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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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Forecasting Patchouli (Pogostemon Cabin Benth) Production in North Kolaka Using ARIMA, LSTM and Hybrid ARIMA-LSTM Bakhtiar, Sri Muslihah; Fajar, Nurhikmah
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.v9i2.25920

Abstract

Patchouli (Pogostemon cablin Benth.) is one of Indonesia’s most economically valuable essential oil commodities. This study forecasts patchouli production using ARIMA, LSTM, and a hybrid ARIMA–LSTM model, emphasizing the novelty of applying machine learning techniques to essential oil production forecasting, an understudied area. Weekly production data from ARS Atsiri North Kolaka (January 2022–July 2025, 187 records) were analyzed. ARIMA was applied to capture linear patterns, LSTM to model nonlinear dynamics, and the hybrid model to combine both characteristics. Model performance was evaluated using MSE, RMSE, and MAPE. The ARIMA (2,1,1) model performed best among the linear approaches, while LSTM with normalization, windowing, and 50 hidden units achieved the highest overall accuracy (MSE = 251.22, RMSE = 321.67, MAPE = 0.238%). The hybrid model did not outperform LSTM, likely due to the limited dataset and the dominance of nonlinear patterns, thus confirming LSTM as the most effective model.
A Spatio-Temporal Panel Data Model for Coronavirus Deaths: Evidence from Europe Rusyana, Asep; Fitrianto, Anwar; Marzuki, Marzuki
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.v9i2.25933

Abstract

The spatial panel data model is a model in which the independent variables are estimated to be influenced by place, time, and explanatory variables. Almost all countries have been attacked by the coronavirus, starting in China in February 2020. Some of the affected residents died, some recovered, and some are still under surveillance. This study aims to identify the most accurate model with the response variable of population deaths due to coronavirus and the independent variables of the number of cases with coronavirus and the number of tests. This study uniquely compares multiple spatial models for pandemic analysis. The four models are SAR, SEM, GSM, and Temporal Spatial Panel Data. The fourth model enables more accurate analysis of COVID-19 mortality by capturing both spatial and temporal dependencies. As a result, the spatial temporal panel data model is the best model with a coefficient of determination of 63.9%.
Optimal Control of Cardiovascular Disease Using Pontryagin’s Maximum Principle Diana, Arista Fitri; Soraya, Tarita Intan; Khumaeroh, Mia Siti; Hajar, Muhammad Ibnu
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.v9i2.25849

Abstract

Cardiovascular disease poses serious global health and economic challenges. This study develops a dynamic model by adapting the infectious-disease SEIR framework to a non-communicable disease context and extending it with a hospitalized compartment. Three control strategies: curative intervention (u1), lifestyle modification (u2), and preventive screening–education (u3) are incorporated and optimized using Pontryagin’s Maximum Principle. Numerical simulations, calibrated with data from Rinkendiknas, World Health Organization, National Health Insurance program, BMC Public Health, National Library of Medicine, and RS Roemani Muhammadiyah Semarang, show that curative control rapidly reduces early case burden, while lifestyle modification and education sustain long-term declines. With combined controls, the exposed, infected, and hospitalized compartments decrease by 10%, 20,8%, and 7,4%, respectively, while costs are reduced by 28,5% compared to single interventions. The integration of epidemiological models, health-system dynamics, and multi-control optimization offers both methodological novelty and practical value for cost-effective cardiovascular disease policy design.
Modeling E-Payment Adoption and its Impact on MSME Financial Inclusion in North Kolaka Bohari, Nurul Aulia; Firdaus, Firdaus; Puspita, Ulva Mega
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.v9i2.25921

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a crucial role in Indonesia’s economic development; however, the adoption of e-payment systems in North Kolaka Regency remains relatively low. This study aims to model and analyze the adoption dynamics of e-payment among MSMEs using an SEIR (Susceptible–Exposed–Infected–Recovered) framework. Based on survey data from 485 MSMEs, simulations were conducted using Python to determine the spread and sustainability of adoption behavior. The results reveal that a majority of MSMEs are still unfamiliar with e-payment systems, while the proportion of active users remains limited. The numerical simulation yields a basic reproduction number of R₀ = 0.4939, indicating that e-payment adoption has not yet reached a sustainable level. To enhance the growth of e-payment usage and strengthen financial inclusion, policy strategies should focus on improving digital financial literacy, providing continuous incentives, and integrating MSMEs into broader go-digital programs.
Predicting Malaria Incidence Using LSTM and Environmental Variables Sulistijanti, Wellie; Khikmah, Laelatul; Rahmasari, Erisa Adyati; Sangnandha, Cikal Arbitan Putra; Yusuf, Idan Maulana; Azizah, Dzahari Alikharimah
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.v9i2.26043

Abstract

Climate change is exacerbating malaria risk in Indonesia, especially in Papua. This study proposes a Bidirectional Long Short-Term Memory (LSTM) model to forecast malaria incidence using climate variables. The dataset comprises monthly malaria and climate records (rainfall, temperature, humidity) from four high-endemic provinces between 2014 and 2024. Key methodologies included data augmentation to address data imbalances and a grouped time-series cross-validation for robust model evaluation. An ARIMA model was implemented as a validation baseline to benchmark the proposed approach. The Bi-LSTM model delivered superior performance, achieving an average test R² of 0.7210 and SMAPE of 11.02%. the model demonstrated excellent generalization with no evidence of overfitting, significantly outperforming the ARIMA baseline. The findings validate the use of deep learning models as effective tools for public health surveillance, providing reliable early warnings to support timely interventions. Future work will apply SHAP interpretability techniques and expanding the model's geographic scope.
Development of a Mathematical Model for the Optimization of Natural Resources in Villages Faturohman, Ikhsan; Hilmi, Yugi
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.v9i2.26131

