Performance Achievement Analysis Using Linear Regression and ARIMA (Case Study: KSP Kredit Union Pancur Solidaritas)

Authors

  • Martinus Safril Departemen Pascasarjana Informatika, Universitas Amikom Yogyakarta, 55281, Indonesia
  • Tonny Hidayat Departemen Pascasarjana Informatika, Universitas Amikom Yogyakarta, 55281, Indonesia

DOI:

https://doi.org/10.32815/jitika.v19i1.1078

Keywords:

arima, big data, performance, cooperative, linear regression

Abstract

Linear regression and ARIMA are methods used to determine the target of an organization's work program and are used to measure the achievement of cooperative performance on an ongoing basis. This study aims to analyze performance achievement using linear regression and ARIMA (Auto Regressive Integrated Moving Average). This type of research uses a descriptive quantitative method. The research data in the form of documentation includes the number of assets, the number of cooperative members, socialization, the number of disbursements, the number of defaults and the number of staff of KSP Credit Union Pancur Solidaritas for the period 2021-2024. The data analysis method uses linear regression and ARIMA tests with the Python program. The results of the study prove that the combination of Linear Regression and ARIMA can produce three different performance scenarios, namely upper performance (the highest anticipated performance), predicted performance (predicted performance), and lower performance (the lowest possible performance). Through the results of this analysis, the predicted growth of CUPS members has increased every month, for August 2019 there was a growth of 1,008 members, an increase in June 2025 of 1,426 members.

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Additional Files

Published

20-02-2025

How to Cite

Safril, M., & Hidayat, T. (2025). Performance Achievement Analysis Using Linear Regression and ARIMA (Case Study: KSP Kredit Union Pancur Solidaritas). Jurnal Ilmiah Teknologi Informasi Asia, 19(1), 13–17. https://doi.org/10.32815/jitika.v19i1.1078