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RAGAM: Journal of Statistics and Its Application
Published by Universitas Lambung Mangkurat
ISSN : -     EISSN : 29628539     DOI : https://doi.org/10.20527/ragam.vXXX
Core Subject : Economy, Humanities, Health, Science, Education,
Humanities Computer Science & IT Economics, Econometrics & Finance Mathematics Public Health
RAGAM Journal publishes scientific articles in the field of statistics and its applications, including: * Biostatistics * Parametric and nonparametric statistics * Quality control * Econometrics and business * Industrial statistics * Time series analysis * Spatial statistics * Data mining * Computational statistics * Applications of statistics in the medical, economic, social, environmental, industrial, technological, and other related fields
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 6 Documents
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Search results for , issue "Vol 4, No 2 (2025): RAGAM: Journal of Statistics " : 6 Documents clear
PEMETAAN PERSEBARAN PENDERITA DEMAM BERDARAH DENGUE MENGGUNAKAN SISTEM INFORMASI GEOGRAFIS DI KABUPATEN BANTUL TAHUN 2024 Sulistyo, Andhy
RAGAM: Journal of Statistics & Its Application Vol 4, No 2 (2025): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v4i2.16808

Abstract

AbstractBackground: Dengue Hemorrhagic Fever (DHF) remains a major public health problem with fluctuating incidence in Indonesia, including Bantul District. In 2024, 672 DHF cases were reported, a sharp increase compared to 135 cases in the previous year. This situation highlights the need for spatial analysis to better understand the disease distribution and support effective control strategies.Objective: This study aims to map the distribution of DHF cases in Bantul District in 2024 and analyze spatial patterns using Geographic Information Systems (GIS).Methods: A descriptive quantitative study with a case study approach was conducted. The population consisted of all reported DHF cases in 2024 obtained from the Bantul District Health Office, including patient residential coordinates. Spatial analysis was performed using ArcGIS 10.3. Global Moran’s I was applied to assess spatial autocorrelation, the Average Nearest Neighbor (ANN) method was used to determine distribution patterns, and the Central Feature tool identified the central point of case concentration.Results: The analysis revealed that DHF cases were significantly clustered, as indicated by a positive Moran’s I value (p<0.05) and an ANN index <1. The central feature analysis showed that case concentrations were mainly located in the working areas of Pleret and Imogiri II primary health centers.Conclusion: The distribution of DHF cases in Bantul District in 2024 is not random but clustered in specific areas. These findings provide crucial evidence for prioritizing targeted interventions such as fogging, community education, and more focused source reduction programs. Keywords: DHF,GIS,ANN, Moran’s I,Bantul
PEMODELAN REGRESI BERGANDA UNTUK FAKTOR-FAKTOR YANG MEMPENGARUHI KEPUTUSAN PEMBELIAN PRODUK IMPLORA MENGGUNAKAN PLATFORM TIKTOK SHOP DI PURWAKARTA Apriani, Farida
RAGAM: Journal of Statistics & Its Application Vol 4, No 2 (2025): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v4i2.16903

Abstract

The cosmetics industry in Indonesia is experiencing rapid growth and has managed to dominate the domestic market, so many cosmetic brands continue to innovate, including the Implora brand. Implora is a cosmetic that can be reached by all strategists looking to be known, namely promotions that use the tiktok shop application. Tiktok shop presents an innovative "Shoppertainment" concept by combining the uniqueness of the TikTok platform, especially entertaining and engaging content, with direct shopping features. This study aims to find out and conduct modelling to determine the influence of social media marketing, product quality, and consumer trust on the purchase of Implora cosmetic products on the TikTok Shop. This study uses primary data in the form of a questionnaire with sampling techniques, namely random and purposive sampling. The respondents are 191 students university in Purwakarta. The method used was descriptive analysis and multiple linear regression; the model obtained using α=0.05, namely  Y=-1.154+0.077X1+0.399X2+0.725X3 with a determination coefficient value of 85.8%. The dominance of the age who buy this product is 19-24 years old and the variables that have a significant influence from this study are product quality and consumer trust, but the social media marketing variables are still maintained, the existence of these findings can provide a more focused strategy direction for implora products to strengthen product quality and build trust while still utilizing social media such as tiktokshop to expand wide marketingT
Penerapan Model Kredibilitas Bühlmann Pada Data Frekuensi Klaim Asuransi Kendaraan Bermotor Di Indonesia Yang Berdistribusi Poisson-Amarendra Maharani, Aliya; Mutaqin, Aceng Komarudin
RAGAM: Journal of Statistics & Its Application Vol 4, No 2 (2025): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v4i2.16591

