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INDONESIA
Zero : Jurnal Sains, Matematika, dan Terapan
Published by Universitas Islam Negeri Sumatera Utara
ISSN : 2580569X     EISSN : 25805754     DOI : 10.30829
Core Subject : Science, Education, Agriculture,
Agriculture, Biological Sciences & Forestry Chemistry Mathematics Physics
Arjuna Subject : -
Articles 282 Documents
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Interregional Poverty Linkages and Human-Capital Correlates in the Special Region of Yogyakarta: Evidence from a Spatial Panel Model Safaat Yulianto; Atika Nurani Ambarwati; Virgania Sari; Aning Azizah Wijayanti; Nadia Resky Reza Az-zahra
ZERO: Jurnal Sains, Matematika dan Terapan Vol 10, No 2 (2026): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v10i2.30830

Abstract

Poverty remains unevenly distributed across the Special Region of Yogyakarta (DI Yogyakarta), suggesting that local conditions and interregional linkages may shape poverty outcomes. This study examined poverty rates across five regencies/city administrative units in DI Yogyakarta during 2021-2025 while accounting for spatial dependence. A balanced panel was analyzed by comparing common, fixed, and random effects models, followed by spatial diagnostics and estimation of a spatial autoregressive fixed-effects model. The average poverty rate declined from 13.28% in 2021 to 10.61% in 2025. Under model-based inference, the spatial lag coefficient was positive (rho = 0.629), indicating spatial association in poverty rates across neighbouring regions. The spatial impact decomposition showed that expected years of schooling had negative direct, indirect, and total effects on poverty, whereas the effects of mean years of schooling, literacy rate, life expectancy at birth, and stunting prevalence were weaker. The findings are interpreted as exploratory, context-specific associations.
A Comparative study of Average-Based FTSMC, GBM, and LSTM for JCI Forecasting Syifa Aulia; I Wayan Mangku; I Gusti Putu Purnaba
ZERO: Jurnal Sains, Matematika dan Terapan Vol 10, No 2 (2026): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v10i2.31020

Abstract

Stocks are high-risk investment instruments, so a model is needed to assist investors in decision-making. The Jakarta Composite Index (JCI) is a key indicator that measures the performance of all stocks on the Indonesian stock exchange. This study compares the performance of the Average-Based FTSMC, GBM, and LSTM models in predicting JCI movements. The research data consists of daily stock index values from June 1, 2024, to June 29, 2026. The models were compared using the evaluation metrics MAPE, RMSE, and MAE. The results show that the Average-Based FTSMC model provides the highest accuracy (MAPE: 0.925%, RMSE: 86.753, and MAE: 65.162). These findings indicate that the fuzzy time series approach is more adaptive to JCI fluctuations than both classical stochastic models and deep learning models. This study is limited to historical data using a single input variable; therefore, generalizing the results to market conditions requires further investigation.

Page 29 of 29 | Total Record : 282

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