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Muhammad Yahya Matdoan
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Parameter: Jurnal Matematika, Statistika dan Terapannya
Published by Universitas Pattimura
Core Subject : Education,
Parameter: Jurnal Matematika, Statistika dan Terapannya is an open access journal (e-journal) published since April 2022. Parameteris published by Department of Mathematics, Faculty of Science and Mathematics, Pattimura. Parameterpublished scientific articles on various aspects related to mathematics and statistics and its application. Articles can be in the form of research results, case studies, or literature reviews.
Articles 95 Documents
Energy Use vs Staff Performance at Soekarno Hatta: Partial Least Squares Structural Equation Modeling and Importance Performance Map Analysis Approach Muchtar, Mc Ali; Rimawan, Erry; Amin, Mawardi
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 4 No 3 (2025): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv4i3pp485-496

Abstract

This study investigates the operational impact of four key infrastructure systems (HVAC, lighting, electrical equipment, and internal transport) on staff performance at Terminal 3 of Soekarno-Hatta International Airport. Despite consuming 86.59% of the terminal’s energy, HVAC systems show no statistically significant contribution to staff performance. In contrast, lighting, electrical equipment, and internal transport significantly improve staff productivity, with internal transport having the highest influence. A structural equation modeling approach using PLS-SEM and Importance-Performance Map Analysis (IPMA) was employed to analyze data from 400 respondents. The model yielded strong explanatory (R² = 0.613) and predictive relevance (Q² = 0.505), validating its robustness. Findings suggest that energy management in airport terminals should shift from consumption-based to performance-based prioritization, favoring infrastructure investments that directly enhance operational efficiency.
Forecasting Regional Economic Growth Using TVARX: Model Accuracy Evaluation in Banten Province Vega, Amelia; Fajar, Muhammad; Prayitno, Hendro; Afrianus, Erya
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 4 No 3 (2025): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv4i3pp551-562

Abstract

Forecasting regional economic performance is essential for supporting timely and responsive policy planning. This study aims to forecast the Gross Regional Domestic Product at constant prices (GRDP) in Banten Province for the second to fourth quarters of 2025 using the Time-Varying Autoregressive model with Exogenous Variables (TVARX). The model incorporates household final consumption expenditure, gross fixed capital formation, exchange rates, and export values as exogenous variables. Model performance was evaluated by comparing combinations of training-testing data proportions (90:10, 80:20, 70:30, and 60:40) and two estimation approaches (local constant and local linear), using the Mean Absolute Percentage Error (MAPE) as the predictive accuracy metric. All variables were transformed into logarithmic form and differenced to ensure stationarity. The results indicate that the model using a 90:10 data split and the local linear estimation approach yielded the most accurate prediction, with the lowest MAPE value of 0.6%. The best-performing model was then applied to forecast out-of-sample GRDP CP for the next three quarters, with its year-on-year growth subsequently analyzed. These findings are expected to serve as a basis for data-driven economic analysis and support macroeconomic planning that is responsive to short-term structural dynamics.
Monitoring and Evaluation of Clinker Quality Using T2 Hotelling-Generalized Variance Control Chart Aisha, Dinda Fitri Nur; Inayatulloh, Faza; Ahsan, Muhammad; Wibawati, Wibawati
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 4 No 3 (2025): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv4i3pp471-484

Abstract

The cement industry is an important sector in infrastructure development, where the quality of clinker determines the final quality of the product. This study evaluates the application of T² Hotelling's and Generalized Variance (GV) multivariate control charts to clinker data based on three main variables: FCaO, C₃S, and C₃A at PT XYZ. The results show that C₃S has the highest variance in phase I and II (2.61 and 2.53), while FCaO has the lowest variance (0.10 and 0.06). All three variables had mean values within the specification limits, although there were still extreme values outside the limits. Assumption tests showed that the data was not multivariate normally distributed, but it was still assumed to be normal for control analysis purposes. In the wet season, the standard deviation decreased from 1.552 to 1.252, and in the dry season from 1.170 to 1.029, indicating a decrease in variability although the process is not yet fully under statistical control. Capability analysis shows that the dry season process is more stable, with most parameters having multivariate values that exceed the threshold. Compared to the wet season, the dry season process showed more consistent performance and was able to meet production quality standards.
Enhancing Rainfall Forecasting Performance in Bandung City Using Bi-LSTM with Grid Search Optimization on Gregorian and Lunar Calendar Data Yunizar, Mahdayani Putri; Talakua, Andrew Hosea; Darmawan, Gumgum
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 4 No 3 (2025): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv4i3pp595-601

Abstract

Rainfall is a climatic factor that strongly influences human activities and plays a crucial role in decision making related to water resources, mobility, and disaster preparedness. High rainfall intensity may escalate into hydrometeorological hazards, underscoring the importance of accurate rainfall forecasting to support early warning and mitigation efforts. This study aims to compare the forecasting accuracy of monthly rainfall predictions between the Gregorian and lunar calendars using the Bidirectional Long Short-Term Memory (Bi-LSTM) model optimized through a grid search approach. The method is designed to capture temporal patterns arising from the distinct structures of two asynchronous calendars. Daily rainfall data from Bandung City, Indonesia, covering the period from 2000 to 2025, were converted into monthly series in both calendar systems. The results reveal that the Gregorian calendar provides significantly better forecasting performance, achieving the lowest MAPE value of 11.60 percent at the three-month horizon. In contrast, the lunar calendar shows higher variability and reaches its best MAPE of 31.43 percent at the same horizon. These findings indicate that the Gregorian calendar offers a more stable temporal representation for rainfall forecasting in Bandung and supports improved predictive modeling for climate-related decision making.
Comparing Weighting Schemes in Modeling Child Malnutrition in East Java Alfasanah, Zulfani; Otok, Bambang Widjanarko; Ahsan, Muhammad
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 4 No 3 (2025): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Partial Least Squares is increasingly used as an alternative to covariance-based SEM due to its flexibility in handling non-normal data, small sample sizes, and complex models, as well as its ability to operate under different inner weighting schemes. However, empirical studies rarely compare these weighting schemes, even though they may influence measurement validity and structural interpretations. This study applies PLS-SEM using both the path and factor weighting schemes to evaluate their performance in modeling child malnutrition. Child malnutrition remains a major public health concern, as it is driven by the interaction of socioeconomic, food security, parenting, and access to basic services. The study estimates and evaluates measurement and structural models using PLS under path and factor schemes. The findings show that both schemes produce acceptable measurement and structural models, but the path scheme yields more consistent indicator significance and more stable structural relationships, while the factor scheme is more sensitive to weaker indicators, leading to some nonsignificant loadings and paths. The results suggest that although both weighting schemes are suitable for exploratory analysis, the path weighting scheme provides more robust and interpretable results for explaining child malnutrition, highlighting the importance of weighting scheme selection in applied PLS-SEM research.

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