Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Jambura Journal of Mathematics PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Thalita, Bella Cindy
Unknown Affiliation
Computer Science & IT Mathematics

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

Found 2 Documents
Search

 1 
Mapping Regional Economic Resilience of Indonesian Provinces Through PCA and K-Means Analysis to Support Regional Development Policy Optimization Thalita, Bella Cindy; A'la, Kevina Alal
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.430

Abstract

In Indonesia’s post-decentralization era, assessing regional economic resilience is critical to promoting inclusive development. This study constructs a composite resilience index using seven indicators Human Development Index (HDI), Open Unemployment Rate, GRDP per capita, Gini Ratio, Economic Growth, Capital Expenditure, and Own-Source Revenue (OSR) across 34 provinces from 2020–2024. Principal Component Analysis (PCA) and K-Means clustering are applied to identify resilience patterns and classify provinces into high, moderate, and low resilience categories. The findings reveal significant interprovincial disparities. Provinces such as DKI Jakarta (HDI: 81.65), Bali (HDI: 76.54), and DI Yogyakarta (HDI: 80.22) consistently demonstrate high resilience, supported by low unemployment (e.g., Jakarta: 5.78%) and robust fiscal capacity (e.g., OSR share: Jakarta 58.29%). In contrast, Papua and West Papua exhibit lower resilience scores, characterized by HDI below 65, limited OSR below 15%, and economic growth volatility. Correlation analysis indicates a strong positive association between HDI and fiscal indicators (r = 0.82), while OLS regression confirms OSR and Capital Expenditure as significant predictors of resilience (p < 0.05). Spatial mapping highlights geographic clustering of resilience, with Western Indonesia outperforming the Eastern region— underscoring persistent spatial inequalities. These findings reinforce the necessity for regionally differentiated policies. The study recommends enhancing fiscal autonomy, investing in human capital, and integrating Fintech-based financial inclusion, especially for lagging regions. The study recommends boosting fiscal autonomy, investing in human capital, and leveraging Fintech for inclusive growth. This framework supports evidence-based policies aligned with Indonesia’s SDG and post-2024 development goals.
Implementasi Metode Extreme Value Theory untuk Menghitung Maksimal Kerugian Akibat Bencana Alam Yusuf, Feby Indriana; A’la, Kevina Alal; Thalita, Bella Cindy
Jambura Journal of Mathematics Vol 8, No 1: February 2026
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjom.v8i1.35193

Abstract

This study employs Extreme Value Theory (EVT) using the Block Maxima (BM) approach and the Generalized Extreme Value (GEV) distribution to model and estimate the potential maximum financial losses caused by natural disasters in Central Java, Indonesia. Historical loss data from 2022 are utilized to calibrate GEV distribution parameters, followed by Monte Carlo simulations to project risks over a 12-year horizon. The results reveal that the data exhibit heavy-tailed characteristics (indicated by a positive shape parameter), signaling significant extreme risks. Goodness-of-fit tests, specifically Kolmogorov-Smirnov and Anderson-Darling, confirm the validity of the GEV model. Return level analysis indicates a sharp escalation in risk; for a 100-year return period, potential losses reach a substantial magnitude. These findings contribute methodologically to regional fiscal risk estimation and underscore the necessity of precise financial mitigation instruments.
Co-Authors A'la, Kevina Alal A’la, Kevina Alal Feby Indriana Yusuf