Prediction of Passing the Mandatory Motor Vehicle Test in Malang Regency Using Linear Regression

The safety of loaded vehicles is of critical importance, as any accident involving them poses a danger to all road users. Consequently, rigorous testing and careful planning are essential. Testing authorities need to forecast the number of vehicles that will undergo inspection. The objective of this study is to predict the number of vehicles that will pass the mandatory motor vehicle inspection at two testing sites in Malang Regency—Talangagung and Karanglo—for the period 2025–2029. This research used historical synthetic data generated based on seasonal and trend patterns from 2020–2024, a linear regression model was developed to forecast daily vehicle test volumes. The model was evaluated using R² scores of 0.87 for Talangagung and 0.82 for Karanglo, indicating a strong fit. The results project an average daily increase of 10% over five years, with Talangagung expected to handle 130–135 vehicles per day and Karanglo 85–90 vehicles per day by 2029. Strategic recommendations include capacity expansion, optimized scheduling, and digital transformation of administrative processes.

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Publication Details

Journal
Journal of Intelligent System and Telecommunication
Published
2026-10-30
DOI
https://doi.org/10.26740/jistel.v2n2.p104-112
Primary Topic
Forecasting Techniques and Applications
Type
article
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article

Prediction of Passing the Mandatory Motor Vehicle Test in Malang Regency Using Linear Regression

Bambang Sismanto
Journal of Intelligent System and Telecommunication
Forecasting Techniques and Applications
article

Prediction of Passing the Mandatory Motor Vehicle Test in Malang Regency Using Linear Regression

Bambang Sismanto
article en

Abstract

The safety of loaded vehicles is of critical importance, as any accident involving them poses a danger to all road users. Consequently, rigorous testing and careful planning are essential. Testing authorities need to forecast the number of vehicles that will undergo inspection. The objective of this study is to predict the number of vehicles that will pass the mandatory motor vehicle inspection at two testing sites in Malang Regency—Talangagung and Karanglo—for the period 2025–2029. This research used historical synthetic data generated based on seasonal and trend patterns from 2020–2024, a linear regression model was developed to forecast daily vehicle test volumes. The model was evaluated using R² scores of 0.87 for Talangagung and 0.82 for Karanglo, indicating a strong fit. The results project an average daily increase of 10% over five years, with Talangagung expected to handle 130–135 vehicles per day and Karanglo 85–90 vehicles per day by 2029. Strategic recommendations include capacity expansion, optimized scheduling, and digital transformation of administrative processes.

Journal of Intelligent System and Telecommunication
Universitas Negeri Surabaya (ID)
Openalex Percentile: Top 9%
Forecasting Techniques and Applications
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Prediction of Passing the Mandatory Motor Vehicle Test in Malang Regency Using Linear Regression — Bambang Sismanto · Journal of Intelligent System and Telecommunication (2026) | TGRS Research Map | TGRS