Article Per Year (5 Year)
p-Index From 2021 - 2026
1.564
P-Index
This Author published in this journals
All Journal Sistemasi: Jurnal Sistem Informasi JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL IT: Media Infromasi STMIK Handayani Makassar Journal of System and Computer Engineering Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Journal Peqguruang: Conference Series Malcom: Indonesian Journal of Machine Learning and Computer Science Ranah Research : Journal of Multidisciplinary Research and Development Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Sahibu, Supriadi
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Public Health Social Sciences Transportation Other

Published : 11 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : Journal of System and Computer Engineering

 1 
Sistem Kontrol dan Monitoring Penggunaan Daya Peralatan Elektronik pada Rumah Berbasis Internet Of Things (IOT) Dahlan, Dahlan; Yuyun, Yuyun; Sahibu, Supriadi
Journal of System and Computer Engineering Vol 6 No 1 (2025): JSCE: January 2025
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v6i1.1613

Abstract

The objectives of this study are (1) to achieve energy efficiency and cost savings (2) Internet of Things (IoT)-based control and monitoring systems using Node MCU ESP32 as a data processing center (3) enabling data processing from PZEM-004T sensors and sending control commands to solid state relays (SSR) based on user input via a website application. The implementation of this system shows significant potential in reducing energy consumption and costs in households. With real-time feedback on energy consumption, users can make wiser decisions about the use of electronic equipment, thereby reducing energy waste. Remote control capabilities allow users to manage electronic equipment more effectively, improve security, and reduce unnecessary energy consumption. This study shows that manual electricity usage reaches 9.59%, while with the implementation of the IoT system it is only 5.49%, so there is a saving in electricity consumption of 4.1%. This proves that the IoT system is more effective and efficient in managing the power consumption of electronic equipment.
Air Conditioner Control and Monitoring System based on Temperature Balance in Server Room using Fuzzy Logic and Internet of Things Methods Putu Rika Permana, I Gusti; Sahibu, Supriadi; Jalil, Abdul; Munawirah, Munawirah
Journal of System and Computer Engineering Vol 6 No 1 (2025): JSCE: January 2025
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v6i1.1623

Abstract

This research develops a temperature and humidity control system in the server room based on the Internet of Things and using fuzzy logic algorithms at AMIK Luwuk Banggai. The system is designed using NodeMCU ESP32, DHT11 sensor, Arduino IDE, and Blynk application, with objective of monitoring and controlling environmental conditions in real time. A series of quantitative experiments were conducted to evaluate the effectiveness of the sensor system. These experiments involved observations, measurements, and a comparison of the results with manual calculations. The results demonstrate that the DHT11 sensor exhibits a margin of error of 1.21% and a hardware accuracy rate of 98.79%. Furthermore, the integration of the Internet of Things (IoT) and the implementation of fuzzy logic in air conditioner control studies, as demonstrated in this study, has the potential to enhance the accuracy of temperature and humidity control within the room server to an accuracy rate of 90.91%. Furthermore, it can improve the responsiveness of the system in maintaining temperature stability. These findings were observed at AMIK Luwuk Banggai, where the application of IoT and fuzzy logic has been implemented. Fuzzy logic offers an effective and dependable approach to regulating temperature fluctuations in the server room, ensuring a stable environment that minimizes the likelihood of operational issues or hardware damage. The objective is to extend the lifespan of the hardware by preventing such complications.
Crop Recommendation Based on Soil and Weather Conditions Using the K-Nearest Neighbors Algorithm Yuliyanto, Yuliyanto; Sahibu, Supriadi; Imran, Taufik; Arisha, Andriansyah Oktafiandi; Munawirah, Munawirah
Journal of System and Computer Engineering Vol 6 No 3 (2025): JSCE: July 2025
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v6i3.1955

Abstract

The national food self-sufficiency program demands innovation in optimizing the selection of agricultural commodities based on environmental and weather conditions. This challenge is rooted in a fundamental problem faced by farmers—achieving harmony among soil characteristics, weather patterns, and suitable crops. In support of this initiative, it is necessary to develop a crop recommendation system based on machine learning that utilizes key soil and weather condition parameters. This study employs the K-Nearest Neighbors (KNN) algorithm, which functions by identifying the optimal value of ‘K’ to maximize classification accuracy. The KNN algorithm is implemented in a crop recommendation system to classify 1,100 datasets representing ideal growing conditions for 11 crop types. These datasets were generated using a normal distribution approach with a 5% variation from the mean values, and were validated using a clipping function to ensure the data remained within ideal ranges. The results of this study demonstrate that the KNN algorithm achieves high accuracy 96,67% in utilizing soil and weather parameters to generate crop recommendations. The average probability score for the recommended crops was 83.33%. Based on experimental testing, rice was recommended during the rainy and extreme rainy seasons, soybeans were recommended during the dry season, and mung beans were most suitable during extreme dry conditions.
Co-Authors Abdul jalil Ahmad, Andani Akbar Iskandar Arisha, Andriansyah Oktafiandi Dahlan Hamdan Gani Ian, Muslihan Imran, Taufik Jusdi, Jusdi Maibara, Rais Munawirah, Munawirah Munsyir, Mulawarman Muslihati Putu Rika Permana, I Gusti Surahman Taufik, Imran Taufiq, Arfah Wardi Wardi YP, Disyan Yuliyanto Yuliyanto Yuyun, Yuyun