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ComTech: Computer, Mathematics and Engineering Applications
Published by Universitas Bina Nusantara
ISSN : 20871244     EISSN : 2476907X     DOI : -
Core Subject : Science, Education, Engineering,
Computer Science & IT Engineering Mathematics
The journal invites professionals in the world of education, research, and entrepreneurship to participate in disseminating ideas, concepts, new theories, or science development in the field of Information Systems, Architecture, Civil Engineering, Computer Engineering, Industrial Engineering, Food Technology, Computer Science, Mathematics, and Statistics through this scientific journal.
Arjuna Subject : -
Articles 6 Documents
 1 
Search results for , issue "Vol. 16 No. 1 (2025): ComTech" : 6 Documents clear
A Data Mining Approach to Understanding Financial Literacy Knowledge and Behavioral Patterns among Tertiary Students Usita, Maricris M.; Luriban, Virgie Liza
ComTech: Computer, Mathematics and Engineering Applications Vol. 16 No. 1 (2025): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v16i1.12221

Abstract

The research sought to data mine the financial literacy of tertiary students to evaluate and pinpoint deficiencies in their financial knowledge, measure the degree of financial goal-setting and budgeting practices, and determine their primary sources of financial advice. The data were gathered through validated questionnaires and disseminated through surveys. The research focused on tertiary students with 316 valid responses for analysis. The research used data mining techniques under the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology to identify students’ financial literacy. Furthermore, a comprehensive analysis using Ms Excel, Statistical Package for Social Sciences (SPSS), and Waikato Environment for Knowledge Analysis (WEKA) reveals significant disparities in financial literacy among various fields of study and course levels. The investigation highlights essential financial behaviors, such as credit card utilization, saving patterns, and budgeting strategies, while revealing deficiencies in formal financial education. The analysis highlights the necessity for specialized financial literacy initiatives in educational programs to bridge knowledge deficiencies and encourage proficient budgeting and goal-setting techniques. The results offer practical guidance for educators, policymakers, and higher education institutions to improve students’ financial well-being, in line with Sustainable Development Goals (SDGs) focused on poverty alleviation and economic development. The research advocates for financial literacy programs in the school curriculum and emphasizes enhancing student participation in workshops. Higher education institutions must provide well-structured financial advice and support services. Lastly, Future studies should delve deeper into socioeconomic factors to improve predictive models and intervention strategies.
Optimizing Quality Attributes of Piper Retrofractum Vahl. Through Partial Least Squares Regression: Insights from Pretreatment and Drying Experiments with Fruit Peel Infusions Lumintu, Ida
ComTech: Computer, Mathematics and Engineering Applications Vol. 16 No. 1 (2025): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v16i1.12246

Abstract

The research aimed to optimize the quality attributes of Piper retrofractum Vahl.—piperine content, color brightness, and water content—using Partial Least Squares Regression (PLSR) to evaluate the pretreatment effects with fruit peel infusions and drying conditions. The research urgency lied in addressing the challenges of achieving consistent product quality while promoting sustainable food processing practices. Around 30 samples of Piper retrofractum Vahl. were subjected to varying pretreatment concentrations, soaking durations, drying durations, and peel types (orange and pineapple). The PLSR model was employed to identify key factors influencing the quality attributes and assess predictive performance based on Root Mean Squared Error (RMSE) and Coefficient of Determination (R²) values. As a result, the PLSR model explains 43.22% of the variance in piperine content, highlighting the importance of shorter soaking durations and higher pretreatment concentrations in preserving piperine levels. For water content, the model captures 75.08% of the variance, emphasizing the critical role of drying duration in reducing moisture. However, the color brightness model explains only 18.5% of the variance, indicating the need to explore contributing factors further. The research introduces the innovative use of fruit peel-infused water as a sustainable pretreatment method, contributing to eco-friendly food processing practices and offering practical insights into optimizing production for improved product quality. The findings underscore the importance of balancing pretreatment and drying parameters to address inconsistencies in quality while promoting sustainability. Future research should expand experimental conditions, integrate additional variables, and explore advanced modeling techniques to enhance predictive accuracy and product quality.
Implementation of Decision Tree with Best Subset Approach to Identify Suicide Cases in Central and East Java Choiri, Moh. Miftahul; Nurdiansyah, Denny; Rokhim, Auliyaur; Patmawati, Pebriana Putri; Pebriani, Putri Vatria
ComTech: Computer, Mathematics and Engineering Applications Vol. 16 No. 1 (2025): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v16i1.12265

Abstract

The research was conducted to determine the descriptive statistics of suicide cases and classify suicide cases based on the attributes of victims who made suicide attempts. The research design used was a quantitative method in the form of exploratory research using the Decision Tree method. The research novelty was applying the Decision Tree method with the Best Subset approach. The research data sources were obtained from online mass media news such as DetikJatim and DetikJateng for suicide attempt cases from January 2022 to July 2024. The research finds significant differences in the number of suicide attempts in East Java and Central Java, with Surabaya, Malang, Blitar, Semarang, and Klaten recording higher numbers. The findings show that males more often attempt suicide, while females more often experience failed attempts. Young adults (20−39 years) record the highest rate, and hanging is the most common method. Unknown mental disorders and depression are the main risk factors, with many attempts occurring without rescue. The implication is that improving emergency response systems and mental health services is essential. The research recommends strengthening mental health and social support for older adults and those under stress. Then, enhancing rapid rescue efforts with comprehensive psychological interventions is essential for suicide prevention. The originality of the research lies in the use of a Decision Tree with the Best Subset approach to identify suicide patterns based on risk factors and methods used.
The Implementation of the Fuzzy C-Means Method in Handling Outlier Data in the 2021 Village Potential Data of Bengkulu Province Panjaitan, Intan Juliana; Indahwati, Indahwati; Afendi, Farit Mochamad
ComTech: Computer, Mathematics and Engineering Applications Vol. 16 No. 1 (2025): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v16i1.12274

