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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 184 Documents
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Numerical Modeling Based on The Finite Element Method by Fortran90 Software on Beam-Column Joint Dermawan, Adi Susetyo; Ishak, Syarifuddin; Sunarwadi, Hadi Surya Wibawanto; Setiawan, Ichwan
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 1 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i1.24753

Abstract

This research discusses the finite element modeling of flexural failure in beam-column joints subjected to monotonic loads. This research aims to model numerically based on the finite element method by Fortran90 software on beam-column joint. The analysis is conducted using two-dimensional finite element method with three sides (triangular). The method used is quantitative and experimental. Validation testing is carried out on beam-column joint specimens with beam dimensions of 15x20 cm and column dimensions of 20x20 cm (a length of 100 cm). The compressive strength of the beam-column joint is 21 MPa. The test was conducted with a loading pattern at the end of the beam at a height of 1 m from the column. The comparison between the calculations using laboratory testing and  the finite element method shows very consistent results.
Ruin Probability Model for Disaster Insurance Companies: A Systematic Literature Review Saefullah, Rifki; Riaman, Riaman; Sukono, Sukono
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 1 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i1.24371

Abstract

Ruin probability modelling is a crucial aspect for insurance companies that is very important and urgent to maintain the company's solvency. Ruin probability modelling helps identify insolvency risks, so companies can take timely preventive measures before it is too late. This research will present a systematic literature review (SLR) using a bibliometric analysis approach with the support of VOSviewer software, utilising the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method. The data sources used in this study came from 3 databases, namely Scopus, ScienceDirect and Dimensions, which resulted in 9 articles relevant to the topic under study. The results identified research gaps that could be an opportunity for future exploration. This research is expected to provide academic and practical contributions in developing ruin risk mitigation strategies in disaster insurance companies facing natural disaster uncertainty.
Optimal Control Application in Mathematical Model of Indonesian Coffee Export Tax Melyana, Nanda; Syahrini, intan; Munzir, Said
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 1 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i1.24344

Abstract

Coffee is one of Indonesia's largest non-oil and gas export commodities in the agricultural sector, significantly contributing to the country's export volume each year. Major export destinations include the United States, Egypt, Japan, Spain, and Malaysia. Approximately 67% of Indonesia's coffee production is exported, while the remaining 33% serves domestic demand. To optimize the economic values related to production, demand, export volume, and export tax revenue, a dynamic model was developed, followed by two simulations: one where the government controls with set economic targets and another without target controls on export tax. The model formulation involved estimating equations using the Two-Stage Least Squares (TSLS) method, which served as constraints within the optimal control model. The objective of the discrete dynamic optimal control function is to minimize a quadratic objective function that represents deviations from target values and optimal control levels. Simulations conducted with varying weights on both the control function and without governmental intervention showed that changes in the export tax have limited impact on final outcomes, likely due to the high export tax rate applied. It is recommended that, to achieve export tax values closer to desired targets, the government could consider adjusting export tariff policies by reducing the export tax rate, which would also encourage increased export volume. @font-face {font-family:"Cambria Math"; panose-1:2 4 5 3 5 4 6 3 2 4; mso-font-charset:0; mso-generic-font-family:roman; mso-font-pitch:variable; mso-font-signature:-536870145 1107305727 0 0 415 0;}@font-face {font-family:Calibri; panose-1:2 15 5 2 2 2 4 3 2 4; mso-font-charset:0; mso-generic-font-family:swiss; mso-font-pitch:variable; mso-font-signature:-469750017 -1073732485 9 0 511 0;}@font-face {font-family:Cambria; panose-1:2 4 5 3 5 4 6 3 2 4; mso-font-charset:0; mso-generic-font-family:roman; mso-font-pitch:variable; mso-font-signature:-536870145 1073743103 0 0 415 0;}@font-face {font-family:"Baskerville Old Face"; panose-1:2 2 6 2 8 5 5 2 3 3; mso-font-charset:77; mso-generic-font-family:roman; mso-font-pitch:variable; mso-font-signature:3 0 0 0 1 0;}p.MsoNormal, li.MsoNormal, div.MsoNormal {mso-style-unhide:no; mso-style-qformat:yes; mso-style-parent:""; margin:0cm; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman",serif; mso-fareast-font-family:"Times New Roman"; mso-ansi-language:EN-US;}p.IOP-CS-Abstract, li.IOP-CS-Abstract, div.IOP-CS-Abstract {mso-style-name:IOP-CS-Abstract; mso-style-unhide:no; mso-style-qformat:yes; mso-style-link:"IOP-CS-Abstract Char"; margin-top:0cm; margin-right:0cm; margin-bottom:18.0pt; margin-left:70.9pt; text-align:justify; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Cambria",serif; mso-fareast-font-family:Calibri; mso-fareast-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-font-kerning:1.0pt; mso-ligatures:standardcontextual; mso-ansi-language:EN-GB;}span.IOP-CS-AbstractChar {mso-style-name:"IOP-CS-Abstract Char"; mso-style-unhide:no; mso-style-locked:yes; mso-style-link:IOP-CS-Abstract; mso-ansi-font-size:11.0pt; mso-bidi-font-size:11.0pt; font-family:"Cambria",serif; mso-ascii-font-family:Cambria; mso-fareast-font-family:Calibri; mso-fareast-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-font-kerning:1.0pt; mso-ligatures:standardcontextual; mso-ansi-language:EN-GB;}.MsoChpDefault {mso-style-type:export-only; mso-default-props:yes; font-size:10.0pt; mso-ansi-font-size:10.0pt; mso-bidi-font-size:10.0pt; mso-font-kerning:0pt; mso-ligatures:none; mso-ansi-language:EN-US;}div.WordSection1 {page:WordSection1;}
Using an LSTM Neural Network to Improve Symmetric and Asymmetric GARCH Volatility Forecast Rahmawanto, Setya Budi; Nugroho, Didit Budi; Trihandaru, Suryasatriya
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 1 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i1.24614

