cover
Contact Name
Muhammad Yahya Matdoan
Contact Email
keepyahya@gmail.com
Phone
+6282193229395
Journal Mail Official
jurnalparameter@gmail.com
Editorial Address
Jl. Ir. M. Putuhena, Poka-Ambon, 97233, Maluku, Indonesia
Location
Kota ambon,
Maluku
INDONESIA
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 98 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.
Exploring the Determinants of Behavioral Intention and Use Behavior Toward TikTok Shop Based on the UTAUT 2 Model Muin, Rizki Fitriani; Otok, Bambang Widjanarko
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 5 No 1 (2026): 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/parameterv5i1pp29-44

Abstract

The rapid growth of social commerce through TikTok Shop has opened new opportunities for businesses and consumers in Indonesia, including in the city of Ambon. This study aims to analyze the factors influencing consumers’ behavioral intention and use behavior in shopping on TikTok Shop by applying the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) model. The respondents of this research were TikTok Shop users in Ambon who had made at least one transaction, with a minimum sample size of 200 participants. The results show that all UTAUT 2 constructs, except for facilitating conditions on use behavior, have a significant effect on consumers’ intention and usage behavior. The variable behavioral intention was found to be the most dominant factor driving actual usage behavior, with R² values of 0.753 for behavioral intention and 0.817 for use behavior, indicating a strong predictive capability of the model. These findings affirm the relevance of the UTAUT 2 model in explaining technology adoption in the context of social commerce and provide practical implications for platform developers and digital business practitioners to design marketing strategies that align with the characteristics of consumers in eastern Indonesia. Keywords: UTAUT 2, TikTok Shop, Behavioral Intention, Use Behavior, Social Commerce, PLS-SEM.
Cluster Analysis on Time Series Data for Indonesian Stock Prices Using Dynamic Time Warping Saputra, Wisnowan Hendy; Shehu, Nuruddeen
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 5 No 1 (2026): 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/parameterv5i1pp01-16

Abstract

This study investigates the application of the Dynamic Time Warping (DTW) algorithm to cluster the ten stocks with the largest market capitalization on the Indonesia Stock Exchange as of February 2026. Unlike conventional distance metrics, DTW handles time lag nonlinearly to identify hidden temporal pattern similarities. Adjusted closing price data was obtained through web scraping from Yahoo Finance using the R programming language. The clustering procedure was performed using Ward's Hierarchical Agglomerative Clustering method, where the optimal number of clusters was determined through Silhouette coefficient analysis. The results indicate that a three-cluster solution is the most representative structure. The first cluster is dominated by the banking and energy sectors with stable growth trends. The second cluster includes cyclical industrial and infrastructure stocks with high volatility. The third cluster uniquely unites GOTO and UNVR stocks in a long-term bearish downward pattern, despite their origins in different sectors. These findings demonstrate that DTW is highly effective in uncovering cross-sector market dynamics, providing a more accurate basis for portfolio diversification strategies than traditional business sector classifications.
Two-Stage Estimation in Copula-Based Bivariate Survival Models with Cox Marginals Rahmawati, Wahyu Dwi; Purnomo, Jerry Dwi Trijoyo; Otok, Bambang Widjanarko
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 5 No 1 (2026): 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/parameterv5i1pp17-28

Abstract

This study is motivated by the presence of dependence between event times in bivariate survival data, which cannot be adequately captured by univariate Cox models. A copula-based bivariate survival model with Cox Proportional Hazards marginals is considered. The estimation procedure follows a two-stage approach, where marginal parameters are first obtained using partial likelihood and the baseline survival function is estimated via the Breslow method. In contrast to conventional approaches that treat marginal estimates as final or impose shared parameter structures, this study introduces a modification in the second stage by performing simultaneous joint estimation of marginal and dependence parameters using the BHHH algorithm. This allows the marginal parameters to be estimated while explicitly accounting for the dependence between event times. Simulation results show that the proposed method produces stable and reliable parameter estimates while preserving the interpretability of marginal effects, providing a flexible framework for modeling dependent bivariate survival data.

Page 10 of 10 | Total Record : 98