Classification of Pension Benefit Adequacy for Civil Servants in Pontianak City Using the C4.5 Algorithm - Indah Maharani, Dwi; Tamtama, Ray (Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Pamulang, Indonesia, 2026)
The development of information technology has encouraged the use of data-driven analysis to support decision-making in the governmental sector, including within the civil service pension system. This study aims to classify the adequacy of pension benefits received by retired Civil Servants in Pontianak City using the C4.5 algorithm. Pension benefit adequacy is determined by comparing the amount of basic pension received with household expenditures, which are calculated using the average monthly per capita expenditure in Pontianak City. The dataset consists of 322 retirees with variables including retirement age, years of service, last education, rank, and number of dependents. The model was developed using several training–testing data proportions, namely 70:30, 75:25, and 80:20. Model evaluation was conducted using accuracy, sensitivity, and specificity based on the confusion matrix. The results show that the 80:20 proportion produces the best model, achieving 100% accuracy, 100% sensitivity, and 100% specificity. The generated decision tree indicates that the most influential variable is the number of dependents, followed by rank and years of service. These findings suggest that household expenditure burdens and employment characteristics play a crucial role in determining pension adequacy. The resulting model is expected to assist pension management institutions in formulating data-driven policies to improve the welfare of retirees.