Journal of Islamic Science, Culture & Social Studies
Social Studies

Penerapan Data Mining pada Suku Bunga Investasi Deposito di Indonesia Menggunakan Metode K-Means Clustering untuk Pengelompokan Profitabilitas

Raden Sasongko1✉ , Arief Wibowo2
1 Universitas Budi Luhur
2 Universitas Budi Luhur
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Published
01-04-2022
Pages
70-80

Abstract

Investment in Indonesia has several types, one of which is deposits through banks, namely individual or collective customers lending excess funds to banks and channeling them in the form of credit. This research is about clustering on several Banks, those are Regional, Private, Foreign, Persero and General Banks which have different interest rates for investments. The method used in this study is the Knowledge Discovery using Database (KDD) method, using RapidMiner tools. The algorithm used to perform clustering is the K-Means algorithm. The data that was used is data on investment credit interest rates from several banks in Indonesia obtained from BPS (Central Statistics Agency) Indonesia. This data is taken from 2009-2020. The clustering results obtained are 3 clusters, where cluster 1 is Regional Bank, which turns out to have stable and high loan interest rates, then cluster 2 is Foreign Bank, which also has the lowest and unstable interest rate. While cluster 3 is a private bank and a state-owned company, these two banks have similar interest rates and levels of stability. In addition, these two banks are in the middle for investment options.

Keywords: Clustering Knowledge Discovery using Database K-Means RapidMiner Investment Loan Interest Rate

References

  1. Aprilla Dennis. (2013). Belajar Data Mining dengan RapidMiner. Innovation and Knowledge Management in Business Globalization: Theory & Practice, Vols 1 and 2, 5(4), 1–5. https://doi.org/10.1007/s13398-014-0173-7.2
  2. Dwiastuti, Ninuk (2020). Pengaruh Kredit Perbankan Terhadap Pertumbuhan Ekonomi dan Hubungannya Dengan Kesejahteraan Masyarakat Kabupaten/Kota di Provinsi Kalimantan Barat. Prosiding Seminar Akademik Tahunan Ilmu Ekonomi dan Studi Pembangunan 2020. Retrieved from http://feb.untan.ac.id/wp-content/uploads/2020/12/Ninuk-Dwiastuti.pdf
  3. Harianto, Kristanto N. & Christopher A.L (2016) Implementasi K-Means Clustering untuk Pengelompokan Analisis Rasio Profitabilitas dalam Working Capital. JUISI, Vol. 02, No. 01, Februari 2016. https://journal.uc.ac.id/index.php/JUISI/article/view/111
  4. Nurdiawan, O., & Salim, N. (2018). Penerapan Data Mining Pada Penjualan Barang Menggunakan Metode Metode Naive Bayes Classifier Untuk Optimasi Strategi Pemasaran. Jurnal Teknologi Informasi Dan Komunikasi, 11(1), 84-95. Retrieved from https://jurnalstmiksubang.ac.id/index.php/jtik/article/view/124
  5. Suindyah D, S. (2017). Pengaruh Investasi, Tenaga Kerja Dan Pengeluaran Pemerintah Terhadap Pertumbuhan Ekonomi Di Provinsi Jawa Timur. Ekuitas (Jurnal Ekonomi Dan Keuangan), 15(4), 477. https://doi.org/10.24034/j25485024.y2011.v15.i4.2312
  6. Uska, M. Z., Usuluddin, U., & Rasyid Hardi Wirasasmita, Usuluddin, Baiq Desi Dwi Arianti . (2020). Evaluation of Rapidminer-Application in Data Mining Learning using PeRSIVA Model. Edumatic: Jurnal Pendidikan Informatika.DOI:10.29408/edumatic.v4i2.2688.
  7. Windha Mega P. D. (2015). Clustering menggunakan K-Means untuk Menentukan Status Gizi Balita. Jurnal Informatika Vol 15.
  8. Yunita, R. (2016). Faktor-Faktor Yang Mempengaruhi Tingkat Profitabilitas Perbankan Syariah Di Indonesia (Studi Kasus pada Bank Umum Syariah di Indonesia Tahun 2009 –2012). Jurnal Akuntansi Indonesia, 3(2), 143. https://doi.org/10.30659/jai.3.2.143-160

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© 2022 Raden Sasongko, Arief Wibowo

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Indexing & Citations

How to Cite

Sasongko, R., & Wibowo, A. . (2022). Penerapan Data Mining pada Suku Bunga Investasi Deposito di Indonesia Menggunakan Metode K-Means Clustering untuk Pengelompokan Profitabilitas. Ascarya: Journal of Islamic Science, Culture, and Social Studies, 2(1), 70-80. https://journal.ascarya.or.id/index.php/iscs/article/view/369

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