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All Journal Journal of Data Analysis BAREKENG: Jurnal Ilmu Matematika dan Terapan Sang Pencerah: Jurnal Ilmiah Universitas Muhammadiyah Buton Al-Mutsla: Jurnal Ilmu-Ilmu Keislaman dan Kemasyarakatan
Darwis Darwis
STAIN Majene
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Determinan Nilai Indeks Prestasi Akademik Mahasiswa Pendidikan Agama Islam Darwis Darwis
Sang Pencerah: Jurnal Ilmiah Universitas Muhammadiyah Buton Vol 8 No 1 (2022): Sang Pencerah: Jurnal Ilmiah Universitas Muhammadiyah Buton
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Muhammadiyah Buton

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (401.5 KB) | DOI: 10.35326/pencerah.v8i1.1878

Abstract

Tingginya IPK yang diperoleh mahasiswa adalah indikator keberhasilan dalam dunia akademik. Salah satunya adalah mahasiswa pendidikan Agama Islam yang cenderung dituntut belajar agama Islam. Hasil belajar mereka dibuktikan dengan level IPK. Penelitian ini bertujuan untuk menemukan determinan nilai indeks prestasi mahasiswa Pendidikan Agama Islam. Jenis penelitian ini adalah kuantitatif. Penelitian ini dilakukan di STAIN Majene dengan sampel penelitian adalah mahasiswa Pendidikan Agama Islam. Jumlah sampel sebanyak 133 mahasiswa Metode penelitian yang digunakan adalah metode pohon regresi. Hasil penelitian ini menemukan bahwa determinan yang paling berkontribusi mempengaruhi nilai IPK mahasiswa Pendidikan Agama Islam adalah biaya SPP, jalur masuk PTKIN, dan alat transportasi. Sedangkan variabel penghasilan rata-rata keluarga pendidikan serta pekerjaan Ayah dan status penerima beasiswa adalah determinan yang kurang berkontribusi dalam mempengaruhi nilai IPK mahasiswa pendidikan agama Islam.
Parameter Estimation of the Temporal Point Process Model through the Bayesian Approach (Case Study : Malaria Disease Data from Wahidin Hospital in Makassar City) Darwis Darwis; Sunusi N; Kresna A.J.
Journal of Data Analysis Volume 2, Number 2, December 2019
Publisher : Department of Statistics, Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (384.967 KB) | DOI: 10.24815/jda.v2i2.15264

Abstract

Penelitian ini bertujuan mengestimasi parameter melalui pendekatan Bayesian dari model temporal point process. Paramater intensitas bersyarat model tersebut dipandang sebagai suatu renewal process yang selanjutnya digunakan melalui pendekatan Squared Error Loss Function (SELF). Parameter intensitas bersyarat model temporal point process diestimasi menggunakan metode maximum likelihood estimation melalui persamaan likelihood point process.  Selain itu, penelitian ini mengkaji metode estimasi maksimum likelihood dan metode Bayes untuk menganalis fungsi resiko dari hasil penaksir parameter intensitas bersyarat. Pada aplikasi estimasi parameter ini, studi kasus yang digunakan adalah menganalisa data orang yang terkena penyakit malaria yang datanya berasal dari Rumah Sakit Wahidin Kota Makassar. Studi kasus tersebut menghasilkan nilai  yang merupakan nilai resiko penaksir MLE yang lebih tinggi dibandingkan dengan menggunakan Metode Bayes sedangkan nilai  merupakan hasil nilai resiko dari penaksir MLE yang lebih kecil dibandingkan dengan menggunakan Metode Bayes. This study parameter estimation of conditional intensity with temporal point process model by Bayesian approach. The conditional intensity with temporal point process model derived as a renewal process where inter event time is defined as its random variable. Squared Error Loss Function (SELF) approach is used to estimate the parameter of conditional intensity with temporal point process model which is happened as a renewal process using Bayesian. The other outlines of this paper is to determine the Risk Function as the result of estimation of conditional intensity by Bayesian and by Maximum likelihood Estimation (MLE). The application taking an analysis of Malaria at a place, which is properly conclude that the estimation using MLE method is more risky than the Bayesian it self.
The teachings of Islam URGENSI AJARAN ISLAM K.H. MUHAMMAD TAHIR PADA GENERASI MILINEAL: URGENSI AJARAN ISLAM K.H. MUHAMMAD TAHIR PADA GENERASI MILINEAL Darwis Darwis
AL-MUTSLA Vol. 4 No. 2 (2022): Al Mutsla : Jurnal Al Mutsla Desember 2022
Publisher : STAIN MAJENE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46870/jstain.v4i2.283