Abstract

Clustering groups aims to ensure similarity within clusters and disparity between them. The research evaluated the Fuzzy C-Means method’s effectiveness in clustering large datasets containing outliers, focusing on the 2021 Village Potential data from Bengkulu Province. The dataset, comprising 1,514 observations from villages and urban villages, provided a comprehensive resource for understanding regional development. Outliers, a common challenge in cluster analysis, were detected using univariate and multivariate methods, revealing substantial variability. PCA was applied, improving clustering quality to address multicollinearity among variables. In the results, the fuzzifier (w) parameter in the FCM method plays a crucial role in controlling the degree of membership for data points in clusters, which can potentially reduce the impact of outliers, enhancing clustering robustness and accuracy. The FCM method effectively produces clusters with high intra-cluster homogeneity and inter-cluster heterogeneity. Using the Elbow method, three optimal clusters are identified. Cluster 1, dominated by villages in Bengkulu City, is the most advanced, with superior infrastructure and services, but the fewest villages business units, necessitating economic empowerment. Cluster 2, comprising villages in North Bengkulu Regency, demonstrates moderate development but suffers from poor transportation access, requiring improvements to support socio-economic activities. Cluster 3, dominated by villages in Kaur Regency, is the least developed, with limited basic services and infrastructure, highlighting the need for substantial investments in governance and essential services. These findings provide actionable insights for village development in Bengkulu Province, supporting targeted policies tailored to each cluster’s unique characteristics.
Comparative Analysis of Reconciliation Techniques: Bottom-Up, Top-Down, and MinT for Product Forecasting in Retail SMEs Rambing, Danni; Kusumaningrum, Retno; Sugiharto, Aris
ComTech: Computer, Mathematics and Engineering Applications Vol. 16 No. 1 (2025): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v16i1.12293

Abstract

Small and Medium Enterprises (SMEs) have experienced rapid growth, contributing approximately 95% to the global economy, 60% to global employment, and 50% to global GDP. This growth is accompanied by significant challenges, with approximately 70% of SMEs failing within the first three years, primarily due to poor inventory management. It emphasizes the crucial role of accurate demand forecasting for SMEs, particularly in the retail sector, where time series at various levels of hierarchical structure exhibit different scales and display diverse patterns. However, most existing research on demand forecasting for SMEs focuses on a single hierarchical level—either bottom, middle, or top—without addressing the entire hierarchy. The research sought to address this gap by forecasting across all hierarchical levels and evaluating different reconciliation techniques to generate coherent and accurate forecasts for multiple products in retail SMEs. The ETS state space model was used as the base forecasting model. This model was widely recognized as a benchmark in forecasting competitions. The reconciliation methods assessed were Bottom-Up, Top-Down based on historical proportions (average proportions), Top-Down based on forecast proportions, and Minimum Trace (MinT) (Ordinary Least Squares (OLS), OLS Non-Negative (OLS Non-Neg), Weighted Least Squares (WLS), and WLS Non-Negative (WLS Non-Neg)). The evaluation results show that the OLS Non-Negative method, with an average SMAPE value of 35.335%, produces more accurate reconciliation than other methods. In addition, this method also outperforms the base model with an increase in accuracy of 13%.
Designing School Building Maintenance Priorities Using the Cost-User Effectiveness Ratio Purwosri, Visaretri Pramuktia; Prasetyo, Hari; Solikin, Mochamad; Harnaeni, Senja Rum; Sunarjono, Sri
ComTech: Computer, Mathematics and Engineering Applications Vol. 16 No. 1 (2025): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v16i1.12385

Abstract

Prioritizing school building maintenance solely based on structural damage often leads to inefficient budget allocation and fewer beneficiaries. The research introduced an integrated Cost-User Effectiveness Ratio (CUER) to establish maintenance priorities by combining three critical factors: damage severity, maintenance costs, and the number of affected students. The CUER formulation employed the Geometric Mean or the root mean multiplication of the cost effectiveness and user effectiveness ratio to balance these factors systematically. The methodology encompassed several steps, including damage assessment and calculation of component importance weights using the Analytical Hierarchy Process (AHP), to determine integrated damage levels, costs, and student weights. These inputs were subsequently used to generate priority rankings of schools requiring maintenance. As a result, the case study in Wonogiri Regency illustrates the superiority of the proposed method over the conventional method. While the conventional approach prioritizes 27 schools benefiting 2,442 students, the CUER approach prioritizes 33 schools benefiting 2,957 students, demonstrating increased efficiency and broader impact. The CUER-based model presents a systematic and equitable solution to prioritize school building maintenance, ensuring the optimal allocation of resources and maximizing benefits within existing budgetary constraints. This innovative approach addresses current challenges in maintenance planning and offers significant implications for improving the management of educational infrastructure.

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