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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknologi Elektro Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Jurnal Ilmu Teknik dan Komputer Jurnal Abdidas Internet of Things and Artificial Intelligence Journal
Akhmad Wahyu Dani, Akhmad Wahyu
Universitas Mercu Buana, Jakarta
Religion Agriculture, Biological Sciences & Forestry Arts Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Public Health Social Sciences Other

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Rancang Bangun Alat Kontrol dan Monitoring Pembersih Udara Menggunakan Metode Ionisasi Berbasis IoT Dani, Akhmad Wahyu; Sirait, Fadli; Saputra, Idris Syaifullah
Jurnal Ilmu Teknik dan Komputer Vol 8, No 2 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/jitkom.v8i2.004

Abstract

Polusi udara ditimbulkan dari hasil pembakaran yang tidak sempurna, dimana proses pembakaran tersebut menghasilkan gas-gas yang berbahaya diantaranya yang paling banyak ditemukan pada lingkungan kita adalah gas CO (karbon monoksida) dan gas NOx (nitrogen monoksida, nitrogen dioksida, dll Polusi udara tidak hanya terjadi diluar ruangan, tetapi terjadi juga di dalam ruangan. Oleh karena itu peneliti ingin membuat salah satu metode untuk pembersih udara menggunakan ionisasi, alat ionisasi bernama generator ion, dimana bekerja dengan melepaskan ion muatan negatif keudara Ion bermuatan negatif ini akan menempel pada partikel-partikel positif seperti debu, asap, dan polutan lainnya sehingga partikel-partikel tersebut menjadi berat dan jatuh ke lantai. Pengionisasi udara membantu menghilangkan polutan dan meningkatkan kualitas udara. Saat pengujian alat sensor MQ-135, PMS5003, DHT22 nilai rata-rata tingkat keberhasilan adalah 85%. Pengujian sensor saat udara terdapat polusi menampilkan nilai karbon monoksida 1073.5 μg/m3, sensor PMS5003 nilai PM2.5 159.0 μg/m3, PM10 171.0 μg/m3, sensor DHT22 membaca suhu 31.1°C dan kelembapan 71.0%. Setelah generator ion negatif aktif, pada tampilan virtuino memperlihatkan katagori kualitas udara berada pada level “Kualitas Udara Sedang” PM2.5 107.0 μg/m3, PM10 11.0 μg/m3, CO 4529.0 μg/m3, suhu 27.0 °C dan kelembapan 61.3 %.
Benchmarking in QoS and Energy Consumption SAW and TOPSIS Algoritm in Low Cost Microcontroller for Wireless Sensor Network Routing Application Hakim, Galang Persada Nurani; Septiyana, Diah; Dani, Akhmad Wahyu; Sirait, Fadli
Jurnal Teknologi Elektro Vol 15, No 2 (2024)
Publisher : Electrical Engineering, Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/jte.2024.v15i2.008

Abstract

The Wireless Sensor Network technologies have provides us with cheap and unique solution to deal with telecommunication infrastructure problem that don’t exist in extreme and isolated area. To guarantee the quality of service of Wireless Sensor Network wireless data transmission, a lot of researchers propose to employ a routing algorithm, such as SAW and fuzzy topsis from MCDM algorithm. A lot of routing algorithm in Wireless Sensor Network was based on these algorithms. In this paper we propose to do simulation and real time energy measurement in order to determine the best MCDM algorithm to be use in Wireless Sensor Network routing. In QoS 3x4 node simulation Both algorithm has provide low delay 31 millisecond and low packet loss 16 bit. This good performance in QoS however has disadvantage which has higher hop quantity. In term of energy consumption SAW has less energy consumption (better) compare with fuzzy topsis for each microcontroller development platforms that we have test. Although it was small but we have difference in energy consumption between SAW and fuzzy topsis, for ESP32 it has difference 39 microJoule, for ESP8266 it has difference 129 microJoule and for ATMEGA328P it has difference 2 microJoule.
Design of Equipment for Detecting and Ensuring Reliability of The Substation Ihsan, Hafid; Muwardi, Rachmat; Yunita, Mirna; Yuliza, Yuliza; Dani, Akhmad Wahyu
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 3 (2024): Volume 4 Issue 3, 2024 [August]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i3.774