Abstract

Ajaran islam salah satu hal yang sangat penting untuk diperhatikan agar dapat menjadi kehidupan manusia yang damai dan tenteram. Pada penelitian ini bertujuan mengetahui muatan ajaran Islam K.H. Muhammad Thahir, menumbuhkan motivasi generasi milineal untuk mempelajari ajaran islam Beliau, dan urgensi ajaran islam K.H. Muhammad Tahir pada generasi milenial. Teknik pengumpulan data yang digunakan yaitu wawancara dan dokumentasi. Metode analisis data menggunakan analisis data deskriptif. Hasil penelitian menunjukkan Muatan ajaran islam Beliau yang dapat dideskripsikan bahwa ajaran islam beliau tidak dapat diketahui akan tetapi muatan ajaran islam Imam Lapeo yaitu kedekatan kepada Allah dengan ibadahnya dan karamah yang dimiliki. Selain itu ada tujuh karakter yang diajarkan Beliau diantaranya: arif, berani, cerdas, dermawan, berpikiran positif, semangat, pejuang spritual. Cara menumbuhkan motivasi generasi milineal mempelajari ajaran islam dari Beliau yaitu karakter beliau yang penuh keikhlasan dan masyarakat membawa anaknya dari kecil dibawa pergi ziarah ke makamnya. Pentingnya ajaran pendidikan Islam K.H. Muhammad Tahir memiliki peran sangat penting dalam pembentukan karakter generasi milenial diantaranya: ajaran pendidikan islam dari Imam Lapeo menjadi teladan bagi kehidupan sehari-hari.
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.
COMPARISON OF COPULA FAMILY (GAUSSIAN, ARCHIMEDEAN, AND REGRESSION) IN A CASE STUDY OF COMPOSITE STOCK PRICE INDEX ON INDONESIA STOCK EXCHANGE Darwis, Darwis; Sartono, Bagus; Yuliani, Leny
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/barekengvol20iss1pp0755-0768

Abstract

Stocks are one of the most popular financial market instruments. On the other hand, stocks are an investment instrument that is widely chosen by investors because stocks are able to provide attractive profit levels. Investment is an effort to postpone consumption in the present. Comparing copula families is crucial for selecting the model that best fits the observed data dependency structure. This helps produce more accurate analysis and more meaningful interpretations. This study analyzes different types of copula relationships using the Tau Kendall method, applying it to the movement of the Composite Stock Price Index (IHSG) on the Indonesia Stock Exchange (IDX). The data used are secondary monthly data of IHSG as a response variable, while the explanatory variables are inflation (%), exchange rate (Rp/USD), and interest rate (%) in 2010-2014. The results show the pattern of the relationship between IHSG and its macroeconomic factors on the IDX using copula parameter estimation with the Tau Kendall approach, with the largest log-likelihood fitting results showing a relationship pattern following the Gumbel copula, namely IHSG with inflation, interest rates with IHSG following the Clayton copula, and exchange rates following the Frank copula. Meanwhile, using the regression copula has better interpretation results compared to the Gaussian and Archimedean copula, with an MAPE value of 0.122 with a correlation of 70.63%.
Co-Authors Bagus Sartono Bambang Widjanarko Otok Haryanto, Albertus Eka Putra Iwan Kurniawan Kresna A.J. Kurniawan, Muhammad Idham Muhammad Zulfadhli, Muhammad Pangesti, Riwi Dyah Sunusi N Yuliani, Leny