Journal of Mathematics and Scientific Computing With Applications
Journal of Mathematics and Scientific Computing With Applications is a broad-based journal covering all branches of computational or applied mathematics with special encouragement to researchers in theoretical computer science and mathematical computing. It covers all major areas, such as numerical analysis, discrete optimization, linear and nonlinear programming, theory of computation, control theory, theory of algorithms, computational logic, applied combinatorics, coding theory, cryptographic, fuzzy theory with applications, differential equations with applications. Journal features research papers in all branches of mathematics that have some bearing on the application to scientific problems, including areas of actuarial science, mathematical biology, mathematical economics, and finance.
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<![CDATA[PERFORMANCE ASSESMENT EVALUATION EMPLOYEES USING METHOD SIMPLE MULTI ATTRIBUTE RATING TECHNIQUE (SMART) AT THE MEDAN FINANCIAL TRAINING CENTER ]]>
<![CDATA[Wira Afandi , Fikry]]>;
<![CDATA[Deasy]]>;
<![CDATA[Alifiah, Nasya]]>;
<![CDATA[Citra Amanda]]>;
<![CDATA[Ratna Sari, Desi]]>
<![CDATA[ Journal of Mathematics and Scientific Computing With Applications Vol. 6 No. 2 (2025) ]]>
Publisher : <![CDATA[Pena Cendekia Insani ]]>
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DOI: 10.53806/jmscowa.v6i2.1126
<![CDATA[Employee performance assessment is one of the important aspects to achieve the goals of an institution. With the application of information technology, a decision support system can be used to provide assessments. One method that can be used to provide employee performance assessments is the SMART (Simple Multi Attribute Rating Technique) method. This method was chosen because of its superiority in being able to solve problems using multicriteria so it is suitable for determining employee performance assessments at the Medan Financial Training Center. The criteria used in determining employee performance assessments at the Medan Financial Training Center are Discipline, Responsibility, Leadership, Innovation, Competence. Data collection was carried out using questionnaires distributed to employees at the Medan Financial Training Center. The results of the study from 20 data samples using the SMART method obtained ranking results from employee performance assessments ranging from very good assessments with a final value of 1 to very poor with a final value of 0.025.]]>
<![CDATA[EFFICIENCY ANALYSIS OF PALM OIL INVENTORY CONTROL AT PTPN IV USING MONTE CARLO SIMULATION ]]>
<![CDATA[Devitasari]]>;
<![CDATA[Yani Sitompul, Apri]]>;
<![CDATA[Cintya Hasmi Pohan, Dian]]>;
<![CDATA[Indriyani Ningsih, Fani]]>;
<![CDATA[Filia Sari, Rina]]>
<![CDATA[ Journal of Mathematics and Scientific Computing With Applications Vol. 6 No. 2 (2025) ]]>
Publisher : <![CDATA[Pena Cendekia Insani ]]>
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DOI: 10.53806/jmscowa.v6i2.1146
<![CDATA[Uncontrolled palm oil inventory can increase operational costs and disrupt production flow. This study aims to validate the effectiveness of the Monte Carlo simulation method in predicting the total palm oil inventory costs at PT. Perkebunan Nusantara IV. Unlike conventional approaches that ignore uncertainty, this study uses Monte Carlo simulation to model cost variability based on historical data from January to December 2024. The simulation process is performed by generating random numbers using the Linear Congruential Generator (LCG) method and determining the probability distribution from historical data. The simulation is run once using the probability distribution obtained from 12 months of historical data. The simulation results show a predicted total inventory cost of Rp 918.117.054.635.00, lower than the actual cost of Rp 919.958.281.123.00, resulting in a potential savings of Rp 1.841.226.488.00. To measure the reliability of the Monte Carlo simulation results, a MAPE calculation was performed by comparing the simulation results with actual data. The calculation results show that the MAPE value is 0.2%. These findings prove that Monte Carlo simulation not only improves forecasting accuracy but also empirically supports more optimal decision-making in inventory management and efficient stock level determination.]]>
