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Fuad Muhajirin Farid
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INDONESIA
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 5 Documents
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Search results for , issue "Vol 4, No 1 (2025): RAGAM: Journal of Statistics " : 5 Documents clear
PENGARUH PERUBAHAN TAHUN TERHADAP PRODUKSI PERTANIAN DI INDONESIA MENGGUNAKAN PENDEKATAN REPEATED MEASURES MANOVA Selly Rizkiyah; Indira Zein Rizqin; Milla Akbarany Baktiar Putri; Muhammad Nasrudin; Trimono Trimono
RAGAM: Journal of Statistics & Its Application Vol 4, No 1 (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.v4i1.14970

Abstract

This study aims to analyze significant differences in rice paddy production in Indonesia based on year factors using the Repeated Measures MANOVA method. The data used includes harvest areas, productivity, and total rice production from various provinces during the period 2020-2024.  The results showed that there was a significant relationship between the variables tested, so the independence assumption in the MANOVA method was not met. Therefore, Repeated Measures-MANOVA was used as an alternative approach that is more suitable for repeated data. The analysis showed that there were significant differences in rice production by year, with a p-value of <0.05 in all multivariate statistics. The results highlight the importance of efficient crop land management and increased productivity to support the sustainability of the agricultural sector. The Repeated Measures-MANOVA approach proved effective in identifying variations in production based on time factors and can be a relevant analytical tool.
Segmentation of West Java Province Based on Socio-Economic Indicators Using K-Means and Agglomerative Clustering Methods Tiara Valentina
RAGAM: Journal of Statistics & Its Application Vol 4, No 1 (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.v4i1.15589

Abstract

Regional segmentation based on socio-economic indicators is a crucial approach in data-driven development planning. Through accurate segmentation, governments can design more targeted policies aligned with the specific characteristics of each region. This study aims to compare two clustering methods, namely K-Means and Agglomerative Clustering, in grouping regions within West Java Province based on socio-economic indicators such as poverty rate, open unemployment rate, and Human Development Index (HDI). The analysis was conducted using the Python programming language on the Google Colab platform. Cluster performance was evaluated using the Elbow Method to determine the optimal number of clusters and the Silhouette Score to assess cluster quality. The results indicate that Agglomerative Clustering produces more consistent and interpretable segmentations, particularly in reflecting the socio-economic similarities between regions. However, in terms of computational efficiency, the K-Means method performs better due to its faster processing time. These findings offer valuable insights for regional policymakers in setting development priorities more effectively, grounded in the actual socio-economic conditions of each area
ANALISIS INFLASI DI INDONESIA: PEMODELAN ARIMA DAN IMPLIKASI KEBIJAKAN EKONOMI ALFISYAHRINA HAPSERY; Artanti Indrasetianingsih; Rabiatul Adawiyah
RAGAM: Journal of Statistics & Its Application Vol 4, No 1 (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.v4i1.14570

Abstract

One of the important indicators on a country's economy is inflation. Inflation is an increase in the price of goods and services in general and continuously over a certain period of time. Various studies have been conducted to predict inflation, both using conventional methods and those using artificial intelligence. This research uses the ARIMA method specifically to help the government in monitoring fiscal and monetary policies so that they are more responsive to the threat of inflation, such as interest rate adjustments or basic commodity price policies. The main objective of this study is to obtain a model that can be used to predict inflation in Indonesia with a high degree of accuracy. The results of the descriptive analysis show that the highest inflation in Indonesia occurred during the monetary crisis, namely in February 1998, which was 12.76, while the highest average inflation occurred in 1998 at 4.818. ARIMA modeling for inflation results in an ARIMA([1,3,5,8,48],0,0) model with an outlier , the model satisfies the residual white noise assumption, but does not meet the normally distributed residual assumption. Based on the RMSE and MAPE values, the results show that the RMSE data out sample has a smaller RMSE value when compared to the in sample data, while the MAPE value is smaller in sample data when compared to the out sample data
PEMODELAN KREDIBILITAS BÜHLMANN-STRAUB UNTUK DATA FREKUENSI KLAIM BERDISTRIBUSI POISSON-SUJATHA Evania Putri; Aceng Komarudin Mutaqin
RAGAM: Journal of Statistics & Its Application Vol 4, No 1 (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.v4i1.14679

Abstract

Motor vehicle insurance provides compensation for damage or loss incurred by motor vehicles. In determining credibility values, claim frequency data is required. Sometimes, this claim frequency data contains overdispersion issues, necessitating alternative methods for modeling claim frequency using a mixture distribution. The mixture distribution used in this research is the Poisson-Sujatha mixture distribution. The credibility method employed is an advancement of the Bühlmann method, known as the Bühlmann-Straub credibility method. The Bühlmann-Straub credibility model has been successfully applied in various insurance contexts, previously used in modeling with the Negative Binomial-Lindley distribution in 2023, yielding significant results.Before applying the credibility model, the parameters of the Poisson-Sujatha distribution are estimated using the maximum likelihood estimation method. The goodness-of-fit test used in this research is the chi-squared goodness-of-fit test. The research data consists of secondary claim frequency data for motor vehicle insurance recorded by PT. X in Category 1 (passenger transport with coverage values between Rp 0 to Rp 125,000,000) in Region 2 (DKI Jakarta, West Java, and Banten) for 2018 and 2019. Based on the application of this claim frequency data, the Bühlmann-Straub credibility factor is close to 1, indicating that the processed data has a significant impact on estimating the average future claim frequency. The estimated average motor insurance claim frequency for Indonesia, Category 1, Region 2, in 2020 is 0.0041, meaning that if there are 10,000 insurance policyholders in 2020, approximately 41 partial loss claims are expected.
Pengaruh Faktor Makroekonomi Terhadap Return Harga Saham Jakarta Islamic Index (JII) Menggunakan Metode Regresi Data Panel Intan Salsabila; Sigit Dwi Prabowo; Fuad Muhajirin Farid
RAGAM: Journal of Statistics & Its Application Vol 4, No 1 (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.v4i1.15389

Abstract

The Indonesian capital market has experienced developments that show its role as an important component in the economy. As one of the countries with a Muslim population, the Jakarta Islamic Index (JII) is used as an investment in stocks based on sharia. Every investor in the capital market, whether based on sharia or conventional, really needs relevant information about what macroeconomic factors can affect investment activities, especially on stock returns. The purpose of this study is to analyze the effect of macroeconomic factors, namely inflation, interest rates, and exchange rates on stock returns in companies listed on the Jakarta Islamic Index (JII) for the 2019-2022 period using the panel data regression analysis method. A method that is more likely to build and test more complex regression models. Based on the results of panel data regression processing, using the common effect model approach as the best model, the results of the f test showed that inflation, interest rates and exchange rates simultaneously had a significant effect on stock returns. The results of the t test also showed that inflation, interest rates, and exchange rates partially had a significant effect on stock returns.

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