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All Journal Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Engineering: Journal of Mechatronics and Education
Elkin Rivalni
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Electrical & Electronics Engineering Engineering

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SISTEM MONITORING SUHU UNTUK MENJAGA KETAHANAN PRODUK MAKANAN TERHADAP RUANG PENYIMPANAN DENGAN MOTODE FUZZY LOGIC Makmun Effendi; Feri Wartono; Elkin Rivalni
Jurnal Pelita Teknologi Vol 14 No 1 (2019): Maret 2019
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (442.469 KB) | DOI: 10.37366/pelitatekno.v14i1.226

Abstract

Temperature in storage room is one of the factors that affects the durability of food. The food when be placed at an inappropriate temperature within a certain period, will cause slimy, smelled of acid, crushed, clot, bacteria can grow faster so that the product's life time will decrease. Therefore, in every storage room must be very concerned in every change of temperature. This research aims to create a set of tools that can monitor the temperature of storage room automatically. The tool will read the high and low temperature in real time using the DS18B20 sensor as a temperature data taker. The data will be processed to produce an output analysis of product durability in the storage room temperature using fuzzy logic method. In this research, the system can display temperature data and the results of the temperature monitoring process so that the system can be implemented and run as a requirement. Keywords:fuzzy logic; monitoring system; temperature
Evaluasi Keamanan Autentikasi Pengguna pada Sistem Operasi Windows dan Linux Galva Al Godzali; Rafif Isdarufa Athallah; Elkin Rivalni
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 1 (2025): Februari : Neptunus : Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i1.590

Abstract

Authentication security is an important aspect of the operating system. This research evaluates the security of user authentication on Windows and Linux operating systems by analyzing various methods such as the use of passwords and two-factor authentication. This study compares effectiveness, flexibility, and stability to provide insight into their advantages and vulnerabilities. The literature review method is used by utilizing secondary data from relevant sources. The research results show that Linux offers superior security due to its open-source nature and strong permission-based model, while Windows excels in ease of use and integrated features such as Active Directory. These results aim to provide information to users and organizations in choosing an operating system that suits their needs.
Comparison of K-Means and K-Medoids Methods in Clustering Stress Levels of 6th Semester Students Nuraini, Roswanda; Sinta Hardianti; Elkin Rivalni
Engineering: Journal of Mechatronics and Education Vol. 2 No. 1 (2025): Engineering: Journal of Mechatronics and Education
Publisher : Yayasan Insan Mulia Bima

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59923/mechatronics.v2i1.517

Abstract

Final-year students often experience high psychological pressure due to academic demands such as thesis completion, final exams, and career uncertainty. This stress can negatively affect their academic performance and overall mental health. This study aims to compare the performance of two clustering methods, K-Means and K-Medoids, in grouping stress levels among sixth-semester students. The comparison is based on three key parameters: accuracy, consistency, and computational speed. Data were collected using psychological questionnaires reflecting students’ stress symptoms and analyzed using both clustering techniques. Preliminary results indicate that K-Medoids outperforms K-Means in terms of accuracy and result stability, particularly when dealing with datasets containing outliers, while K-Means is more efficient in processing large-scale data. These findings are expected to serve as a reference for educational institutions in developing early stress detection systems based on data mining to enhance more targeted psychological support services.
Co-Authors Feri Wartono Galva Al Godzali Makmun Effendi Nuraini, Roswanda Rafif Isdarufa Athallah Sinta Hardianti