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All Journal Jupiter Jurnal Informatika Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) International Journal of Artificial Intelligence Research I-ROBOT Cyberspace: Jurnal Pendidikan Teknologi Informasi JOURNAL OF APPLIED INFORMATICS AND COMPUTING Prosiding Seminar Nasional Darmajaya Jurnal Informasi dan Komputer Jurnal Teknologi Informatika dan Komputer International Research on Big-data and Computer Technology (IRobot) Bulletin of Network Engineer and Informatics (BUFNETS) Jurnal Alih Teknologi Sistem Informasi (JATSI)
Budi Sutomo, Budi
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Library & Information Science Mathematics Other

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Journal : Jupiter

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Perancangan dan Implementasi Sistem Smart Air Conditioner Berbasis IoT di Gedung Kampus Dharma Wacana untuk Optimalisasi Energi Saputri, Tri Aristi; Sutomo, Budi; Hairunnisa, Afifah; Syaputra, M. Adie; Sulistiyanto, Sulistiyanto
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 17 No 1 (2025): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

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Abstract

The conventional air conditioning (AC) system utilized in the Dharma Wacana Campus building results in high operational costs. Therefore, this study intends to develop and execute an IoT-based Smart Air Conditioner System to enhance energy efficiency and reduce operational expenses. The research methodology comprises three main stages: (1) System Design, where both hardware and software are developed to monitor and control room temperature and humidity; (2) System Implementation, which involves the installation of sensors and actuators, as well as integration with an IoT platform for remote control; and (3) System Evaluation, where the system's performance is assessed through energy consumption data analysis and user satisfaction surveys. The findings indicate that the IoT-based Smart Air Conditioner System can improve energy efficiency by 15% and reduce operational costs by 20%. The analysis reveals that this system offers advantages regarding energy efficiency and cost savings. However, it also presents challenges, including the need for more complex maintenance and higher initial costs. Consequently, it is recommended to implement this system in other educational buildings.   Keywords— Smart Air Conditioner, Energy Efficiency, Internet of Things (IoT), Educational Buildings, AI Based Energy Optimization
Prediksi Kemacetan Lalu Lintas Jaringan Menggunakan Algoritma Random Forest Berbasis Data Mikrotik Putri, Desmita Wahyu; Sutomo, Budi
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 17 No 1 (2025): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.16911154

Abstract

Network traffic congestion is a major challenge in computer network management, especially in campus environments with a growing number of users and increasing internet access needs. The use of the network for various academic and operational activities often causes congestion, which impacts the quality of service and user performance in accessing information and collaborating online. Issues such as high data volume, network performance instability, inefficient bandwidth allocation, and lack of congestion prediction systems are the main contributing factors. This research aims to predict network congestion using the Random Forest algorithm. The data used was obtained from MikroTik devices and packet analysis using Wireshark, including information about active users, jitter, and bandwidth. The research methods include data collection, preprocessing, model training, and model performance evaluation. The research results show that the Random Forest algorithm is capable of predicting network congestion. This can provide important insights for network managers in taking steps to optimize network performance and reduce congestion. By providing a quantitative data-based approach, this research is expected to be an effective solution for addressing network congestion issues, particularly in complex environments such as campuses.   Keywords: Network congestion, Random Forest, MikroTik, Wireshark, prediction.
Co-Authors Anwar, Edi Desi Kurniawati Hairunnisa, Afifah Handayani, Etik Puji Ikhanto, M Nur Ikhsanto, M Nur Muhammad Adie Saputra, Muhammad Adie Muhammad Reza Redo Islami Noviditia, Saskia Pratama, Heri Pratama, Muhammad Aldo Eka Predianto, Eko Putra, Muhammad Aqida Putri, Desmita Wahyu Ridwan Yusuf Saprudin, Usep Saputra, Bima Arif Saputri, Tri Aristy Sulistiyanto Sulistiyanto, Sulistiyanto Syaputra, Muhammad Adie Tri Aristy Saputri tullah, Kholik Hidaya Wati, Sindi Jamila Zailani, Nur