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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 213 Documents
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ANALYSIS OF ACADEMIC SATISFACTION LEVEL USING PROBABILISTIC FUZZY INFERENCE SYSTEM Ayu Siska Maryoni
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 13, No 2 (2025): 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.13.2.2025.134-143

Abstract

Student academic satisfaction is a crucial indicator for evaluating the quality of higher education services. However, the subjective nature and inherent uncertainty in student perceptions render conventional measurement approaches less effective. This study aims to develop and apply a Probabilistic Fuzzy Inference System to analyze the level of academic satisfaction in a more adaptive and logical manner.This method integrates fuzzy logic (to handle linguistic ambiguity) and probability (to address the uncertainty in the contribution of service aspects such as academic administration, academic advisor support, information accessibility, and supporting facilities). Data were collected using a five-level linguistic scale questionnaire, which was converted into fuzzy numbers using triangular membership functions. Inference was carried out using a probabilistic fuzzy rule base.The defuzzification result of the developed system yielded a value of 3.52, which indicates a high level of satisfaction. These findings suggest that the probabilistic fuzzy approach offers a more realistic and flexible evaluation compared to static methods, while being effective in identifying the most influential service aspects. This study contributes to the development of logic- and data-driven academic evaluation models.
Application of Empirical Best Linear Unbiased Prediction (EBLUP) in Estimating Labor Force Participation Rate at the Regency/City Level in Kalimantan Island, 2016 Izumi Citra Amelia; Riski Tommi Mardoni; Syofmarlianisyah Putri; Debby Cynthia Ningrum; Iftina Ika Rahmawati; Cucu Sumarni
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 13, No 2 (2025): 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.13.2.2025.85-97

Abstract

The Labor Force Participation Rate (LFPR) serves as a vital indicator for labor market planning, particularly in Kalimantan, a region experiencing sustained economic growth. In 2016, however, regency- and city-level LFPR data were unavailable due to a reduced sample size in the National Labor Force Survey. This study employs Small Area Estimation (SAE) using the Empirical Best Linear Unbiased Prediction (EBLUP) method to estimate LFPR at the sub-provincial level. Auxiliary variables include the number of vocational high schools (SMK), the proportion of villages receiving foreign aid, the share of trade-related enterprises, and the number of villages with migrant workers. Findings indicate that SAE-EBLUP produces estimates with lower relative standard errors (RSE) than direct estimation, offering improved precision for small-area LFPR estimates.
MODELING OF FACTORS INFLUENCING GENDER DEVELOPMENT INDEX (GDI) IN PAPUA PROVINCE USING SPLINE NONPARAMETRIC REGRESSION Sintah Sintah; Ferry Kondo Lembang; Norisca Lewaherilla
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 12, No 2 (2024): 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.12.2.2024.29-41

Abstract

The Gender Development Index (GDI) is an index of achieving basic human development capabilities to measure success in efforts to develop the quality of human life by considering gender inequality. Papua Province is the province with the lowest GDI score when compared to the 34 provinces in Indonesia. This condition shows that there is still a development gap between the male and female genders. For this reason, it is necessary to research the factors that are suspected to influence GDI in Papua Province. In this study, the pattern of GDI data and the factors that are thought to influence it do not form a specific pattern, so we used spline nonparametric regression. Based on this study, the best model is obtained by the optimal knot point based on the smallest Generalized Cross Validation (GCV) value, which are 3-knots and six significant variables, namely, Life Expectancy , Expected Years of Schooling , Female Income Contribution , Sex Ratio , Female Labor Force Participation Rate , High School Enrollment Rate. This model has an  of 99.95%. The predictor variable used has an effect of 99.95%, and other variables influence the rest.

Page 22 of 22 | Total Record : 213

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