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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 222 Documents
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Evaluating Double Resampling through Simulation and Application in Semiparametric Truncated Spline for Waste Economic Value Hidayat, Kamelia; Fernandes, Adji Achmad Rinaldo; Iriany, Atiek; Hidayatulloh, Moh. Zhafran
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 3 (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.v9i3.26773

Abstract

This study developed a double resampling procedure as a method for estimating standard error in truncated spline semiparametric path modeling, given that standard error cannot be obtained analytically. Primary data were collected from 100 respondents through a Likert scale questionnaire and analyzed using a path structure involving Facility and Infrastructure Quality and Waste Bank Participation have a significantly positive effect on 3R-Based Waste Management Practices and the Waste Economic Value . The modeling process involved selecting knots, estimating spline functions, and evaluating double resampling performance through simulation studies. The results showed that and had a significant positive effect on and , while the relationship between and was negative before and after the 21% threshold. The simulation study shows that the Jackknife-Bootstrap method produces lower standard errors and bias, while the Bootstrap-Jackknife method is more stable at very small sample size. These findings confirm the effectiveness of double resampling.
Sentiment Analysis of Indonesia's Free Nutritious Meal Program on Platform X (Formerly Twitter) Using IndoBERT Muhabbab, Adiba Zahriyah; Bunyamin, Bunyamin; Hasmawati, Hasmawati
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 3 (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.v9i3.27629

Abstract

Public sentiment toward government programs is increasingly expressed through social media, necessitating robust quantitative evaluation methods. This study examines public sentiment toward Indonesia's Free Nutritious Meal (Makan Bergizi Gratis/MBG) program using 7,958 manually annotated Indonesian-language posts from platform X (January-August 2025), consisting of 3,752 positive, 848 negative, and 3,358 neutral tweets. Sentiment classification was conducted using IndoBERT-base-P2 and compared with a Support Vector Machine (SVM) baseline with TF-IDF features, employing class-weighted learning to address data imbalance. Model performance was evaluated using accuracy and macro F1-score, followed by paired-sample statistical testing. IndoBERT-base-P2 achieved 92% accuracy and a macro F1-score of 0.90, outperforming SVM (86% accuracy, macro F1 = 0.83). Paired t-test results indicate that this improvement is statistically significant (p < 0.05), confirming the robustness of transformer-based modeling. This study contributes methodologically by integrating contextual language modeling, imbalance-aware optimization, and inferential statistical validation within a unified sentiment analysis framework, demonstrating the quantitative advantage of transformer-based approaches for Indonesian social media policy analysis.
A Modified Frequency-Based FLRG Fuzzy Time Series Model for National Rice Production Forecasting Brata, Adika Setia; Lestari, Windy; Rahmawati, Suci; Jayantara, Dimas
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 3 (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.v9i3.26441

Abstract

Accurate predictions of national rice production are crucial for food sustainability, yet data fluctuations pose a major challenge. This study aims to improve forecasting accuracy by developing a modified Fuzzy Time Series (FTS) model that simplifies the Fuzzy Logical Relationship Group (FLRG) by retaining only the logical relationships with the highest frequency of occurrence. Monthly Indonesian rice production data from January 2018 to March 2025 were used to test this model. To assess the effectiveness of this modification, the model's performance was compared with Chen's conventional FTS models of orders 1 to 3 through MAD, RMSE, and MAPE. Results indicate that the modified third-order FLRG achieved the best accuracy (MAD = 196,410; RMSE = 271,774; MAPE = 5.46%), while reducing FLRG complexity by 10.84%. This demonstrates that FLRG simplification effectively captures longer seasonal dependencies while reducing computational complexity. Nevertheless, the model's sensitivity to sudden structural changes underscores the need for adaptive or probabilistic FLRG enhancement, with hybrid mechanisms as a potential complement. Overall, the proposed approach provides an efficient decision-support tool for maintaining food supply stability and guiding data-driven agricultural policy in Indonesia.
Does Technology Adoption Mediate the Determinant Factor of MSMEs Competitive Advantage? Abbas, Bakhtiar; Hakim, Abdul; Pratama, Muhammad Faried
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 3 (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.v9i3.27539