Abstract

Volatility forecasting is crucial for financial risk management, yet traditional models like GARCH struggle with nonlinearities and asymmetric effects. This study leverages Long Short-Term Memory (LSTM) neural networks to enhance symmetric and asymmetric GARCH models, addressing these limitations. By integrating LSTM with GARCH, GARCH-X, and Realized GARCH frameworks, we propose hybrid models (Baseline and Extended versions) to improve forecasting accuracy. Using daily data from FTSE 100, Nikkei 225, and S&P 500 indices (2000–2020), we compared hybrid models against traditional models. Results show that the Extended LSTM hybrid model outperforms both traditional GARCH-type models and the Baseline LSTM, capturing complex volatility patterns more effectively. The Extended model’s architecture, featuring ReLU, GRU, and dropout layers, mitigates over-smoothing and enhances responsiveness to market fluctuations. This research demonstrates LSTM’s potential to refine volatility forecasting, offering valuable insights for investors and risk managers.
Influence of World Development Indicators on Human Development: A Multiple Linear Regression and PSI Ranking Approach Irvan, Irvan; Zahedi, Zahedi; Nusantara, Badai Charamsar; Romantica, Krishna Prafidya; Siswadi, Siswadi; Nasution, Marah Doly
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 1 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i1.23925

Abstract

This study investigates the influence of World Development Indicators (WDI)on the Human Development Index (HDI) within the regional context of Asiancountries. Understanding the interaction between these indicators and HDIholds strategic relevance for enhancing the formulation of evidence-baseddevelopment policies. The analysis focuses on five key indicators: populationgrowth, voice and accountability, government effectiveness, GDP per capitagrowth, and control of corruption. These variables represent essentialdimensions of governance and socioeconomic advancement. The datasetcomprises information from 46 Asian countries sourced from the World Bank.The methodological framework integrates multiple linear regression to evaluatethe magnitude of each variable’s contribution to HDI. The Preference SelectionIndex (PSI) is utilized to establish a performance-based ranking of countriesgrounded in the selected indicators. Results demonstrate that population growthand government effectiveness have significant impacts on HDI outcomes, whilethe remaining variables exhibit no statistically significant effects. Comparativeanalysis using PSI reveals inconsistencies between development indicator valuesand actual HDI positions. South Korea shows the highest consistency betweenquantitative rankings and HDI classification. These findings offer practicalinsights for policy prioritization by identifying the most influential determinantsof human development in the region. The study emphasizes the importance oftailored development strategies and encourages future research to strengthenmodel robustness through control variable inclusion, sensitivity analysis, andnon-linear modeling approaches.
Geographically Weighted Negative Binomial Regression (GWNBR) Modeling of Tuberculosis (TB) in North Sumatra Ayunda, Afrila; Husein, Ismail; Faigle, Ulrich
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 1 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i1.25006

Abstract

Tuberculosis (TB) remains a serious public health challenge in North Sumatra, Indonesia, necessitating precise statistical modeling to understand its spatial patterns and associated risk factors. This study applies three statistical approaches — Poisson Regression, Negative Binomial Regression (NBR), and Geographically Weighted Negative Binomial Regression (GWNBR) — to investigate the distribution of TB cases across 33 districts and cities in North Sumatra in 2022. An overdispersion test revealed significant variance, indicating the inappropriateness of the Poisson model. The NBR model identified the number of medical personnel as the sole significant covariate, yielding an AIC of 478.31. A Breusch–Pagan test confirmed significant spatial heterogeneity across areas, justifying the use of GWNBR. The GWNBR approach captured spatially varying relationships between TB incidence and covariates, providing more localized insights and yielding an AIC of 512.34. The findings highlight the importance of adopting spatially adaptive methods when modeling disease patterns, allowing for targeted, area-specific public health interventions.
LASSO Quantile Regression for Predictive Modeling of Dengue Hemorrhagic Fever Incidence in Indonesia Arifin, Samsul; Anggraini, Dewi; Susanti, Dewi Sri
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 1 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i1.24877