Abstract

In motor vehicle insurance, policyholders are required to pay a premium to the insurance company. One method to assist insurance companies in determining premiums is credibility theory. One model from this approach is the Bühlmann credibility model. Generally, claim frequency data is overdispersed. There are various distributions suitable for addressing overdispersion, one of which is the Poisson-Amarendra distribution. The method used to estimate the parameters of the Poisson-Amarendra is the maximum likelihood method. The research material used is motor vehicle insurance data in Indonesia for the year 2019, recorded by PT. X, categorized into 8 categories and 3 regions. The results of the Chi-Square goodness-of-fit test show that the claim frequency data from the population distributed by the Poisson-Amarendra distribution includes category 2 in region 1 and category 6 in region 3. The results of applying the Bühlmann credibility model yield a credibility factor of 0.0029 for category 2 in region 1 and 0.0101 for category 6 in region 3. The estimated average claim frequency for motor vehicle insurance in the next period for category 2 in region 1 is 0.0029. This means that if the number of insurance policyholders in 2020 is the same as in 2019, which is 15,878, an estimated 46 partial loss claims will occur. The estimated average claim frequency for category 6 in region 3 is 0.0102, with an estimated 44 partial loss claims occurring in 2020, assuming the number of policyholders in 2020 remains the same as in 2019, which is 4,313.
COMPARISON OF SIX NORMAL DISTRIBUTION PARAMETER ESTIMATION METHODS: MONTE CARLO SIMULATION STUDY WITH COMPREHENSIVE EVALUATION Sihombing, Pardomuan Robinson
RAGAM: Journal of Statistics & Its Application Vol 4, No 2 (2025): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v4i2.17104

Abstract

Estimating normal distribution parameters is one of the fundamental problems in statistics that has attracted the attention of researchers for more than two centuries. This study aims to analyse and compare the performance of six normal distribution parameter estimation methods, which include Method of Moments (MoM), Maximum Likelihood Estimation (MLE), Least Squares Estimation (LSE), Bayesian Estimation, Percentile Matching, and Generalised Method of Moments (GMM), through a systematic and comprehensive approach. The methodology of this study combines rigorous theoretical mathematical derivation for each estimation method with empirical evaluation through extensive Monte Carlo simulations. Each method was derived mathematically from the basic principle to the final estimator formula, then implemented in a simulation with 500 replications on various sample sizes, i.e. n = 30, 50, 100, and 200, of the normal distribution of N (5, 4). In small samples with n = 30, Percentile Matching showed the highest MSE for   parameter estimation with a value of 0.162, while MoM, MLE, and LSE showed the best performance with MSE for μ parameter of 0.127 and MSE for parameter 0.067. The main conclusions of this study show that MLE provides an optimal balance between statistical accuracy and computational efficiency for most practical applications. Bayesian Estimation shows good stability at all sample sizes and is superior when informative prior information is available. 
Analisis Regresi Panel terhadap Faktor-Faktor yang Mempengaruhi Tingkat Kemiskinan di Kalimantan Selatan Tahun 2018-2022 Irawan, Ade; Wati, Herlina; Salam, Nur; Asianingrum, Al Hujjah
RAGAM: Journal of Statistics & Its Application Vol 4, No 2 (2025): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v4i2.15871

Abstract

This study aims to analyze the effects of population growth rate, Human Development Index (HDI), and per capita expenditure on poverty levels in 13 regencies/cities of South Kalimantan Province during the period 2018–2022. The study uses secondary data obtained from the Central Bureau of Statistics and applies panel data regression using the Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM). Model selection was conducted using the Chow test, Breusch–Pagan Lagrange Multiplier test, and Hausman test, as well as considering variable significance and model explanatory power. The results indicate that the Fixed Effect Model with time effects (FEM-time) is the most appropriate model. Initial estimation results show that population growth rate and per capita expenditure have significant negative effects on poverty, while HDI has a significant positive effect. However, after applying robust standard errors to address autocorrelation and heteroskedasticity, only per capita expenditure remains statistically significant. These findings suggest that improvements in household purchasing power play a central role in reducing poverty in South Kalimantan, while the impacts of demographic and human development factors tend to vary over time. This study is expected to provide empirical evidence to support more adaptive and region-specific poverty alleviation policies.
WILCOXON RANK-SUM HYPOTHESIS TESTING OF MILITARY BUDGETS AS A PERCENTAGE OF GROSS DOMESTIC PRODUCT AND GOVERNMENT SPENDING Susdarwono, Endro Tri; Wiranta, Alma
RAGAM: Journal of Statistics & Its Application Vol 4, No 2 (2025): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v4i2.17181

Abstract

This study aims to describe the policy of determining military budget size as a percentage of Gross Domestic Product (GDP) and government spending in countries in Asia, Oceania, and Africa. The approach used in this study is descriptive quantitative. The data used are national defense allocations published by SIPRI. Data analysis used a hypothesis test with a Wilcoxon rank sum. This study concluded that for hypothesis testing with a Wilcoxon rank sum and using the same sample size and no more than 20 samples, the policy of determining military budget size as a percentage of Gross Domestic Product (GDP) in Asian and African countries differs. For testing with a different sample size and no more than 20 samples, the policy of determining military budget size as a percentage of Gross Domestic Product (GDP) in Asian and African countries is the same. Based on hypothesis testing with a Wilcoxon rank sum and using a sample size greater than 20 samples, the policy of determining military budget size as a percentage of government spending in Asian, Oceania, and African countries differs.

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