KNNDT Analisis Perbandingan Kinerja Model K-Nearest Neighbors dan Decision Tree untuk Prediksi Pengeluaran Nasabah

Shindy Yuliyatini; Via Olga Pangaribuan; Adnan  Nuur Bachtiar

doi:10.51353/sy3myf10

Authors

Shindy Yuliyatini Universitas Budiluhur https://orcid.org/0009-0004-5689-5277
Via Olga Pangaribuan Universitas Paramadina
Adnan Nuur Bachtiar Universitas Paramadina

DOI:

https://doi.org/10.51353/sy3myf10

Keywords:

KNN, Decision Tree, Expense Prediction, MAE, MSE

Abstract

Customer expenditure prediction is a crucial aspect of financial data analysis, helping banking institutions better understand consumer behavior. This study compares the performance of two machine learning algorithms, K-Nearest Neighbors (KNN) and Decision Tree, in predicting customer expenditures. The dataset used consists of 2,567 transaction records from a single customer at Bank BCA. The performance of both models is evaluated using three key metrics: Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE). The results show that the KNN algorithm outperforms the Decision Tree by producing lower prediction errors across all evaluation metrics, making it more effective for this predictive task.

References

[1] aws, “Apa itu Machine Learning?,” aws.com. Accessed: Jan. 11, 2025. [Online]. Available: https://aws.amazon.com/id/what-is/machine-learning/

[2] S. Amir and Kusrini, “Prediksi Kebutuhan Nasabah Dengan Teknik Data Mining Dalam Mendukung Strategi Pemasaran Bank,” Jurnal Bangkit Indonesia, vol. 7, no. 2, p. 40, 2018.

[3] N. Nuraeni, “Klasifikasi Data Mining untuk Prediksi Potensi Nasabah dalam Membuat Deposito Berjangka Data Mining Classification for Predicting Customer Potential in Making Term Deposits,” Jurnal Ilmiah Intech : Information Technology Journal of UMUS, vol. 3, no. 01, pp. 65–75, 2021.

[4] N. M. Wasilah, “Penerapan Data Mining Untuk Menganalisis Kepuasan Konsumen Menggunakan Metode C4.5,” vol. 5, no. 1, pp. 85–90, 2013.

[5] R. Indah, O. Limabri, and A. Arif, “Reliya Indah Okta Limabri, Ferry Putrawansyah, Alfis Arif PENERAPAN DATA MINING UNTUK MENGKLASIFIKASI NASABAH BANK SUMSEL BABEL MENGGUNAKAN ALGORITMA C4.5,” ESCAF 2nd2023, pp. 1101–1108, 2023.

[6] F. Febri, Hasbi Yallah, Muhammad Darwis, and Retno Henrowati, “Penerapan Algoritma Id3 Melalui Aplikasi Orange Untuk Prediksi Akurasi Akreditasi Sekolah Dasar Di Depok,” Jurnal Manajemen Informatika dan Sistem Informasi, vol. 7, no. 2, pp. 131–141, 2024, doi: 10.36595/misi.v7i2.1199.

[7] A. Suresh, “Prediction of major crop yields of Tamilnadu using K-means and Modified KNN,” 2018 3rd International Conference on Communication and Electronics Systems (ICCES), no. Icces, pp. 88–93, 2018.

[8] M. Yusa, E. Utami, and E. Luthfi. Taufiq, “Evaluasi Performa Algoritma Klasifikasi Decision Tree Id3 ,” InfoSys Journal, vol. 4, no. 1, pp. 23–34, 2016.

[9] A. Chakure, “Decision Tree Classification,” Toward Data Science. [Online]. Available: https://towardsdatascience.com/decision-tree-classification-de64fc4d5aac

[10] A. A. Suryanto, “Penerapan Metode Mean Absolute Error (Mea) Dalam Algoritma Regresi Linear Untuk Prediksi Produksi Padi,” Saintekbu, vol. 11, no. 1, pp. 78–83, 2019, doi: 10.32764/saintekbu.v11i1.298.

[11] Widiarti, R. R. Periwi, and A. Sutrisno, “Perbandingan Mean Squared Error ( MSE ) Metode Prasad-Rao dan Jiang-Lahiri-Wan Pada Pendugaan Area Kecil,” Seminar Nasional Teknoka, vol. 2, no. 2502, pp. 56–60, 2017, [Online]. Available: https://journal.uhamka.ac.id/index.php/teknoka/article/view/752/296

[12] E. K. Hendarwati, P. Lepong, and S. Suyitno, “Pemilihan Semivariogram Terbaik Berdasarkan Root Mean Square Error (RMSE) pada Data Spasial Eksplorasi Emas Awak Mas,” Geosains Kutai Basin, vol. 6, no. 1, p. 47, 2023, doi: 10.30872/geofisunmul.v6i1.1072.

[13] dicoding intern, “Apa itu Machine Learning? Beserta Pengertian dan Cara Kerjanya,” dicoding.com. Accessed: Jan. 11, 2025. [Online]. Available: https://www.dicoding.com/blog/machine-learning-adalah/

[14] IBM, “Apa algoritma k-tetangga terdekat (KNN)?,” ibm.com. Accessed: Jan. 11, 2025. [Online]. Available: https://www.ibm.com/id-id/topics/knn

[15] Siti Khadijah Azzukhruf Firdausi, “Decision Tree: Pengertian, Manfaat, Plus-Minus, & Contohnya,” dibimbing.id. Accessed: Jan. 11, 2025. [Online]. Available: https://dibimbing.id/blog/detail/decision-tree-pengertian-manfaat-plus-minus-contohnya