<![CDATA[APPLICATION OF WEIGHT PRODUCT AND TOPSIS METHODS IN SELECTING THE BEST ONLINE TRANSPORTATION SERVICE ]]>
<![CDATA[Nur Fitriani]]>;
<![CDATA[Hamidah Nasution]]>;
<![CDATA[Ismail Husein]]>;
<![CDATA[Hashem Beg, Abul]]>
<![CDATA[ Journal of Mathematics and Scientific Computing With Applications Vol. 6 No. 2 (2025) ]]>
Publisher : <![CDATA[Pena Cendekia Insani ]]>
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DOI: 10.53806/jmscowa.v6i2.1206
<![CDATA[This study emphasises the application of mathematical and computational modelling to support multi-criteria decision-making in the selection of online transportation services. Using Microsoft Excel, the research employs the Weighted Product (WP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods to assess alternatives based on six quantitative criteria: price, promotion, service variety, payment method, convenience, and punctuality. The integrated application of WP and TOPSIS provides a systematic process of normalisation, weighting, and ranking to determine the optimal alternative. The findings indicate that GOJEK achieves the highest preference value (0.6107), followed by GRAB (0.5533), IN-DRIVE (0.5000), and MAXIM (0.3893). The methodological contribution of this research lies in demonstrating how the integration of WP and TOPSIS within computational tools establishes an effective mathematical framework for optimising decision-making in service evaluation.]]>
<![CDATA[IMPLEMENTATION OF PRINCIPAL COMPONENT ANALYSIS (PCA) IN DIMENSION REDUCTION BASED ON INDONESIAN HEALTH DATA ]]>
<![CDATA[Rangkuti, Siti Rafiah]]>;
<![CDATA[Fadhillah, Nurul]]>;
<![CDATA[Sari, Rita Novita]]>;
<![CDATA[Klause Roder]]>
<![CDATA[ Journal of Mathematics and Scientific Computing With Applications Vol. 6 No. 2 (2025) ]]>
Publisher : <![CDATA[Pena Cendekia Insani ]]>
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DOI: 10.53806/jmscowa.v6i2.1313
<![CDATA[Indonesian health data for 2024 has multidimensional characteristics with a large number of interconnected variables, leading to high complexity in the analysis and visualization process. This complexity poses a challenge in generating information that is easy to understand and can support data-driven decision-making. This research aims to implement the Principal Component Analysis (PCA) method as a technique for dimension reduction and visualization of Indonesian health data. The research method used is a quantitative approach with descriptive-exploratory secondary data analysis. The research stages include data pre-processing, PCA implementation, principal component determination, variable contribution analysis, and data visualization using scatter plots and biplots. The research results show that PCA is able to significantly reduce the number of variables while still retaining most of the main information contained in the data. Principal component analysis-based visualization produces clearer and more easily interpretable patterns and structures in health data. Thus, PCA has proven effective in simplifying the complexity of national health data and supporting the presentation of more informative and actionable information for decision-making in the health sector.]]>
<![CDATA[GRAPH INTERPRETATION OF IRREDUCIBLE, REDUCIBLE, PERIODIC, AND APERIODIC PROPERTIES IN MARKOV CHAINS ]]>
<![CDATA[Suci Rachmadini, Haliza]]>;
<![CDATA[Muhammad, Faisal]]>;
<![CDATA[Razvan Serban]]>
<![CDATA[ Journal of Mathematics and Scientific Computing With Applications Vol. 6 No. 2 (2025) ]]>
Publisher : <![CDATA[Pena Cendekia Insani ]]>
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DOI: 10.53806/jmscowa.v6i2.1331