Abstract

This study integrates Linear Programming (LP) and Geographic Information System (GIS) to optimize land and water resource utilization in Indonesian rural areas. The proposed multi-period LP model aims to maximize farmers’ net profit under land, water, and labor constraints, where decision variables represent the land area (in tumbak) allocated to each crop per period. Conducted in three agricultural villages of Garut Regency with 60 farmer respondents selected through stratified sampling, the model was solved using Excel Solver and spatially visualized through GIS. Results show an optimal cultivated area of 453.202 tumbak, utilizing 16,412.49 m³ of water and 5,319.098 man-days of labor, producing Rp 2,078,047,500 in gross revenue and Rp 26,493,556 in net profit. Land-use efficiency improved by 64.8% from baseline conditions, with land as the main binding constraint. The model offers a practical decision-support tool for policymakers to plan crop rotation, irrigation scheduling, and sustainable land-use strategies.
Classification of Numeracy Achievement of Junior High School Educational Units Based on National Assessment Data using Random Forest Pramesti, Angelin Ica; Murwaningtyas, Chatarina Enny
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.v9i2.26156

Abstract

This study classifies numeracy achievement in Indonesian junior high schools using 2023 National Assessment data from 11,399 schools. The Random Forest algorithm was applied because it is able to capture nonlinear relationships and complex interactions between heterogeneous predictors, while simultaneously reducing variance through bagging and out-of-bag validation techniques. Two models were developed, one without and one with literacy variables. The addition of literacy increased accuracy from 82.97% to 90.0% and increased the ROC-AUC value from 0.8986 to 0.9609. Based on Gini importance, literacy was the most influential predictor, followed by religiosity, learning experience, gender equality, and class size. Government policies need to integrate literacy and numeracy improvements within a unified curriculum framework and promote gender equality and contextual learning in schools. Furthermore, utilizing data-driven analysis from the National Assessment is crucial for guiding targeted interventions and equitable resource allocation for numeracy improvement.
Polygon Area Board Game for Building Thinking Skills in Area Conservation and Measurement Karlimah, Karlimah; Lidinillah, Dindin Abdul Muiz; Supriadi, Supriadi; Apriani, Ika Fitri; Insani, Sofi Mutiara
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.v9i2.26017

Abstract

This study aimed to develop a board game to enhance fifth-grade students’ understanding of area concepts and the law of conservation of area in polygons. The research employed the ADDIE model, covering analysis, design, development, implementation, and evaluation stages. Expert validation and classroom trials were conducted to assess validity, practicality, and effectiveness. The results showed that the board game achieved a validity score of 89% (very feasible) and improved students’ test performance by 23%. Students exhibited high engagement and active participation during learning activities. The study highlights the importance of integrating design elements such as layout, color, and illustration to support conceptual understanding. It concludes that well-designed board games can effectively foster critical thinking and motivation in elementary mathematics learning.
GSTAR (1;1) Transfer Function Model for Forecasting Chili Prices with Rainfall Effect Yundari, Yundari; Rahmawati, Asri; Pratiwi, Yuyun Eka
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.v9i2.26119

Abstract

Chili price fluctuations are strongly influenced by climate variability, distribution inefficiencies, and spatial. The ARIMA–TF and GSTARX models can address these issues. However, GSTARX is generally limited to linear responses of exogenous variables, while ARIMA–TF does not capture spatial heterogeneity. This study proposes an integration of the GSTAR and Transfer Function approaches. This model combines spatial-temporal dependencies with the external factors such as rainfall. The modeling process begins with GSTAR modeling, followed by parameter estimation of the transfer function using the Marquardt algorithm. The data used are rainfall and chili prices in three locations in West Kalimantan. The model data estimation results show very good accuracy, with MAPE values of 15%, 8%, and 14%. These results confirm that rainfall is a crucial factor influencing chili price variations and demonstrate the reliability of GSTAR–TF in forecasting agricultural commodities in the face of climate variability.
Routh-Hurwitz Stability Analysis of the Predator-Prey Model with Prey Population Harvesting in Polluted Aquatic Ecosystems Fiska, Nissa; Ikhwan, Muhammad; Nurmaulidar, Nurmaulidar; Askal, Oky
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.v9i2.26061

Abstract

Environmental pollution and overharvesting are critical external factors that disrupt predator–prey balance in aquatic ecosystems. This study develops a two-dimensional nonlinear predator–prey model incorporating both toxicity and harvesting. Local stability is analyzed using the Routh–Hurwitz criterion, and findings are validated through numerical simulations under varied initial conditions. The system yields four equilibria: E0, E1 and E1 are unstable extinction states, while the interior equilibrium E*= (0.4146, 1.0899) is locally stable, with Tr(J)=-1.3052 and det(J)=0.4177. Stability is preserved as long as the combined toxicity–harvesting parameter remains below approximately 4.1-4.2 day-1. The novelty of this work lies in explicitly quantifying threshold effects of harvesting and toxicity, showing that coexistence is achievable under moderate external pressures. These results highlight that sustainable management requires keeping exploitation and pollution below critical thresholds to ensure long-term persistence of both prey and predator.

Page 17 of 19 | Total Record : 184

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