMA (Festival Riset Ilmiah Manajemen Dan Akuntansi), vol. 5, no. 3, 2022, pp. 483–94, https://doi.org/10.55916/frima.v0i3.317.

Hidayat, Taufik. “Klasifikasi Data Jamaah Umroh Menggunakan Metode K-Means Clustering.” Jurnal Sistim Informasi Dan Teknologi, vol. 4, 2022, pp. 19–24, https://doi.org/10.37034/jsisfotek.v4i1.115.

Nabila, Zulfa, et al. “Analisis Data Mining Untuk Clustering Kasus Covid-19 Di Provinsi Lampung Dengan Algoritma K-Means.” Jurnal Teknologi Dan Sistem Informasi (JTSI), vol. 2, no. 2, 2021, p. 100.

Pranatawijaya, Viktor Handrianus, et al. “Penerapan Skala Likert Dan Skala Dikotomi Pada Kuesioner Online.” Jurnal Sains Dan Informatika, vol. 5, no. 2, 2019, pp. 128–37, https://doi.org/10.34128/jsi.v5i2.185.

Surbakti, Novi Karolina. “Data Mining Pengelompokan Pasien Rawat Inap Peserta BPJS Menggunakan Metode Clustering (Studi Kasus : RSU.Bangkatan).” Journal of Information and Technology, vol. 1, no. 2, 2021, pp. 47–53, https://doi.org/10.32938/jitu.v1i2.1470.

WIDYANINGSIH, TRI ANANDA, and Denni Pratama. “Penerapan Metode K-Means Clustering Dalam Mengelompokkan Jumlah Peserta Bpjs Kesehatan Jkn/Kis Di Kabupaten Cirebon.” E-Link: Jurnal Teknik Elektro Dan Informatika, vol. 18, no. 1, 2023, p. 17, https://doi.org/10.30587/e-link.v18i1.5330.

Windarto, A. P., et al. “Penerapan Data Mining Menggunakan Algoritma C4. 5 Dalam Mengukur Tingkat Kepuasan Pasien BPJS.” Prosiding Seminar …, vol. 2, 2020, pp. 376–85, http://tunasbangsa.ac.id/seminar/index.php/senaris/article/view/185.