<![CDATA[Markov chains are widely used stochastic models for describing dynamic systems whose future states depend only on short-term probabilistic transitions. Key structural properties irreducibility, reducibility, periodicity, and aperiodicity are crucial for understanding long-term behavior, particularly the existence and stability of stationary distributions. Traditionally, these characteristics are determined through analysis of the transition probability matrix; however, this approach can be computationally demanding and difficult to interpret for large systems. This study explores an alternative representation using directed graphs, where each state is modeled as a node and each positive transition probability as a directed edge. The approach connects irreducibility with strong graph connectivity, while reducibility corresponds to the presence of separate communication classes. Periodicity and aperiodicity are identified through the structure of cycles and the greatest common divisor of return path lengths. The results demonstrate that graph-based analysis provides clearer and more intuitive framework for examining structural properties of Markov chains.]]>
<![CDATA[BINARY LOGISTIC REGRESSION ANALYSIS OF ENVIRONMENTAL AND SOCIODEMOGRAPHIC DETERMINANTS FOR CHILDHOOD STUNTING ]]>
<![CDATA[Khikmah, Laelatul]]>;
<![CDATA[Ashari, Ayu]]>;
<![CDATA[Ambarwati, Atika Nurani]]>;
<![CDATA[Priyandhini, Vania Putri]]>;
<![CDATA[Natonegoro, Muhammad Alif]]>
<![CDATA[ Journal of Mathematics and Scientific Computing With Applications Vol. 6 No. 2 (2025) ]]>
Publisher : <![CDATA[Pena Cendekia Insani ]]>
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DOI: 10.53806/jmscowa.v6i2.1400
<![CDATA[This study analyzed the influence of regional disparities, environmental factors, and sociodemographic characteristics on stunting risk among children under five in Central Java. A cross-sectional design utilized secondary data from 73,358 children, which were evaluated through binary logistic regression to identify multiple risk factors. The results revealed that children residing in urban areas exhibited 1.73 times higher odds of stunting (95% CI: 1.27–2.36, p < 0.001). Unsafe non-drinking water access emerged as the most significant predictor, increasing stunting odds by 2.30 times (95% CI:1.56–3.37, p < 0.001). Conversely, parental education, employment status, and toilet availability showed no statistically significant associations with the outcome in this cohort. The study concluded that structural environmental challenges in urbanized settings outweighed individual sociodemographic factors. These findings highlight the necessity for targeted urban-specific sanitation strategies and improved water quality for daily household hygiene to effectively mitigate stunting prevalence and support regional health development targets.]]>
<![CDATA[ANALYSIS OF THE COMPOSITION OF TWO PLANE ISOMETRIES: TRANSLATION, REFLECTION, AND ROTATION USING A LINEAR ALGEBRA APPROACH ]]>
<![CDATA[Pramudya, Ikrar]]>;
<![CDATA[Saputra, Bagus Aqil]]>;
<![CDATA[Kurniawati, Ira]]>
<![CDATA[ Journal of Mathematics and Scientific Computing With Applications Vol. 6 No. 2 (2025) ]]>
Publisher : <![CDATA[Pena Cendekia Insani ]]>
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DOI: 10.53806/jmscowa.v6i2.1410
<![CDATA[Geometric transformation is a branch of mathematics that focuses on the transformation (bijective function) of geometric objects in a plane or transformation in . One of the topics discussed in geometric transformation is the properties of the composition of two isometries. Generally, topics in geometric transformation are studied using an axiomatic geometry approach that requires strong geometric visualization skills. This research aims to study the composition of two isometries through an alternative approach, specifically linear algebra. The study focuses on deriving the properties of the composition of two isometries, namely translations, reflections, and rotations, while considering their algebraic forms. The research methodology employed is literature study and deductive reasoning in accordance with mathematical syllogism. The results of this research are theorems that state the properties of the composition of two isometries. Based on the findings of this study, it can be concluded that the properties of the composition of two isometries can be derived using a linear algebra approach.]]>
<![CDATA[ENHANCING USER ENGAGEMENT IN DESA DIGITAL INDONESIA (DDI) KMS THROUGH GAMIFICATION DIGITAL NUDGES ]]>
<![CDATA[Hutauruk, Dzakiyyah Hasbi]]>;
<![CDATA[Nurhadryani, Yani]]>;
<![CDATA[Mardiana, Rina]]>
<![CDATA[ Journal of Mathematics and Scientific Computing With Applications Vol. 6 No. 2 (2025) ]]>