Abstract

This study explores the effect of human resource competence, entrepreneurial orientation, and also social capital on MSMEs competitive advantages mediated by technology adoption. This study employed a quantitative approach, utilizing a survey method to collect data from respondents. MSME actors in Kendari, Southeast Sulawesi were being population in this research. Purposive sampling was used to choose the 150 MSME actors that made up the research sample. This research uses data analysis with the Partial Least Square (PLS) approach assisted by SmartPLS. The analysis results indicate that human resource competence, entrepreneurial orientation, and also social capital significantly and positively affect MSMEs competitiveness. However, technology adoption does not significantly affect MSMEs competitive advantage in Kendari, Southeast Sulawesi. Technology adoption is able to strengthen mediate the effect of human resource competence and entrepreneurial orientation on MSMEs competitiveness. However, it does not mediate the relationship between social capital and MSMEs competitiveness. This research contributes to the theoretical framework of MSMEs competitive advantage by integrating technologies challenges to the MSMEs sector. The study provides practical insights for MSME emphasizing the need should be more informed with competence and strategic concerns.
Implications of Age-Based Clustering for Survival and Relapse-Free Analysis in METABRIC Breast Cancer Azhari, Alif; Mauliddin, Mauliddin
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 3 (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.v9i3.26030

Abstract

Cox proportional hazards models are widely used for breast cancer survival analysis, but their validity is often limited by violations of the proportional hazard assumption. Machine learning techniques offer potential ways to improve model robustness, yet their combined use remains underexplored. This study aims to compare the proportional hazard assumptions fulfilment and the discriminatory ability of the models before and after age-based clustering. K-medoids was selected for its robustness to outliers. The results demonstrate that clustering significantly improved adherence to the proportional hazards assumption and increased the concordance index, indicating better predictive performance. Number of variables satisfying the assumption increased from 3 in the global model to 5-6 across clusters. Tumor size and positive lymph nodes consistently had a significant effect on all clusters for both survival time and relapse-free time. These findings suggest that age-based clustering can enhance the robustness and predictive performance of Cox models.
Adaptive Learning in Higher Education: A Stochastic Modeling Approach Revealing Absorbing States and Dominant Adaptive Parameters Simanjuntak, Ruth Mayasari
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 3 (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.v9i3.26991

Abstract

This study evaluates the effectiveness of adaptive learning methods using an integrated stochastic modeling framework. Empirical analysis based on real data from 30 students, and stochastic simulation-based analysis (DTMC, Monte Carlo, Sobol, and HBM) used for modeling, probabilistic validation, and parameter sensitivity exploration. A Discrete-Time Markov Chain was applied to model transitions in learner ability, and Monte Carlo simulation was used to validate the probabilistic behavior. The Sobol sensitivity method identified the dominant parameters, while Hierarchical Bayesian Modeling accounted for inter-student variability. The findings show consistent upward transitions, with no students regressing to lower ability states and those in the High category remaining in an absorbing state. Sensitivity analysis indicates that adaptivity level (α) has the strongest influence on performance improvement, followed by difficulty ratio (λ) and feedback frequency (β). The Bayesian model explains more than 70% of the variance in learning gains. Overall, the study concludes that stochastic modeling provides a robust framework for evaluating adaptive learning systems and demonstrates that well-designed adaptive mechanisms significantly enhance student performance, with engagement measured through system interaction logs.
Transportation Infrastructure Optimization for Enchancing Disaster Preparedness in The Sepaku Semoi Dam Emergency Plan (EAP) Yulfadli, Zony; Tukimun, Tukimun; Putri, Friska Feronica Bn; Beg, Abul Hashem
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 3 (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.v9i3.25562

