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All Journal Operations Research: International Conference Series Parameter: Journal of Statistics ACE : Accounting Research Journal
Zahra, Lathifah
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics

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EXPLORATION OF STUDENTS INTERESTS IN MBKM AT RIAU UNIVERSITY USING A MACHINE LEARNING APPROACH Safitri, Nuraini; Zahra, Lathifah; Lafina, Melanie Maria; Erda, Gustriza; Yolanda, Anne Mudya
Parameter: Journal of Statistics Vol. 4 No. 2 (2024)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2024.v4.i2.17158

Abstract

This study aims to analyze the factors that have a significant influence on the interest of Riau University students in the Merdeka Belajar Kampus Merdeka (MBKM) program using a machine learning approach. MBKM is an innovation initiated by the Ministry of Education and Culture with the aim of improving student competence through its various programs. The Riau University as one of the universities supports this program by providing opportunities for its students to participate in various activities provided in the MBKM program. This study will specifically use a machine learning approach by utilizing several methods to analyze significant factors that have not been analyzed in depth by previous studies. The methods used in this analysis are logistic regression, decision trees, random forests, and naive bayes by utilizing secondary data on the level of interest of Riau University students to participate in the MBKM program in 2023. The variables used in this study include gender, generation, faculty, knowledge, self-confidence, feeling benefits, family support, friend support, lecturer support, self-ability, and facilities as independent variables and MBKM interest as a dependent variable. The results of the analysis of several methods show that the logistic regression method provides the best performance in modeling with an accuracy level of 95%. Variables that have a significant influence on students' interest in the MBKM program have also been successfully identified. The variables that have a significant effect are self-ability and family support. The development strategy of MBKM at the University of Riau can be optimized by paying attention to and focusing on these variables. The optimization of this strategy aims to make the implementation of the program more effective and efficient. Supportive policies such as workshops for the development of students' soft skills can be one of the strategic steps to improve students' abilities to the maximum
Estimation of the Three-Parameter Inverse Rayleigh Distribution Parameters for Guinea Pig Survival Data Faradila, Eky; Utari, Farah Asyifa; Zahra, Lathifah; Novitasari, Ratna; Astuti, Syaftiani Dwi; Sirait, Haposan
Operations Research: International Conference Series Vol. 6 No. 2 (2025): Operations Research International Conference Series (ORICS), June 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i2.384

Abstract

The Generalized Transmuted Inverse Rayleigh Function (GTIR) distribution is an extension of the inverse Rayleigh distribution, which is commonly used to model reliability and survival data. By incorporating an additional shape parameter (α) and a transmutation parameter (λ) alongside the scale parameter (σ), this distribution offers greater flexibility in handling skewed data or data with a non-monotonic hazard function. The parameters of the GTIR distribution are estimated using the Maximum Likelihood Estimation (MLE) method; however, they must be solved implicitly through numerical procedures. In this study, the GTIR distribution was employed to analyze the survival data of guinea pigs infected with tuberculosis. The primary objective of this analysis was to estimate the distribution parameters and to provide an overview of the survival pattern. The application of the GTIR distribution to the survival and hazard functions demonstrated that guinea pigs experience a sharp decline in survival probability at the onset of tuberculosis infection, followed by a gradual decrease in the risk of mortality over time. The hazard rate pattern, which initially increases and then decreases, indicates that the most critical period occurs immediately after infection. Parameter estimation of the GTIR distribution using the MLE approach yielded estimates of λ = 0.781, α = 10.135, and σ = 12.319, confirming that this model effectively captures the complex survival pattern with high accuracy.
Pengaruh Likuiditas, Profitabilitas, Leverage, Ukuran Perusahaan, Audit Quality, Dan Opinion Shopping Terhadap Opini Audit Going Concern Zahra, Lathifah; Wijayanti, Dwi Marlina
ACE: Accounting Research Journal Vol 5 No 1 (2025): June
Publisher : Fakultas Ekonomi dan Bisnis Universitas Papua

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

A going concern audit opinion is an auditor's assessment that indicates that a company cannot maintain its business. This assessment has the effect of losing public trust in the company's image. The aim of this research is to analyze and provide empirical evidence regarding the influence of liquidity, profitability, leverage, company size, audit quality, and opinion shopping on going concern audit opinions in various industrial sector companies listed on the Indonesia Stock Exchange in 2017-2021. This research uses a purposive sampling technique with a sample size of 24 companies, with logistic regression analysis using EViews 12. The results of this research show that the liquidity and profitability variables have a negative effect on the acceptance of going concern audit opinions. Meanwhile, the variables leverage, company size, audit quality, and opinion shopping have no effect on receiving going concern audit opinions. The results of this research can be a reference for plans and policies in the company so that conditions remain stable for the sustainability of the company
Co-Authors Anne Mudya Yolanda Astuti, Syaftiani Dwi Faradila, Eky Gustriza Erda Haposan Sirait Lafina, Melanie Maria Ratna Novitasari Safitri, Nuraini Utari, Farah Asyifa Wijayanti, Dwi Marlina