Abstract

Substations are vital elements of electrical infrastructure that necessitate continuous monitoring and maintenance to ensure optimal performance. This research advocates for the deployment and design of devices based on the Raspberry Pi 3 Model B to enhance substation reliability. The project involves developing hardware and software capable of real-time monitoring of substation conditions, utilizing sensors to measure critical parameters such as temperature, current, voltage, and humidity. The monitoring software is designed to collect, analyze, and report data, employing detection algorithms, including the Fuzzy Mamdani method, to ensure accurate sensor and frequency measurements and to identify potential disturbances or anomalies. Additionally, the system integrates automatic mechanisms for maintaining substation conditions, encompassing preventive measures and rapid responses to emergency situations. Testing under various fault scenarios and operational conditions demonstrated the device's effectiveness in detecting issues and providing swift responses, thereby enhancing substation performance. The results show an average error of 0.14% for voltage measurements, 0.31% for current measurements, and 0.02% for data transmission frequency. This implementation is expected to positively impact substation management and maintenance, reduce the risk of system failures, and improve overall operational efficiency. Leveraging Raspberry Pi technology ensures a cost-effective solution that can be seamlessly integrated with existing substation monitoring systems.
Workshop Pengenalan Hardware Komputer kepada Warga Pulau Lancang, Kepulauan Seribu Hajar, Muhammad Hafizd Ibnu; Suwoyo, Heru; Triyanto Pangaribowo; Kadarina, Trie Maya; Sirait, Fadli; Dani, Akhmad Wahyu; Supegina, Fina; Yuliza, Yuliza; Gunardi, Yudhi
Jurnal Abdidas Vol. 5 No. 6 (2024): Desember
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/abdidas.v5i6.1092

Abstract

Komputer merupakan perangkat elektronik yang mengintegrasikan berbagai komponen untuk menghasilkan informasi yang telah diolah sebelumnya. Dalam konteks pengabdian masyarakat yang dilaksanakan di Sekolah Madrasah Diniyah Pulau Lancang, diperkenalkan pentingnya pemahaman tentang perangkat keras komputer kepada warga. Hal ini didasarkan pada kebutuhan mendesak akan literasi teknologi karena hampir seluruh aktivitas, termasuk pelaksanaan ujian, telah berbasis komputer. Program pengabdian ini bertujuan untuk meningkatkan pengetahuan peserta mengenai fungsi masing-masing perangkat komputer serta kemampuan dalam mengoperasikan komputer dengan baik. Metode yang digunakan dalam program ini adalah pendekatan interaktif, melibatkan kolaborasi aktif antara warga, dewan guru, siswa/i, dan karang taruna di Pulau Lancang. Hasil kegiatan menunjukkan bahwa program ini memberikan manfaat dalam pengembangan ilmu pengetahuan dan teknologi bagi warga, terutama dalam meningkatkan pemahaman teknologi dasar komputer. Program ini diharapkan dapat menjadi langkah awal untuk mempersiapkan komunitas Pulau Lancang dalam menghadapi era digital.
E-Beacon Card Training Based Application Internet Of Things (IOT) in The School Environment Simanjuntak, Imelda Uli Vistalina; Rahmawati, Yosy; Salamah, Ketty Siti; Dani, Akhmad Wahyu; 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.
Design and Implementation of a Real-Time Monitoring System for a 150 kV Substation with Multi-Platform Notification and Visualization: English Kartika, Eka Anggara Yuda; Muwardi, Rachmat; Rahmatullah, Rizky; Yunita, Mirna; Yuliza, Yuliza; Dani, Akhmad Wahyu
Internet of Things and Artificial Intelligence Journal Vol. 5 No. 2 (2025): Volume 5 Issue 2, 2025 [May]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v5i2.942