Abstract

This study examines the optimization of evacuation routes within the Emergency Action Plan (EAP) for the Sepaku Semoi Dam in East Kalimantan, Indonesia, through the application Analytical Hierarchy Process (AHP). The analysis was based on three key criteria : accesibility (0.45), road capacity ( 0.30) and physical resilience (0.25). The evaluation was carried out utilizing expert questionnaires (n = 80), field surveys, and secondary data, which encompassed HEC-RAS flood simulations and the official Emergency Action Plan (RTD) document. The results underscore the Silkar-Bukit Raya-Petung corridor (A1) as the most reliable evacuation route, succeeded by the Trans Kalimantan Road (A2) and the Southern Ring Road (A3), whereas the Karang Jinawi-Sotek Road (A4) plays a supplementary role for areas with high population density. Furthermore, two additional routes (A5 and A6) are suggested as qualitative extensions to the network, which are not part of the AHP ranking, aimed at enhancing spatial coverage for underserved communities. The estimation of the evacuation fleet suggests that around 23,700 residents would need transportation in the event of a dam failure. The combination of AHP with spatial and survey-based data establishes a systematic and replicable framework for prioritizing evacuation routes in the context of dam-related disaster preparedness.
Classifying Alumni Satisfaction in Integrity Zone Universities Using CART: Evidence from Indonesian Higher Education Nurhasanah, Nurhasanah; Baqtini, Eka; Ramadhani, Evi; Salwa, Nany; Siregar, Latifah Rahayu
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 3 (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.v9i3.26769

Abstract

This study examines alumni satisfaction within the Integrity Zone framework in Indonesian higher education using survey data collected from 315 alumni out of a total population of 1,483 graduates. Alumni satisfaction was dichotomized into satisfied and dissatisfied groups and analyzed using the Classification and Regression Tree (CART) method to identify the most influential service related factors. The results indicate that employee sincerity, service timeliness, completeness of information, adequacy of facilities, and institutional transparency particularly the availability of anti-corruption information are the key determinants of alumni satisfaction. The CART model achieved an Area Under the Curve (AUC) value of 0.73, indicating fair discriminative ability according to standard classification guidelines. These findings provide practical insights for improving service quality and integrity-oriented governance in higher education institutions.
Modeling Monthly Rainfall Data Using the Alpha Power Transformed X-Lindley Distribution in the Toba Lake Region Najib, Mohamad Khoirun; Nurdiati, Sri; Khatizah, Elis; Firdawanti, Aulia Rizki; Irwandi, Hendri; Azhari, Mirza Farhan; Martal, David Vijanarco; Abisha, Nicholas
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 3 (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.v9i3.25692

Abstract

Modeling rainfall is crucial for hydrological studies and climate adaptation, especially in regions with complex topography such as the Toba Lake area, North Sumatra. Classical probability distributions often struggle to represent skewness, heavy tails, and variability observed in tropical rainfall. This study explores APTXL distribution as a flexible two-parameter model. Through the alpha power transformation, APTXL extends the X-Lindley distribution by introducing an additional shape parameter, allowing better accommodation of asymmetrical and extreme values while maintaining analytical tractability. Statistical properties are derived, and parameters are estimated using maximum likelihood. The model is applied to a long-term dataset from 13 meteorological stations, covering 408 monthly observations per station. Comparative analysis against Gamma, Lognormal, and Generalized Extreme Value distributions using multiple goodness-of-fit criteria indicates that APTXL provides consistently improved performance. These results suggest APTXL as a practical tool for rainfall modeling and water-resource applications in climate-sensitive regions.
Comparative Performance of Spatial Robust Small Area Estimation Methods: A Simulation Study Arianingsih, Baiq Dian; Sadik, Kusman; Indahwati, Indahwati
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 3 (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.v9i3.26477

Abstract

Estimating parameters for small areas often faces limitations due to insufficient sample sizes, resulting in low-precision estimates. The Small Area Estimation (SAE) approach is used to address this problem by utilizing auxiliary variables to improve estimation efficiency. This study evaluates four SAE methods, namely EBLUP, REBLUP, SEBLUP, and SREBLUP, through a simulation study based on a nested error model across 18 scenarios that combine two area sizes (16 and 64 areas), levels of outlier contamination in the error component, and degrees of spatial correlation in the area-level random effects. Each scenario is replicated 50 times. Model performance is evaluated using Relative Bias (RB) and Relative Root Mean Square Error (RRMSE). The results show that non-robust methods are sensitive to outliers, whereas robust methods produce more stable estimates. The SREBLUP method demonstrates the best performance under low to moderate spatial correlation. In addition, an ANOVA test is conducted to identify factors that significantly affect the response.

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