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All Journal EKSAKTA: Journal of Sciences and Data Analysis Variance : Journal of Statistics and Its Applications Community Development Journal: Jurnal Pengabdian Masyarakat
Rohim, Febrian Hikmah Nur
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Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Health Professions Materials Science & Nanotechnology Mathematics Public Health

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CLASSIFICATION OF MYPERTAMINA APP REVIEWS USING SUPPORT VECTOR MACHINE Fadlurohman, Alwan; Yunanita, Novia; Rohim, Febrian Hikmah Nur; Wardani, Amelia Kusuma; Ningrum, Ariska Fitriyana
VARIANCE: Journal of Statistics and Its Applications Vol 6 No 2 (2024): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol6iss2page223-228

Abstract

Indonesia is rich in natural resources, including oil and gas, and it manages these strategic assets through state-owned enterprises, one of which is PT Pertamina. Pertamina is responsible for domestic fuel production, distribution, and price stabilization. To improve efficiency and transparency, Pertamina developed the MyPertamina application that enables cashless fuel purchases, stock monitoring, and up-to-date price information. The application aims to streamline distribution and control fuel prices, thus helping to stabilize the cost of goods and services. MyPertamina also ensures subsidized fuel distribution is more effective and targeted by identifying and verifying subsidy recipients, reducing the potential for abuse. A sentimental analysis of subsidized fuel user reviews using this application is needed to understand the public's views. This research uses the Support Vector Machine (SVM) method to analyze the sentiment of MyPertamina app reviews. This research produced a stable model. Out of 200 reviews, 190 were negative, and nine were positive, with an SVM model accuracy of 97%. Wordcloud visualization shows the words that appear frequently in each sentiment. Positive reviews appreciated the photo verification feature, easy payment, and good service. Negative reviews included verification difficulty, app error, and feature failure.
Itu Analisis faktor kejadian batu empedu menggunakan model regresi logistik biner. Amri, Ihsan Fathoni; Rohim, Febrian Hikmah Nur; Nurul Azka, M. Ilham; Rakhmawati, Muji Silvi
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 6, ISSUE 2, October 2025
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol6.iss2.art3

Abstract

Gallstone disease (cholelithiasis) is a digestive system disorder with a globally increasing prevalence. This study aims to identify risk factors contributing to the occurrence of gallstones using a logistic regression model. The data were obtained from the UC Irvine Machine Learning Repository, comprising a total of 319 outpatients from Ankara VM Medical Park Hospital, Turkey. The analysis was conducted on 23 independent variables, including demographic characteristics, body composition, medical history, and laboratory results. The Chi-Square test identified four significant variables, while the Wald test revealed six statistically significant predictors of gallstone occurrence: age, comorbidities, diabetes mellitus, visceral fat rating, visceral fat area, and vitamin D levels. Diabetes mellitus emerged as the most dominant risk factor (OR = 11.5), whereas higher levels of vitamin D showed a protective effect. The logistic regression model demonstrated a classification accuracy of 77%, indicating good predictive performance. These findings are expected to support early detection, clinical decision-making, and preventive interventions for more effective gallstone prevention.
PENGOPTIMALAN KETERAMPILAN DIGITAL SISWA SMAN 01 KEMBANG MELALUI PEMBUATAN GOOGLE FORM DAN ANALISIS DATA Ningrum, Ariska Fitriyana; Yusrin, Yusrin; Yunanita, Novia; Rohim, Febrian Hikmah Nur
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 5 No. 5 (2024): Vol. 5 No. 5 Tahun 2024
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v5i5.34842

Abstract

Penguasaan teknologi informasi merupakan keterampilan penting dalam menghadapi era digital, terutama bagi siswa sekolah menengah atas (SMA). Kegiatan pengabdian masyarakat ini berfokus pada peningkatan literasi digital siswa kelas 11 SMAN 01 Kembang melalui pelatihan pembuatan Google Form dan analisis data. Tujuan utama dari kegiatan ini adalah membekali siswa dengan keterampilan praktis dalam menggunakan Google Form untuk pengumpulan dan analisis data yang mendukung kegiatan akademik. Dalam workshop, siswa diperkenalkan pada fungsi Google Form, mulai dari cara membuat form, memilih jenis pertanyaan, hingga teknik dasar analisis data. Dengan metode pembelajaran interaktif, siswa diajak untuk langsung mempraktikkan setiap langkah dalam pembuatan formulir online dan bereksperimen dengan berbagai fitur yang tersedia. Hasil dari kegiatan ini menunjukkan peningkatan kemampuan digital siswa, terbukti dari keberhasilan mereka dalam membuat dan menggunakan Google Form secara mandiri. Selain itu, workshop ini juga membantu memperkuat keterampilan berpikir analitis dan kritis siswa dalam menghadapi masalah berbasis data. Dampak jangka panjang yang diharapkan adalah kemampuan siswa dan sekolah untuk mengintegrasikan teknologi informasi secara lebih luas dalam proses pembelajaran, sekaligus mempersiapkan siswa untuk tantangan dunia digital yang semakin berkembang.
Co-Authors Alwan Fadlurohman Ariska Fitriyana Ningrum Ihsan Fathoni Amri Nurul Azka, M. Ilham Rakhmawati, Muji Silvi Wardani, Amelia Kusuma Yunanita, Novia Yusrin, Yusrin