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All Journal Epsilon: Jurnal Matematika Murni dan Terapan Jurnal Matematika Sains dan Teknologi BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Pengabdian Sumber Daya Manusia Jurnal Pengabdian Pada Masyarakat RAGAM: Journal of Statistics and Its Application
Lestia, Aprida Siska
Program Studi Matematika FMIPA Universitas Lambung Mangkurat
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PENDEKATAN BAYESIAN MARKOV CHAIN MONTE CARLO (MCMC) METROPOLIS-HASTINGS PADA PEMODELAN KLAIM ASURANSI KESEHATAN Lestia, Aprida Siska; Idris, Mochammad
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN (EPSILON: JOURNAL OF PURE AND APPLIED MATHEMATICS) Vol 18, No 2 (2024)
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/epsilon.v18i2.13872

Abstract

The distribution of health insurance claims that tend to be asymmetric and have heavy tails, requires a method that can offer more flexible and robust solutions than traditional frequentist approaches, such as the Bayesian Method. The advantage of this method lies in its ability to comprehensively account for uncertainty in parameter estimation, thereby producing a posterior distribution that can capture complex pattern of claim data. This study aims to apply the Bayesian approach with the Markov Chain Monte Carlo (MCMC) Metropolis-Hastings method in modeling health insurance claims. The claim data used are divided into outpatient and inpatient claims, with the lognormal distribution fitting proven to be the most appropriate for both types of claims. Risk estimation through Value at Risk (VaR) and Conditional Tail Expectation (CTE) using the Bayesian approach showed more moderate results compared to empirical estimates, indicating that this approach can reduce risk overestimation
LEVEL SOFT GROUP AND ITS PROPERTIES Abdurrahman, Saman; Idris, Mochammad; Faisal, Faisal; Hijriati, Na’imah; Thresye, Thresye; Lestia, Aprida Siska
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp2263-2274

Abstract

In this paper, we present an application of fuzzy subset and fuzzy subgroup to a soft set and a soft group, thereby creating a soft set and a soft group within the same group. Furthermore, we refer to the soft and soft groups as level soft sets and level soft groups. We also found out the level of soft sets and the operations on soft sets, such as intersection, union, and subset. We also examine what conditions a fuzzy subgroup and a soft group must meet to form a level soft group. Moreover, we scrutinize the properties of operations on a soft set, specifically intersection, union, and AND, and apply them to the level soft group to ascertain if they consistently produce a level soft group over the same set. Furthermore, we investigate the formation of a level soft and level soft group resulting from the homomorphism of the group and soft group. The research findings can enrich studies on the relationships between structures in fuzzy subgroups and soft groups and the application of soft group levels in further research.
ESTIMASI PARAMETER RANDOM EFFECT MODEL PADA REGRESI PANEL MENGGUNAKAN METODE GENERALIZED LEAST SQUARE (STUDI KASUS: KEMISKINAN DI PROVINSI KALIMANTAN SELATAN) Ariandy Hermawan; Yuana Sukmawaty; Aprida Siska Lestia
RAGAM: Journal of Statistics & Its Application Vol 1, No 1 (2022): RAGAM: Journal of Statistics and Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v1i1.7419

Abstract

Poverty is a condition that concerns the inability to meet the most minimum demands of life, especially from the aspects of consumption, income, education, and health. The problem of poverty is very complex and multidimensional in nature, as it relates to social, economic, cultural and other aspects. This study focuses on observation areas in South Kalimantan Province, with the PPM value in 2021 reaching (4.83%) still above the target goal of the Regional Medium-Term Development Plan (RPJMD) of South Kalimantan Province (3.96- 4.01%), so that further interventions are still needed to be able to reduce PPM in poverty cases. This study aims to estimate the parameters of the panel regression model used to analyze factors that are suspected to affect poverty cases in South Kalimantan Province in 2016-2020. The Random Effect Model (REM) is the best model used in this study, assuming that there are differences in slopes and interceptions caused by residual due to differences between individual units and between time periods. The process of estimating parameters on REM is determined through the Generalized Least Squares (GLS) Estimator method . From the results of the data processing, it was obtained that the model is influenced by economic growth, life expectancy, open unemployment rate, and labor force participation rate. From the results of the analysis of 2 (two) models, it was tested significantly and affected poverty in South Kalimantan Province in 2016-2020.  Keywords:   Poverty, Data Regression Panel, Generalized Least Square Method (GLS).
PEMODELAN REGRESI DATA PANEL PADA TINGKAT PARTISIPASI ANGKATAN KERJA PEREMPUAN DI PROVINSI KALIMANTAN SELATAN Putri Norhikmah; Fuad Muhajirin Farid; Aprida Siska Lestia
RAGAM: Journal of Statistics & Its Application Vol 1, No 1 (2022): RAGAM: Journal of Statistics and Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v1i1.7383

Abstract

Women’s Labor Force Participation Rate (LFPR) is an indication that can shows how much participation of women in the process development. The purpose of this study is to provide an overview of LFPR women in the Province of South Kalimantan, explaining the expected variables influence on women’s LFPR in South Kalimantan Province and determine the best model. This research data is sourced from the Centra Statistics Agency of South Kalimantan Province with a time period of 2017-2020. Variable independen research, namely female workers, female residents who are still in school and taking care of the household, the average length of schooling for women, female population according to the highest education ever graduate from senior high school above, female household heads, status of married and unmarried women marriage, district/city minimum wage, human development index women and regional domestic income growth at constant prices while the dependent variable is female LFPR. The results of data analysis, can be conclude that the Fixed Effect Model as the best model of panel regression. Women’s LFPR in South Kalimantan Province by producing two recommendation with Fixed Effect Model an R-Squared in the first model of 99,40%.Keywords:  Women’s LFPR, Panel Data Regression, South Kalimantan
Co-Authors Ahmad Taufik Amalia, Zharfa Rizqi Andriani, Asfia Ariandy Hermawan Azkia Azkia Azkia Khairal Jamil Balya, Muhammad Afief Dewi Anggraini Dewi Sri Susanti Faisal Faisal Fitriani Fitriani Fuad Muhajirin Farid Fuad Muhajirin Farid Gunawan, I Wayan Ari Hijriati, Naimah Idris, Mochammad Kasim Alfarisi Lissa, Hermei Maria Ulfah Muhammad Firdaus Muhammad Meidy Maulana Nabila Septiani Nadya Pratiwi Noor Baitirahmah Noor Jannah, Noor Nur Salam Nur Salam Pardi Affandi Putri Norhikmah Riska Fitria Rusidawati Rusidawati Saman Abdurrahman Sekar Wahyuningtias Siti Jubaidah Syifa Ajeria Thaibatun Nissa Thresye Thresye Tri Puspa Lestari Winda Adinda Tanjung Wuri Setyana Sari Yogi Apriyanto Yuana Sukmawaty Yuni Yulida