Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal STATISTIKA
Aulia Rizki Firdawanti
Statistics and Data Science, SSMI, IPB University, Indonesia
Decision Sciences, Operations Research & Management Mathematics

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Interpretable Tree-Based Models for Identifying Youth Not in Employment, Education, or Training Siti Nur Azizah; Nabila Syukri; Mauizatun Hasanah; Nimas Ayu Hapsari; Bagus Sartono; Aulia Rizki Firdawanti; Budi Susetyo; Gerry Alfa Dito
Statistika Vol. 26 No. 1 (2026): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v26i1.9117

Abstract

Abstract. Youth Not in Employment, Education, or Training (NEET) is an important indicator in evaluating the extent to which Indonesia's demographic bonus can be optimally utilized. West Java, as the province with the largest number of young people and a NEET rate above the national average, is a strategic context for analysis. Using large-scale SUSENAS 2024 data with class imbalance, this study aims to: (1) compare the performance of Decision Tree, Random Forest, and XGBoost in predicting NEET status under various class imbalance handling strategies; (2) identify key features contributing to predictions using SHAP; and (3) identify NEET typologies based on feature contribution similarities. The Random Forest–Class Weight model showed the best performance with a balanced accuracy of 0.7519. SHAP analysis identified eight key predictors contributing to NEET status, namely age, highest level of education, per capita expenditure, savings account ownership, access to financial services, marital status, KIP/PIP receipt, and gender. Local SHAP-value-based clustering yielded five NEET profiles with distinct combinations of risk factors. Two clusters showed the most distinct risk patterns, each characterized by economic vulnerability and limitations due to domestic roles, making them most easily recognized by the model, while the other clusters showed more complex risk patterns. These findings indicate that NEET status is formed through various risk pathways influenced by economic, educational, and demographic factors, thus requiring the formulation of more targeted policies.
A Hybrid Decision Tree and K-Means Approach for Classifying Community Happiness in Bogor Regency Anwar Fajar Rizki; Dwi Fitrianti; Sri Amaliya; Bagus Sartono; Aulia Rizki Firdawanti
Statistika Vol. 25 No. 2 (2025): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v25i2.5590

Abstract

Abstract. Happiness is one of the key indicators for measuring the quality of life in a community. This study aims to classify the level of happiness among residents of Bogor Regency using a hybrid approach that combines Decision Trees and K-means. The research procedure consisted of data preprocessing, clustering using K-Means to form preliminary groups, and further classification through a Decision Tree to interpret the determinants of happiness. The analysis revealed that the residents of Bogor Regency can be categorized into two groups: those who are fairly happy and those who are less happy. The hybrid model achieved its best performance with a balanced accuracy of 84%, an F1-Score of 37%, and a Kappa score of 28%. Socioeconomic factors, such as marital status, family status, occupation, and the number of cigarettes smoked, were identified as the primary determinants influencing happiness levels. The main contribution of this study lies in demonstrating the effectiveness of a hybrid Decision Tree–K-Means approach for happiness classification and providing interpretable insights that are directly useful for policymakers. These findings offer strategic implications for the local government to design more inclusive socioeconomic policies that aim to enhance happiness and overall well-being among the residents of Bogor Regency.
Co-Authors Anwar Fajar Rizki Bagus Sartono Budi Susetyo Dwi Fitrianti Gerry Alfa Dito Mauizatun Hasanah Nabila Syukri Nimas Ayu Hapsari Siti Nur Azizah Sri Amaliya