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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat
Yuliza Yuliza
Department of Electrical Engineering, Universitas Mercu Buana, Jakarta, Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Computer Science & IT Education Electrical & Electronics Engineering Social Sciences

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E-Beacon Card Training Based Application Internet Of Things (IOT) in The School Environment Imelda Uli Vistalina Simanjuntak; Yosy Rahmawati; Ketty Siti Salamah; Akhmad Wahyu Dani; Yuliza Yuliza
ABDIMAS: Jurnal Pengabdian Masyarakat Vol. 6 No. 2 (2023): ABDIMAS UMTAS: Jurnal Pengabdian Kepada Masyarakat
Publisher : LPPM Universitas Muhammadiyah Tasikmalaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35568/abdimas.v6i2.3312

Abstract

At that time, SMK Yadika 11 Jatirangga Bekasi still needed help communicating announcements within the school. In addition to being expensive, buying an intercom is also less effective during the teaching and learning process due to noise pollution. Therefore the PPM Team at Mercu Buana University wanted to provide a solution by introducing Internet of Things (IoT) technology on one of the Bluetooth ebacon devices. eBeacon Card is a Bluetooth Low Energy transmitter connected to various electronic devices. This device will be connected via a short message to each person's cell phone, such as an SMS notification. In this training, two eBeacon Cards uses, which should be applicable in two rooms with a radius of 20 m. However, due to space limitations, both are installed in one room. So that the target information announcement target can receive data from both eBeacon cards with the same announcement display twice. Some of the outputs used in evaluating this training were that they understood the IoT process, how to install and create eBeacon, and could use it for other needs such as announcements, advertisements, etc.
Raspberry Pi 4 and Ultrasonic Sensor for Real-Time Waste Classification and Monitoring with Capacity Alert System Yuliza Yuliza; Rachmat Muwardi; Prima Wijaya Kusuma; Lenni Lenni; Rizky Rahmatullah; Mirna Yunita; Akhmad Wahyu Dani
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 10 No. 4 (2024): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v10i4.30036

Abstract

The problem of waste management creates daily rubbish buildup due to thorough sorting. garbage sometimes accumulates in public garbage receptacles due to officials' ignorance of bin capacity and collectors' schedules, causing unclean conditions and the development of deadly diseases. Internet of Things technology was used to create a smart waste classification system with a notification mechanism in this study. This system classifies waste into plastic, metal, B3, and organic using a Raspberry Pi 4, camera module, and deep learning model. The classification uses a Convolutional Neural Network to speed up waste processing and separation. This research can be linked with research on separating trash types in one container and then allocated to garbage bins by type. Ultrasonic sensors and Raspberry Pi 4 can continuously monitor waste levels by sending data to the Ubidots IoT platform over HTTP. Based on experimental device data, system analysis shows 90% classification accuracy for all four waste categories. A Wireshark network analysis showed 61,098 bytes/s of throughput, 16 ms of delay, and zero data loss, demonstrating the system's ability for real-time monitoring and alerting. This research provides a realistic, cost-effective, and minimal solution to improve garbage classification and reduce collection costs to promote sustainability.
Co-Authors Akhmad Wahyu Dani Imelda Uli Vistalina Simanjuntak Ketty Siti Salamah Lenni Lenni Mirna Yunita Prima Wijaya Kusuma Rachmat Muwardi Rizky Rahmatullah Yosy Rahmawati