Penerapan Data Mining Clustering terhadap Perekonomian di Kelurahan Sawah Lebar Menggunakan Algoritma K-Means

Authors

  • Soni Ayi Purnama Universitas Bengkulu
  • Willi Novrian Universitas Bengkulu
  • Niska Ramadani Universitas Bengkulu

DOI:

https://doi.org/10.32627/internal.v7i2.1191

Keywords:

Clustering, Data Mining, K-Means

Abstract

This study aims to analyze the economic conditions of the community in Sawah Lebar Village, Ratu Agung District, Bengkulu City, Bengkulu Province, using the data mining clustering method based on the K-Means algorithm. The K-Means algorithm is applied to group economic data of the community based on several variables, such as Employment Status, Home Ownership, Dependents, Monthly Income, Monthly Expenditure and Age of Head of Family. Through this clustering process, several groups (clusters) are produced that identify different economic patterns in the region, namely Cluster_0 (C0), Cluster_1 (C1) and Cluster_2 (C2). In order for the results of this study to be accurate, the data processing in this study uses the Rapidminer Studio Application. From the results of the data processing that has been carried out, it was found that for C0 there are 17 data, C1 there are 16 Data and C2 there are 17 Data. Then, for the recommendation of the community that is recommended to receive government assistance, it is the community that is in the lowest economic class, namely Cluster_1 (C1), Cluster_2 (C2) is the community with the highest economy, while the community in Cluster_0 (C0) is the middle economy.

 

References

A. Setiawan and S. Huda, “Analisis Faktor yang Mempengaruhi Pertumbuhan Ekonomi Di Kabupaten Mojokerto,” J. Syntax Admiration, vol. 2, no. 8, pp. 1384–1394, 2021, doi: 10.46799/jsa.v2i8.295.

P. Yuniarti, W. Wianti, and N. E. Nurgaheni, “Analisis Faktor-faktor yang Mempengaruhi Tingkat Pertumbuhan Ekonomi di Indonesia,” SERAMBI J. Ekon. Manaj. dan Bisnis Islam, vol. 2, no. 3, pp. 169–176, 2020, doi: 10.36407/serambi.v2i3.207.

J. O. F. Management, “Simanungkalit / JOURNAL OF MANAGEMENT (SME’s) Vol. 13, No.3, 2020, p327-340,” vol. 13, no. 3, pp. 327–340, 2020.

C. J. Siti Mariam, Fitri Handayani, “Penerapan Algoritma Clustering K-Means Untuk Menentukan Prioritas Penerima Bantuan Rumah Akibat Bencana Alam,” J. Tek. Inform. dan Sist. Inf., vol. 10, no. 2, pp. 231–240, 2023.

F. Febriansyah and S. Muntari, “Penerapan Algoritma K-Means untuk Klasterisasi Penduduk Miskin pada Kota Pagar Alam,” JISKA (Jurnal Inform. Sunan Kalijaga), vol. 8, no. 1, pp. 66–77, 2023, doi: 10.14421/jiska.2023.8.1.66-77.

… Preddy, P. Marpaung, I. Pebrian, and W. Putri, “Penerapan Data Mining Untuk Pengelompokan Kepadatan Penduduk Kabupaten Deli Serdang Menggunakan Algoritma K-Means,” J. Ilmu Komput. dan Sist. Inf., vol. 6, no. 2, pp. 64–70, 2023.

I. Iin, R. Fadila, A. Rizki Rinaldi, and F. Fathurrohman, “Penerapan Data Mining Dalam Mengelompokan Jumlah Umkm Berdasarkan Kabupaten Kota Menggunakan K-Means Clustering,” JATI (Jurnal Mhs. Tek. Inform., vol. 8, no. 2, pp. 1446–1450, 2024, doi: 10.36040/jati.v8i2.8427.

G. Sonia and R. A. Putri, “Penerapan Metode K-Means Clustering Untuk Mengelompokkan Data Kelayakan Penerima Bantuan Renovasi Rumah,” Build. Informatics, Technol. Sci., vol. 5, no. 2, pp. 442–455, 2023, doi: 10.47065/bits.v5i2.4298.

D. Endrawati, S. Nujum, and A. Selong, “Pengaruh Pertumbuhan Ekonomi, Rasio Gini dan Indeks Pembangunan Manusia Terhadap Tingkat Kemiskinan Indonesia 2017-2022,” J. Pendidik. Tambusai, vol. 7, no. 3, pp. 20144–20151, 2023.

Y. R. Sari, A. Sudewa, D. A. Lestari, and T. I. Jaya, “Penerapan Algoritma K-Means Untuk Clustering Data Kemiskinan Provinsi Banten Menggunakan Rapidminer,” CESS (Journal Comput. Eng. Syst. Sci., vol. 5, no. 2, p. 192, 2020, doi: 10.24114/cess.v5i2.18519.

R. Maulidiah, M. Muchtar, N. A. Fitri, I. Asriani, and M. P. Yasmine, “Pengelompokan Data Pertumbuhan dan Kontribusi Ekonomi Indonesia Menurut Provinsi Menggunakan Metode K-Means Clustering,” J-SISKO TECH (Jurnal Teknol. Sist. Inf. dan Sist. Komput. TGD), vol. 6, no. 2, p. 436, 2023, doi: 10.53513/jsk.v6i2.7769.

N. Nurjanah, N. Suarna, W. Prihartono, T. Informatika, R. P. Lunak, and G. Tasikmalaya, “Implementasi K-Means Clustering Untuk Mengelompokan,” vol. 8, no. 2, pp. 2462–2468, 2024.

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Published

2024-12-31

How to Cite

Ayi Purnama, S. ., Novrian, W., & Ramadani, N. (2024). Penerapan Data Mining Clustering terhadap Perekonomian di Kelurahan Sawah Lebar Menggunakan Algoritma K-Means. INTERNAL (Information System Journal), 7(2), 178–186. https://doi.org/10.32627/internal.v7i2.1191

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