Abstract

This paper presents the development and implementation of an innovative real-time monitoring and notification system for a 150 kV electrical substation, leveraging Raspberry Pi 3, Node-RED, MySQL, and Firebase. The system measures key electrical parameters such as voltage, current, power, and frequency using sensors connected to a Programmable Logic Controller (PLC). The data is processed and displayed through a single-line diagram on both a web-based dashboard and an Android application. Color-coded indicators, controlled by JavaScript, reflect real-time equipment status, with normal conditions marked in red and fault conditions indicated in black. The novelty of this system lies in its integration of real-time data processing, dynamic visualization, and multi-channel notification mechanisms, combining web, mobile app, and messaging services like WhatsApp and email for operator alerts. This multi-layered approach improves operator response time and enhances monitoring accuracy, especially in remote or field environments. Experimental tests, including high-voltage and low-voltage fault simulations, demonstrated the system’s ability to accurately detect faults and communicate them through the notifications in real-time, with an average measurement error of just 1.56%. The system not only provides enhanced situational awareness but also offers an efficient, cost-effective solution for remote substation monitoring, ensuring continuous supervision and immediate response to power system anomalies.
Rancang Bangun Alat Pengukur Tekanan Darah Untuk Deteksi Tingkat Risiko Cardiovascular Disease Dengan Metode Fuzzy Logic Mamdani Berbasis IoT Zulfiyani, Rizka; Dani, Akhmad Wahyu; Sirait, Fadli
Jurnal Teknologi Elektro Vol 16, No 2 (2025)
Publisher : Electrical Engineering, Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/jte.2025.v16i2.001

Abstract

Hampir 3 dari 4 kematian yang terjadi di dunia disebabkan oleh penyakit tidak menular (WHO, 2022). Sekitar 73% kematian di Indonesia disebabkan oleh penyakit tidak menular dan cardiovascular disease menyumbang angka tertinggi sebesar 35% (WHO,2018). Cardiovascular disease merupakan penyakit tidak menular namun penderita penyakit tidak menular seringkali tidak menyadari dirinya mengidap penyakit hingga tanda, gejala, dan komplikasi muncul. Penelitian ini bertujuan merancang sistem Pengukur Tekanan Darah untuk Deteksi Tingkat Risiko Cardiovascular disease dengan Metode Fuzzy logic Mamdani Berbasis IoT. Prinsip kerja dari prototipe ini adalah mengukur tekanan darah menggunakan sensor tekanan MPX5050GP kemudian dengan keypad 4x4 digunakan untuk menginputkan parameter-parameter yang turut menjadi sebab dalam meningkatkan risiko cardiovascular disease yaitu tingkat kolesterol dan indeks massa tubuh. Data yang diperoleh selanjutnya akan ditampung kemudian diolah dengan fuzzy logic menggunakan metode mamdani untuk mendapatkan nilai tingkat risiko cardiovascular disease kemudian hasilnya akan ditampilkan pada LCD 16x2 dan dikirim secara wireless serta ditampilkan pada Platform IoT ThingSpeak. Pengolah data menggunakan Mikrokontroler ATMega328 yang sudah tertanam pada Arduino Uno serta ESP32 sebagai internet of things.  Berdasarkan analisa dan pengujian yang telah dilakukan didapatkan hasil akurasi pengukuran tekanan darah pada rancang bangun adalah sebesar 98,2% untuk pengukuran tekanan darah sistol dan 97,83% untuk pengukuran tekanan darah diastol. Waktu tunda rata-rata ketika ESP32 mengirim data dan IoT Platform ThingSpeak menampilkan data sebesar 15,6 detik.  Hasil akurasi untuk memprediksi risiko cardiovascular disease pada rancang bangun yang dibandingkan dengan perhitungan fuzzy logic dengan metode Mamdani pada Matlab adalah sebesar 99,69%.
Raspberry Pi 4 and Ultrasonic Sensor for Real-Time Waste Classification and Monitoring with Capacity Alert System Yuliza, Yuliza; Muwardi, Rachmat; Kusuma, Prima Wijaya; Lenni, Lenni; Rahmatullah, Rizky; Yunita, Mirna; Dani, Akhmad Wahyu
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 Fadli Sirait Fina Supegina Galang Persada Nurani Hakim Ihsan, Hafid Kartika, Eka Anggara Yuda Ketty Siti Salamah Kusnanto, Kresna Jery Kusuma, Prima Wijaya Lenni Lenni, Lenni Miharno, Satriyo Mirna Yunita Muhammad Hafizd Ibnu Hajar Rachmat Muwardi Rahmatullah, Rizky Rohilah Sahak, Rohilah Saputra, Idris Syaifullah Septiyana, Diah Simanjuntak, Imelda Uli Vistalina Suwoyo, Heru Trie Maya Kadarina Triyanto Pangaribowo Ulil Albab Yosy Rahmawati Yudhi Gunardi Yuliza Yuliza Zulfiyani, Rizka