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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Scan : Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknologi Elektro Jurnal Inspiration Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SemanTIK : Teknik Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING Sebatik Jurnal Riset Informatika Journal of System and Computer Engineering Journal Peqguruang: Conference Series Jurnal Pengabdian Masyarakat UNIPOL Ceddi Journal of Information System and Technology (JST) Ceddi Journal of Education Jurnal Teknik Informatika dan Teknologi Informasi JTT: Journal Teknik Dan Teknologi
Supriadi Sahibu
Pascasarjana Sistem Komputer STMIK Handayani Makassar
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Smart Office Implementation System for Electrical Energy Consumption Efficiency Using IoT-Based Fuzzy Algorithm M. Ikhsan U; Andani Achmad; Supriadi Sahibu; Nim Von-Lind
Ceddi Journal of Information System and Technology Vol. 4 No. 1 (2025): April
Publisher : Yayasan Cendekiawan Inovasi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jst.v4i1.110

Abstract

Increased electricity consumption in office environments often results in waste and inefficient costs. This study aims to develop an Internet of Things (IoT)-based Smart Office system using a fuzzy algorithm to improve electricity efficiency. The method used is the Research and Development (R&D) approach with the Continuous Improvement Spiral model. This system is designed by utilizing a DHT11 sensor for temperature and an LDR for light intensity, which is connected to an Arduino Nano as the main data processor. Data is processed using a fuzzy algorithm to control electronic devices, such as lights and fans, and monitored through the Blynk application. The results showed that the system was able to reduce electricity consumption from 63.57 kWh to 41.32 kWh, with significant savings in monthly electricity costs. The average sensor accuracy reached 99.40% for DHT11 and 96.36% for LDR. This system makes a positive contribution to energy efficiency and is a sustainable solution for office environments.
National Exam Try Out Application Design At SMP Negeri 35 Makassar Dewi Angraini; Ernie C. Avila; Robbi Rahim; Supriadi Sahibu
Ceddi Journal of Education Vol. 2 No. 2 (2023): December
Publisher : Yayasan Cendekiawan Inovasi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/cje.v2i2.56

Abstract

The problem with the current system is that Try Out for the National Examination at SMP Negeri 35 Makassar is still done manually, therefore I provide a solution for designing the Try Out application, which produces an application that can help students in preparation for the National Examination. This research aims to design an effective and efficient national exam try-out application at SMP Negeri 35 Makassar, implementing the Dynamic System Development Method (DSDM) at SMP Negeri 35 Makassar. This data was obtained through literature studies and interviews. Data analysis uses PHP programming scripts and MySQL data. The results of this research show that the Try Out application is user-friendly, has an attractive appearance, and has complete features that can make things easier for students, especially in carrying out Try Outs, so that the process of processing test results is more effective and efficient, the Try Out Application is quite good, useful for users and so needed that it was declared feasible based on the tests carried out, with an average score of 86.00% from 44 respondents.
Integration Of Fingerprint Attendance Systems And Iot-Based Computer Vision For Employee Presence Monitoring Aang Kunaefi; Andani Achmad; Supriadi Sahibu; Wardi Wardi; Imran Taufik; Nasrullah Nasrullah
Journal of System and Computer Engineering Vol 7 No 4 (2026): JSCE: October 2026
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v7i4.2891

Abstract

The fingerprint-based attendance system at the Makassar Public Health Laboratory (BLKM Makassar) has limitations because it only records administrative attendance and cannot verify the physical presence of employees in the workplace. This study aims to design and implement an integrated fingerprint attendance and Internet of Things (IoT)-based computer vision system to support automated employee presence monitoring. The system uses two ESP32-CAM units installed in the lobby area and connected to a Flask Python server and MariaDB database. Image processing employs Histogram of Oriented Gradients (HOG) for face localization, dlib 68 facial landmarks for face alignment, and ResNet-34 to generate 128-dimensional face embeddings. Face identification is performed using Euclidean Distance with a threshold of 0.45 and a Time Window Buffer mechanism during monitoring cycles at 10:00 and 14:00 WITA. The results show that image transmission through HTTP POST operates with HTTP 200 OK and a latency of approximately 80 ms. Under normal walking conditions, the system achieved a 100% detection success rate. From 150 dynamic tests, the multi-camera system achieved an overall detection success rate of 63.33%, while Camera 1 and Camera 2 achieved 60.67% and 40.00%, respectively. The system achieved a 74% success rate under fast walking conditions, which decreased to 16% during running due to motion blur and lighting conditions. The integration of fingerprint attendance and computer vision provides supporting information for identifying discrepancies between administrative attendance records and the visual presence of employees within the monitored camera-covered area.
Deteksi Dini Potensi Tip Burn dan Frog Eye pada Selada Hidroponik Berbasis Kondisi Lingkungan Menggunakan Naive Bayes pada ESP32 Fadhlan Muhammad; Wardi wardi; Imran Taufik; Mashur Razak; Abdul Latief Arda; Supriadi Sahibu
Journal of System and Computer Engineering Vol 7 No 4 (2026): JSCE: October 2026
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v7i4.2962

Abstract

Lettuce (Lactuca sativa L.) is a high-value horticultural commodity susceptible to tip burn, a calcium deficiency disorder triggered by high temperature and low humidity, and frog eye, a fungal leaf spot caused by Cercospora canescens that thrives under low temperature and high humidity. Visual inspection detects both only after damage has occurred. This study developed an Internet of Things early detection system that classifies environmental risk conditions using Gaussian Naive Bayes embedded directly on an ESP32 microcontroller. The system integrates DHT22, pH, and TDS sensors and sends automatic Telegram notifications. Environmental data were collected for 31 days at a hydroponic farm in Makassar, yielding 1,005 valid records after preprocessing. The model was trained in Python with scikit-learn, and its parameters were deployed on the ESP32 as embedded machine learning. The simulation model achieved 95.56 percent accuracy, while the real-data model achieved 94.03 percent accuracy on 201 test samples, with a five-fold cross-validation accuracy of 92.91 percent and a spread of only 0.12 percent across four validation methods. Field visual validation showed 52 percent agreement, indicating that the system is best suited as an early warning of conducive conditions rather than as a symptom diagnosis tool. Keywords—Embedded Machine Learning, ESP32, Frog Eye, Naive Bayes, Tip Burn
Co-Authors Aang Kunaefi Abd. Rahman Abdul Jalil Abdul Latief Arda Abdullah, Alfiah Agusriandi, Agusriandi Agussalim, Agussalim Akbar Akbar Amiruddin. A Andani Achmad Andani Achmad Andani Achmad Andi Yulia Muniar Arisha, Zanifah Butsiarah Dewi Angraini Ernie C. Avila Fadhlan Muhammad Fajar Husain A Fandi Ishadinata Farida Farida Febri Hidayat Saputra Hatma Hatma Husni Sulaiman Ilin Sukma Imran Taufik Jawati Jawati Kamaruddin Latief, Rifaldy Ramadhan Mansyur Mashur Razak Muh. Ilham Ramadhan Muslihan, Muslihan Nasrullah Nim Von-Lind Nur Iman Nurul Hidayah Reski Badillah Rismawati Bambang Robbi Rahim Sri Kurniyan Sari Syafruddin Syarif Syafruddin Syarif U, M Ikhsan Wardi Wardi WILYAM ARIESTA HALUK Yuyun Yuyun Yuyun Zahir Zainuddin Zahir Zainuddin Zahir Zainuddin Zahir Zainuddin Zahir Zainuddin3