Prediksi Limit Kredit Menggunakan Metode Regresi Linear

Ahmad Yusuf, Henny Leidiyana, Imam Budiawan

Abstract


Determining appropriate credit limits is essential for financial institutions to manage credit risk effectively while optimizing revenue. This study aims to develop a predictive model for credit limits using linear regression, incorporating primary features such as Rating, Income, and Balance. The dataset consists of 400 credit card customer records with 11 variables, comprising both numerical and categorical data. The research follows the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology, covering stages including business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Data analysis was conducted using Google Colab, involving quality assessment, categorical feature encoding through label encoding, and data normalization utilizing MinMaxScaler. Correlation analysis results indicated that Rating, Income, and Balance have strong correlations with Credit Limit, hence these three variables were chosen as primary predictors for the modeling process.

 


Keywords


Linear Regression, Credit Limit, Google Colab, Prediction

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References


Amansyah, I., Indra, J., Nurlaelasari, E., & Juwita, A. R. (2024). Prediksi Penjualan Kendaraan Menggunakan Regresi Linear:Studi Kasus pada Industri Otomotif di Indonesia. Journal Of Social Science Research, 4, 1199–1216. https://j-innovative.org/index.php/Innovative

Anggrawan, A., Hairani, H., & Azmi, N. (2022). Prediksi Penjualan Produk Unilever Menggunakan Metode Regresi Linear. Jurnal Bumigora Information Technology (BITe), 4(2), 123–132. https://doi.org/10.30812/bite.v4i2.2416

Arinal, V., Azhari, M., & Pendahuluan, I. (2023). Penerapan Regresi Linear Untuk Prediksi Harga Beras Di Indonesia. 5(1), 341–346.

Bambang Riono, S. (2022). Analisis Strategi Pemasaran Kredit, Prosedur Pemberian Kredit, Dan Kualitas Pelayanan Terhadap Kepuasan Nasabah Koperasi Simpan Pinjam. Jurnal Ilmiah Manajemen Dan Kewirausahaan, 1(3), 375–386. https://doi.org/10.55606/jimak.v1i3.508

Farid, M., Wahyudi, D., Chrisvo, A. R., Hidayatullah, M. F., & Parhusip, J. (2024). Analisis Distribusi Selisih Tingkat Penggangguran Terbuka (Tpt) Dan Tingat Partisipasi Angkatan Kerja (Tpak) Menggunakan Google Colab. Jurnal Teknik Informatika Dan Multimedia, 4(2), 39–45. https://journal.politeknik-pratama.ac.id/index.php/JTIM/article/view/828/755

Indah Sucianty, F., & Suria Manda, G. (2022). Analisis Manajemen Risiko Kredit Usaha (KUR) Untuk Meminimalkan. Faradila Indah Sucianty1, Gusganda Suria Manda2, 2022(24), 18–25. https://doi.org/10.5281/zenodo.7460372

Mudassir, A. F., Modding, B., & Hajering, H. (2020). Analisis Kebijakan Pemberian Kredit di Bank Perkreditan Rakyat (BPR). Journal of Accounting and Finance (JAF), 1(1), 1–16. https://doi.org/10.52103/jaf.v1i1.61

Panggabean, D. S. O., Buulolo, E., & Silalahi, N. (2020). Penerapan Data Mining Untuk Memprediksi Pemesanan Bibit Pohon Dengan Regresi Linear Berganda. JURIKOM (Jurnal Riset Komputer), 7(1), 56. https://doi.org/10.30865/jurikom.v7i1.1947

Rawan, D., Pidana, T., & Di, N. (2025). 3 1,2,3. 2023, 606–615.

Rohimah, W., Budianto, E. W. H., & Dewi, N. D. T. (2023). Pemetaan Penelitian seputar Bank CIMB Niaga Syariah dan Konvensional: Studi Bibliometrik VOSviewer dan Literature Review. JEMPER (Jurnal Ekonomi Manajemen Perbankan ), 5(1), 30. https://doi.org/10.32897/jemper.v5i1.2607

Setyoningrum, N. R., Rahimma, P. J., Teknologi, S. T., Tanjungpinang, I., & Tanjungpinang, K. (2022). Implementasi Algoritma Regresi Linear Dalam Sistem Prediksi Pendaftar Mahasiswa Baru Sekolah Tinggi Teknologi Indonesia Tanjungpinang. Prosiding Seminar Nasional Ilmu Sosial Dan Teknologi (SNISTEK), 4, 13–18. https://ejournal.upbatam.ac.id/index.php/prosiding/article/view/5200

Simanjuntak, J. (2023). Penggunaan Informasi Debitor Dari Sistem Layanan Informasi Keuangan Otoritas Jasa Keuangan (Slik Ojk) Sebagai Alat Bukti Permohonan Pkpu. Jurnal Hukum To-Ra : Hukum Untuk Mengatur Dan Melindungi Masyarakat, 9(1), 73–84. https://doi.org/10.55809/tora.v9i1.209

Triono, A., Setia Budi, A., & Abdillah, R. (2023). Agus Triono, Apri Setia Budi, Rafi Abdillah, dan Wahyudi. “Implementasi Peretasan Sandi Vigenere Cipher Menggunakan Bahasa Pemrograman Python.” Jurnal JOCOTIS - Journal Science Informatica and Robotics, vol. 1, no. 1, September 2023, pp. 1-9. E-ISSN: xxxx. Jurnal JOCOTIS-Journal Science Informatica and Robotics E-ISSN : Xxxx-Xxxx, 1(1), 1–9. https://jurnal.ittc.web.id/index.php/jct/




DOI: https://doi.org/10.5281/zenodo.17212143

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ISSN : 3025-6704