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Jurnal Statistika Universitas Muhammadiyah Semarang
Published by Universitas Muhammadiyah Semarang
ISSN : 23383216     EISSN : 25281070     DOI : -
Core Subject : Science,
Decision Sciences, Operations Research & Management
Focus and Scope a. Statistika Teori, Statistika Komputasi, Statistika terapan b. Matematika Teori dan Aplikasi c. Design of Experiment
Arjuna Subject : Matematika - Pemodelan dan Simulasi
Articles 205 Documents
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COMPARISON OF THE KAPLAN-MEIER METHOD AND THE TARONE-WARE TEST BASED BY GENDER ON STUNTING DATA AT PUSKESMAS LEGOK Naufal Fadhlullah; Asthagina Delia Putri; Wiwik Wiyanti
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 14, No 1 (2026): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.14.1.2026.22-31

Abstract

Stunting is one of the problems of acute malnutrition due to the consumption of unnutritious food for a long period, at least the first 1000 days of life. Biological differences between males and females can be a risk in the detection of stunting time. Therefore, this study was conducted to determine whether there is a significant difference in the detection time of stunting in male and female toddlers at Puskesmas Legok. Comparison data between groups by sex were analyzed using Kaplan-Meier and Tarone-Ware test. The results of the study showed that there was a significant difference in the detection time of stunting in toddlers based on gender. The average stunting detection time in female toddlers is longer than in male toddlers. The Tarone-Ware test also showed significant results with a Chi-Square value of 7.802 and p = 0.005. therefore, this study reveals that there are differences in the time of stunting detection based on gender.
CLUSTERING OF REGENCIES IN WEST KALIMANTAN BASED ON FINANCIAL RATIOS USING THE AVERAGE LINKAGE METHOD Hazwani Dhiya' Atiq Viatmaja; Annisa Auliarahmi; Gabriella Simarmata
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 14, No 1 (2026): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.14.1.2026.43-60

Abstract

Regional financial management serves as a crucial framework for assessing fiscal viability and the impact of policies on development. In West Kalimantan, identifying patterns in budget performance is essential to support targeted financial policy decisions, particularly regarding fiscal solvency and flexibility. This study aims to group regencies in West Kalimantan based on budget ratios derived from the 2024 Audited Examination Result Reports and evaluate the quality of the formed clusters. The research employs a quantitative descriptive method using Hierarchical Cluster Analysis with the Average Linkage approach and Manhattan distance. Five financial ratios were analyzed across twelve regencies, with cluster validity tested using Silhouette, Davies-Bouldin, and Dunn indices. The results indicate that the optimal number of clusters is two. Cluster 1 consists solely of the Bengkayang Regency, characterized as an outlier with an extremely high financial independence ratio, indicating strong fiscal autonomy. Cluster 2 comprises the remaining eleven regencies, characterized by low financial independence and high dependency on central government transfers, despite demonstrating relatively good revenue effectiveness. The study concludes that significant fiscal disparity exists in West Kalimantan. These findings suggest that policy planning should focus on enhancing local revenue generation and fiscal independence for the majority of regencies to approach optimal performance.
FORECASTING THE NUMBER OF BREAST CANCER AMONG WOMEN IN INDONESIA BASED ON TIME SERIES MODELS Wulanova Romadhona; Syasya Qonita Azizah; Vivin Vivin
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 14, No 1 (2026): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.14.1.2026.61-70

Abstract

Breast cancer is one of the leading causes of death among women in Indonesia, requiring a mathematical prediction model to support health policy and planning. This study uses two time series forecasting methods with an autocorrelation approach, namely Autoregressive Integrated Moving Average (ARIMA) and Exponential Smoothing State Space (ETS), to predict the number of new breast cancer cases among women in Indonesia. The data used is secondary data from Gapminder for the period 1990-2021 and analyzed using accuracy metrics such as AIC, BIC, RMSE, MAE, and MAPE. The best ARIMA model obtained was ARIMA (0,2,2), with AIC (358.16) and BIC (362.37) values, as well as smaller RMSE and MAE values compared to the ETS (M,A,N) model. Diagnostic results showed good model fit with ARIMA model residuals being white noise. The forecast results for 2022-2031 show a consistent upward trend in the number of cases, from around 26,218 cases in 2022 to 20,616 cases in 2031. These findings confirm that the ARIMA model is effective in capturing long-term linear patterns and can be used as a basis for formulating strategies for the prevention and early detection of breast cancer in Indonesia.
APPLICATION OF BINARY LOGISTIC REGRESSION WITH TIME BASED SAMPLING IN ANALYSIS OF RISK FACTORS FOR MOTORCYCLE TRAFFIC VIOLATIONS IN MEDAN CITY Graceya Zagita Manik; Irgie Attaurrazaq; Donni Ramadhan Siregar; Katrin Jenny Sirait
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 14, No 1 (2026): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.14.1.2026.32-42

Abstract

Traffic violations by motorcyclists are a major contributor to accidents in Medan City. This research sought to examine the frequency of violations and the factors affecting the likelihood of such violations among riders at three intersections in Medan City: Dr. Mansyur, Setia Budi, and Fly Over Jamin Ginting. A cross-sectional quantitative design and time-based sampling was used. Observations were conducted over three days in two sessions (daytime 02:00–03:00 PM and afternoon 04:00–05:00 PM WIB), with a sample of 540 motorcyclists. The dependent variable was violation status; independent variables included gender, motorcycle type, rider status, and observation time. Binary logistic regression was applied. Results showed a violation rate of . Simultaneously, all independent variables had a significant effect (p<0.001). Partially, only rider status was significant (p<0.001; OR=2.728), meaning riders with a passenger were 2.789 times more likely to violate than solo riders. Gender, motorcycle type, and observation time were not significant. The model fitted well (Hosmer–Lemeshow test, ). In conclusion, rider status is the main factor, so supervision should focus on riders with passengers.
ASSESSING CLUSTER VALIDITY AND STABILITY OF HIERARCHICAL WARD’S LINKAGE AND NON-HIERARCHICAL K-MEANS ON THE EBGS INDEX OF REGENCIES/MUNICIPALITIES IN SOUTH SULAWESI Elisabeth Evelin Karuna; Mahrani Mahrani; Atiqa Azza El Darman
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 14, No 1 (2026): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.14.1.2026.01-21

Abstract

Abstract: Cluster analysis is a statistical method used to group objects based on similar characteristics. In general, there are two main categories in cluster analysis, namely hierarchical methods (such as Ward's linkage) and non-hierarchical methods (such as K-Means). This study aims to compare the performance of these two methods in grouping the Electronic-Based Government System (EBGS) Index of districts/cities in South Sulawesi Province. The results of the analysis show that both methods produce identical validity index values, namely a Silhouette Coefficient of 0.67, a Davies-Bouldin Index (DBI) of 0.39, and a Calinski-Harabasz Index (CHI) of 83.02. These values indicate that the clusters formed have high internal compactness and clear separation between clusters. In addition, the Adjusted Rand Index (ARI) value of 1.00 indicates perfect agreement between the results of Ward's linkage and K-Means, signifying a very high level of stability. Thus, the results of this study show that the grouping of the SPBE Index in South Sulawesi is valid, stable, and able to represent the natural structure of the data consistently. Keywords:Cluster; K-Means; Ward's Linkage; Validity; Stability; EBGS

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