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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Mabrur: Academic Journal of Hajj and Umra
Kurniawan, Muhammad Idham
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Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Pengaruh Kualitas Pelayanan Terhadap Kepuasan Jemaah Umrah Jamilatunniswa, Emil; Setiawan, Asep Iwan; Kurniawan, Muhammad Idham; Dasir, Khoirizi H.
Mabrur: Academic Journal of Hajj and Umra Vol. 3 No. 1 (2024): Mabrur: Academic Journal of Hajj and Umra
Publisher : Faculty of Da'wah and Communication, UIN Sunan Gunung Djati, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/mjhu.v3i1.35268

Abstract

The aim of this study was to determine the effect of service quality on the satisfaction of Umrah pilgrims and to determine the level of congregation satisfaction at KBIHU Al-Falah Cicalengka. With a quantitative approach, this study uses primary data collection techniques obtained through distributing questionnaires to Umrah pilgrims and data processed using simple linear regression analysis with a sample size of 30 people. The theory of service quality in this study aims to determine the value of good and bad service quality. The results of this study indicate that the services at KBIHU Al-Falah are good and the level of congregation satisfaction is also very satisfied.
COMPARISON OF BINARY PROBIT REGRESSION AND FOURIER SERIES NONPARAMETRIC LOGISTIC REGRESSION IN MODELING DIABETES STATUS AT HAJJ GENERAL HOSPITAL SURABAYA Otok, Bambang Widjanarko; Zulfadhli, Muhammad; Pangesti, Riwi Dyah; Kurniawan, Muhammad Idham; Haryanto, Albertus Eka Putra; Darwis, Darwis; Kurniawan, Iwan
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss1pp0255-0270

Abstract

Diabetes mellitus is a chronic disease with a rising global prevalence, including in Indonesia. Early detection and accurate modeling are crucial for effective prevention and management. Binary Logistic Regression (BLR) is commonly used for binary outcome modeling; however, in practice, the relationship between binary outcomes and continuous predictors is often nonlinear, making BLR less suitable. To address these limitations, alternative methods such as Binary Probit Regression (BPR) and Flexible Semiparametric Nonlinear Binary Logistic Regression (FSNBLR) have been developed. This study aims to compare the performance of BLR, BPR, and FSNBLR models in classifying diabetes mellitus cases at Hajj General Hospital Surabaya. All three models were estimated using the Maximum Likelihood Estimation (MLE) method. Since the resulting estimators do not have closed-form solutions, numerical iteration using the Newton-Raphson method was applied. Model performance was assessed using Area Under the Curve (AUC), accuracy, sensitivity, and specificity. The FSNBLR model outperformed both the BLR and BPR models. It achieved the highest AUC value of 81.86%, while BLR (66.30%) and BPR (66.30%). That is indicated FSNBLR superior discriminative ability. In addition, the FSNBLR model recorded higher accuracy, sensitivity, and specificity compared to the other two models. The FSNBLR model demonstrated better predictive performance in identifying diabetes mellitus cases, especially in scenarios involving nonlinear relationships between predictors and the outcome variable. These findings suggest that flexible semiparametric approaches offer greater effectiveness in medical classification tasks, particularly for chronic conditions like diabetes mellitus.
Co-Authors Asep Iwan Setiawan, Asep Iwan Bambang Widjanarko Otok darwis darwis, darwis Dasir, Khoirizi H. Haryanto, Albertus Eka Putra Iwan Kurniawan Jamilatunniswa, Emil Muhammad Zulfadhli, Muhammad Pangesti, Riwi Dyah