Article Per Year (5 Year)
p-Index From 2021 - 2026
0.835
P-Index
This Author published in this journals
All Journal Jurnal Aplikasi Statistika & Komputasi Statistik PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Sohibien, Gama Putra Danu
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search

 1 
Quantile Regression with Constrained B-Splines for Modelling Average Years of Schooling and Household Expenditure Sasmita, Yoga; Budiman Johra, Muhammad; Jatmiko, Yogo Aryo; Lubis, Deltha A.; Rahmad, Rizal; Sohibien, Gama Putra Danu
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 17 No 1 (2025): Jurnal Aplikasi Statistika & Komputasi Statistik
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v17i1.793

Abstract

Introduction/Main Objectives: Education serves as a driving force for the transformation of society to break the cycle of poverty. This study examines the relationship between average years of schooling and per capita household expenditure in Kalimantan Tengah Province in 2020. Background Problems: The method of estimating a regression model that is assumed to follow a certain form of regression equation such as linear, quadratic and others is called parametric regression. However, researchers often encounter difficulties in determining the model specification through data distribution, so the method used is nonparametric regression. Novelty: This research uses a quantile-based approach to explore how the impact of education on per capita expenditure varies across different levels of household education. This provides a more nuanced understanding of the relationship, showing not just whether education matters, but how its influence changes at different levels of educational attainment. Research Methods: The relationship between average years of schooling and per capita household expenditure is modeled using a quantile regression model with the constrained B-Splines method. Finding/Results: Based on the established classification, it can be concluded that an increase in the average years of schooling among household members tends to have a greater impact on raising per capita expenditure.
Forecasting Farmer Exchange Rate (FER) in Southeast Sulawesi Province Using Cheng’s Fuzzy Time Series Method Rastina; Laome, Lilis; Abapihi, Bahriddin; Wibawa, Gusti Ngurah Adhi; Laome, Mukhsar; Laome, Makkulau; Sohibien, Gama Putra Danu; Sukim; Fathurrahman Yahyasatrio
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 17 No 2 (2025): Jurnal Aplikasi Statistika & Komputasi Statistik
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v17i2.801

Abstract

Introduction/Main Objectives: This study aims to forecast the Farmer Exchange Rate (FER) in Southeast Sulawesi Province for 2024 as a basis for short-term economic assessment and policy-related analysis. Background Problems: FER is a key indicator of farmers’ purchasing power and agricultural welfare; however, its monthly dynamics are characterized by fluctuations and uncertainty, making conventional forecasting methods less effective in capturing its behavior. Novelty: This study contributes by implementing the the Fuzzy Time Series (FTS) Cheng approach for FER forecasting in Southeast Sulawesi, emphasizing its suitability for handling vagueness and nonlinear patterns inherent in agricultural economic indicators. Research Methods: The analysis utilizes monthly secondary FER data obtained from BPS-Statistics of Southeast Sulawesi Province, covering the period from January 2014 to December 2023. Forecast accuracy is evaluated using the Mean Absolute Percentage Error (MAPE). Finding/Results: The forecasting results indicate that the FER values for January, February, and March 2024 are each estimated at 105.93. The model achieved a MAPE of 0.3027%, corresponding to an accuracy level of 99.6973%, which places the forecasting performance in the “excellent” category.
Spatial Model for Food Security in Eastern Indonesia 2024 Shohwah, Fathiyah Nur; Arufi, Imam Fathoni; Wicaksono, Mohammad Iqbal; Meilawati, Nadia Lutfi; Meilani, Nilam Cahya; Sohibien, Gama Putra Danu
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.v2025i1.468

Abstract

Food security is the condition of meeting food needs for the country down to the individual level, as measured by the availability, affordability, utilization, and stability of food. Despite being a basic human need, food security in Indonesia is not evenly distributed, especially in Eastern Indonesia. Based on these findings, this study aims to determine the general picture of food security and the factors influencing it in districts/cities in Eastern Indonesia in 2024. The method used is the Spatial Durbin Model (SDM) with an inverse distance weighting matrix. The results show that the variables Distribution of GRDP of Sector Agriculture, Forestry and Fishing, Poverty Rate, Average Years of Schooling, Lag of Food Security Index, Lag of Open Unemployment Rate, and Lag of Poverty Rate have a significant influence on the Food Security Index variable in districts/cities in Eastern Indonesia in 2024.
The Impact of the Job Creation Law and Other Variables on Indonesia's FDI from 2018 to 2024 Sofiana, Apriani; Sohibien, Gama Putra Danu
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.v2025i1.555

Abstract

Although national Foreign Direct Investment (FDI) realization in Indonesia increased following the enactment of the Job Creation Law in 2021, regional FDI realization actually showed a decline in 17 of Indonesia's 34 provinces. Reviews from international organizations such as the World Bank and the World Trade Organization (WTO) suggest the need for analysis to examine the influence of investment-supporting variables on FDI in Indonesia, including the Job Creation Law policy. Therefore, the objective of this study is to analyze the variables influencing regional FDI realization in 34 provinces for the 2018-2024 period. The method used is panel data regression with the selected Random Effect Model (REM). The results show that the Household Consumption Expenditure (HCE) as a proxy for market size, non-oil and gas exports as a proxy for openness of market access, the mining sector's GRDP as a proxy for natural resource potential, and the Job Creation Law have a positive effect on regional FDI realization. These results align with eclectic dunning theory. Disparities in FDI realization were also found, regions outside Java Island that experienced high FDI realization were partly due to internal factors such as abundant natural resources, the presence of industrial areas, and product diversification.
The Influences of Climate Change and Social Vulnerability on Dengue Fever Incidence Rate in West Java Province 2019–2023 Hanif, Alwan Nabil; Sohibien, Gama Putra Danu; Wulansari, Ika Yuni
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.v2025i1.606

Abstract

In Indonesia, dengue fever is a serious public health problem. The increase in dengue fever cases is influenced by climate change and social vulnerability factors. This study focuses on West Java Province in 2019–2023, aiming to describe the spatial-temporal pattern of dengue fever incidence and analyze the influence of climate factors and social vulnerability using a spatial-temporal model, namely Geographically Temporally Weighted Regression (GTWR). The exploration results show a high concentration of dengue fever incidence rates in 2019, while in 2023, the intensity of dengue fever incidence decreases. The GTWR model produces local parameters across various regions and time periods, indicating that in most regencies/cities, rainfall, population density, access to inadequate sanitation, health facility ratio, and education level have a positive effect on dengue fever incidence rates, while land surface temperature and the percentage of poor people have a negative effect. From the GTWR model results, areas with high levels of dengue fever vulnerability can be identified as priorities for dengue fever management interventions. Therefore, this study contributes to early warning research and dengue fever control program planning by considering the risk of dengue fever vulnerability in each region.
Co-Authors Arufi, Imam Fathoni Bahriddin Abapihi Budiman Johra, Muhammad Fathurrahman Yahyasatrio Hanif, Alwan Nabil Laome, Makkulau Laome, Mukhsar Lilis Laome Lubis, Deltha A. Meilani, Nilam Cahya Meilawati, Nadia Lutfi Rahmad, Rizal Rastina Sasmita, Yoga Shohwah, Fathiyah Nur Sofiana, Apriani Sukim Wibawa, Gusti Ngurah Adhi Wicaksono, Mohammad Iqbal Wulansari, Ika Yuni Yogo Aryo Jatmiko, Yogo Aryo