Abstract

Dengue Hemorrhagic Fever (DHF) is an endemic disease that continues to burden public health in Indonesia, characterized by an uneven pattern of distribution influenced by various environmental, social, and economic factors. This study aims to develop a predictive model for DHF incidence using the LASSO Quantile Regression approach, which can reveal the influence of predictor variables across different quantiles while addressing multicollinearity and overfitting issues. The data used includes nine predictor variables obtained from BPS and BMKG for the year 2025. The estimation results show that the urban/rural Area Size consistently affects all quantiles, while the percentage of population living in poverty and the number of healthcare facilities are significant only at the 0.25 and 0.50 quantiles. Model evaluation indicates that this approach provides good predictive performance, especially at the 0.25 quantile, with a R² pseudo value of 0.2838. These findings suggest that the LASSO Quantile Regression method is effective in identifying the determinants of DHF in Indonesia.
Spatial Modeling of Food Security Index in Central Java Using Mixed Geographically Weighted Regression Chamidah, Nur; Saifudin, Toha; Mahadesyawardani, Arinda; Fauziah, Nathania; Rahayu, Rizky Dwi Kurnia; Siagian, Kimberly Maserati; Wieldyanisa, Ezha Easyfa
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 1 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i1.25044

Abstract

Central Java plays an important role in Indonesia’s food security, ranking second nationally in the 2023 Food Security Index (FSI). However, nearly 45% of its districts/cities fall below the provincial average, reflecting spatial disparities. This study applies the Mixed Geographically Weighted Regression (MGWR) method to model the factors influencing FSI in Central Java by considering global and local spatial heterogeneity. Six clusters were formed based on similar characteristics. The MGWR model identifies that the factor of households not having access to clean water has a global negative effect which contributes 0.1710 points in decreasing the FSI, while population density is the dominant local factor that has a significant negative effect on the FSI in 21 districts/cities, covering approximately 60% of the area in Central Java. The MGWR model using a fixed Gaussian kernel outperforms global regression and GWR, with the lowest AIC, highest (93.11%), and a MAPE of 1.00838%. 
Design and Development of an Information System for Recognition of Endangered Animals in Indonesia Based on Android Using the RAD Method Hasibuan, M. Syahputra; Alda, Muhamad
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 1 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i1.25064

Abstract

The Medan City Ministry of Religion Office is a state ministry that provides Rare animals are animals that are few in number and very rarely found. An animal is said to be rare if its population is decreasing rapidly and the number worldwide is less than 10,000. Natural factors or those influenced by human activities cause animals to become rare and endangered, for example low reproductive rates, insufficient types of food available, habitat destruction, or illegal hunting. From this, there are several problems that can be identified in the introduction of rare and endangered animals in Indonesia. Most people do not know or know about the rare and endangered animals in Indonesia. Apart from that, there is still very little digital media that provides informative and interactive information. This has resulted in a lack of public knowledge about rare and endangered animals. Therefore, the aim of this research is to build an Android-based information system to make it easier for the public to obtain information on endangered animals in Indonesia. The system development method used is the Rapid Application Development (RAD) method which consists of planning stages, design workshops and implementation. Meanwhile, the tool used by the author in creating information system designs visually is UML (Unified Modeling Language). This Android-based information system was built using Kodular tools and the Firebase database. With this information system, it is hoped that it can help the public obtain information regarding endangered animals in Indonesia easily and quickly via Android cellphones.
Design and Development of Social Assistance Applications Mobile-Based Using Extreme Programming (XP) Methods at the Ministry of Religion of Medan City Nababan, Yusuf Walhadi Rama Putra; Alda, Muhamad
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 2 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i2.25063

Abstract

The Medan City Ministry of Religion Office is a state ministry that provides social assistance services to the community. In carrying out the distribution of social assistance to the community, the Medan City Ministry of Religion Office has not yet provided a system, so the distribution and recording process is still carried out conventionally. In distributing social assistance zakat, the Ministry of Religion still records each aid recipient in a book, so there are still problems in terms of searching for data which takes a long time, data damage, data loss and the possibility of entering the same data (data redundancy). Therefore, the aim of this research is to build a mobile-based application to make it easier to record and monitor the distribution of social assistance to the community. The system development method used is the Extreme Programming (XP) method which consists of the Planning, Design, Coding and Testing stages. Meanwhile, the tool used by the author in creating information system designs visually is UML (Unified Modeling Language). This mobile-based application was built using Android Studio tools and a MySQL database. With this application, it is hoped that it can help the Medan City Ministry of Religion Office to record and monitor the distribution of social assistance to the community easily and quickly via Android cellphones.

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