Publisher : <![CDATA[Pena Cendekia Insani ]]>
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DOI: 10.53806/jmscowa.v6i2.1422
<![CDATA[This study examined how digital nudges integrated with gamification could improve user engagement in Desa Digital Indonesia (DDI) KMS. Using a user-centered design approach, the research was conducted in two iterative cycles involving user testing and interviews with 5 and 20 participants from rural backgrounds. An iterative process involving two design cycles was conducted, including user analysis, prototype development, and evaluation. The initial evaluation involved five participants and revealed that leaderboard and badge features were generally acceptable but less effective in collaborative contexts. Based on these findings, the design was refined by introducing collaborative elements and small incentives, including achievement titles and promotional rewards. The second evaluation showed improved user acceptance, with all participants preferring the new design, and the incentive-based feature receiving the highest positive rating (90%). The findings indicate that combining competitive, collaborative, and incentive-based nudges leads to more effective and contextually relevant user engagement in rural systems.]]>
<![CDATA[SERVICE QUALITY ANALYSIS OF CAMPUS-BASED MOTORCYCLE TAXI (GOPUS): AN INTEGRATED SERVQUAL–IPA–PGCV APPROACH ]]>
<![CDATA[Dinda Renata Cecilia]]>;
<![CDATA[Rina Filia Sari]]>;
<![CDATA[Rini Halila Nasution]]>
<![CDATA[ Journal of Mathematics and Scientific Computing With Applications Vol. 6 No. 2 (2025) ]]>
Publisher : <![CDATA[Pena Cendekia Insani ]]>
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DOI: 10.53806/jmscowa.v6i2.1423
<![CDATA[This study evaluates the service quality of GOPUS, an informal,WhatsApp-based campus ride-hailing service at UINSU, Indonesia. Using a quantitative approach, data were collected from 100 student respondents via Likert-scale questionnaires assessing expectations andperceptions across five SERVQUAL dimensions. After validity and reliability screening, 16 items remained for analysis. The SERVQUALgap analysis, Importance-Performance Analysis (IPA), and PotentialGain in Customer Value (PGCV) index were applied to identify improvement priorities. Results reveal a negative service gap across keyattributes, with five indicators falling into IPA Quadrant I (ConcentrateHere). PGCV prioritizes driver service satisfaction (P GCV = 5.95) andtraining (P GCV = 3.75) for immediate intervention. The findings provide actionable recommendations for enhancing operational standards,safety, and user satisfaction in informal campus transport systems.]]>
<![CDATA[DETERMINATION OF ELIGIBILITY FOR RECEIVING THE FAMILY HOPE PROGRAM ASSISTANCE USING THE EVALUATION BASED ON DISTANCE FROM AVERAGE SOLUTION (EDAS) METHOD ]]>
<![CDATA[Br Pohan, Dian Cinta Hasmi]]>;
<![CDATA[Husein, Ismail]]>;
<![CDATA[Sari, Rina Filia]]>
<![CDATA[ Journal of Mathematics and Scientific Computing With Applications Vol. 6 No. 2 (2025) ]]>
Publisher : <![CDATA[Pena Cendekia Insani ]]>
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DOI: 10.53806/jmscowa.v6i1.1424
<![CDATA[This study proposes a decision support framework for determining eligibility for Indonesia’s Program Keluarga Harapan (PKH) using the Evaluation Based on Distance from Average Solution (EDAS) method. Seven criteria derived from national social welfare policy were weighted using the Analytic Hierarchy Process (AHP), achieving a consistency ratio of 0.038. The model was applied to 98 household alternatives in Air Merah Village. The resulting assessment scores ranged from 0.0119to 0.7866. A Monte Carlo sensitivity analysis with 5,000 iterations under ±10% ±15% weight perturbations yielded a high Spearman rank correlation (rho = 0.91,95% CI [0.89, 0.93]), indicating strong ranking stability. The EDAS results showed 78% agreement with manual village selection and 80% alignment within the top-20 priority group. The proposed framework reduces subjectivity and improves transparency in beneficiary selection. Limitations include the cross-sectional design and single-location data. The model is scalable and suitable for broader policy implementation.]]>
