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All Journal ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Jurnal Otomasi Kontrol dan Instrumentasi
RUSANTO, BENYAMIN HERYANTO
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Chemical Engineering, Chemistry & Bioengineering Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Performance Comparison of 1D-CNN and LSTM Deep Learning Models for Time Series-Based Electric Power Prediction SUKATMO, SUKATMO; NUGROHO, HAPSORO AGUNG; RUSANTO, BENYAMIN HERYANTO; SOEKIRNO, SANTOSO
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 13, No 1: Published January 2025
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v13i1.44

Abstract

Accurate electrical power prediction is essential for efficient energy management, especially in institutions with dynamic energy needs. This study compares the performance of 1D-CNN and LSTM for time series based electrical power prediction, using a dataset from the Building Automation System (BAS) of STMKG building. The evaluation metrics Mean Squared Error (MSE) and Mean Absolute Error (MAE) are used to measure accuracy. The results show that the LSTM had an average MSE value of 3.35E-04±0.00013 and an MAE of 0.01312±0.0079 across 10 trials. This is slightly better than the 1D-CNN, which had an average MSE value of 4.68E-04±0.0003 and an MAE of 0.01855±0.00586. Despite the marginal difference, 1D-CNN provides a computational time efficiency advantage of 63.08s, 1D-CNN is about 84.19% faster.
Rancang Bangun Intensitymeter Berbasis MEMS Dengan Algoritma Pendeteksi Kejadian STA/LTA dan Sistem Peringatan Multi-Saluran Rawana, Aziz; Rusanto, Benyamin Heryanto; Trihadi, Edward; Nardi, Nardi
Jurnal Otomasi Kontrol dan Instrumentasi Vol 17 No 2 (2025): Jurnal Otomasi Kontrol dan Instrumentasi
Publisher : Pusat Teknologi Instrumentasi dan Otomasi (PTIO) - Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/joki.2025.17.2.8

Abstract

Indonesia is an earthquake-prone country due to its location at the convergence of three major tectonic plates. To support disaster mitigation, a reliable and affordable monitoring system is required. This study presents a low-cost intensitymeter using a MEMS WT61C sensor with the STA/LTA detection algorithm, Raspberry Pi 4 for processing, and a Ublox Neo-M8N GNSS module for time and location synchronization. The system supports online and offline modes with a store-and-forward mechanism and delivers alerts via buzzer, SMS, and Telegram. The WT61C was configured with 20 Hz bandwidth and 100 Hz sampling rate. Tests showed the device detected local earthquakes, calculated Peak Ground Acceleration (PGA), and estimated Modified Mercalli Intensity (MMI). In simulations of the Lombok 2018 earthquake (M7.0), it produced PGA values of 0.5704 g (23.3% error) and 0.7495 g (0.8% error) against the reference 0.744 g, both consistent with MMI VIII. SMS was sent serially with 5–7 s latency, while Telegram worked in real time. Validation was limited to a simulator with one dataset, without diverse soil or magnitude scenarios. In conclusion, the system provides an effective, low-cost solution for earthquake intensity monitoring and has potential for early warning applications.
Design and Construction of Low-Cost Seismometer using Geophone Sensor Based on Single Board Computer FAUZAN, RAIHAN AHMAD; RUSANTO, BENYAMIN HERYANTO; SINAMBELA, MARZUKI; TRIHADI, EDWARD
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 13, No 4: Published November 2025
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v13i4.381

Abstract

Salah satu faktor utama dalam upaya peningkatan sistem pemantauan seismik adalah penyebaran dan interkoneksi jaringan seismograf secara menyeluruh. Penggunaan geophone dapat menjadi solusi alternatif yang potensial dalam membuat low-cost seismograf untuk meningkatkan cakupan dan efisiensi jaringan pemantauan seismik. Penelitian ini bertujuan untuk merancang low-cost seismometer yang terdiri dari sensor geophone, rangkaian signal conditioning, modul ADC ADS1256, GPS Ublox Neo-7M, dan Raspberry Pi 3 Model B+. Data ditampilkan melalui antarmuka berbasis website secara realtime menggunakan protokol komunikasi MQTT dan disimpan dalam format miniSEED. Hasil pengujian menunjukkan tingkat background noise pada sensor yang cukup baik (84.8% titik frekuensi berada dalam batasan NHNM/NLNM), dengan kemampuan mendeteksi gempa lokal pada magnitude ≥3.0. Prototipe ini memberikan solusi low-cost seismograf yang efektif untuk pemantauan seismik.
Design and Development of IoT-Enabled Portable Device for Multiparameter Air Quality Monitoring ADINARA, DERBY BRYLIAN; RACHMAWARDANI, AGUSTINA; WASTUMIRAD, ADI WIDIATMOKO; RUSANTO, BENYAMIN HERYANTO; PRASETYO, DWI INDRA; KURNIAWAN, HANIF; HANI, ABDUL MANAF
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 13, No 4: Published November 2025
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v13i4.339

Abstract

The limitations of Indonesia's air quality monitoring infrastructure have prompted research to develop portable Internet of Things (IoT)-based monitoring devices. The system is designed using ESP32 and Arduino Uno integrated with MQ136 (SO2), MQ131 (NO2), MiCS-5524 (CO), TGS-2611 (CH4), Gravity-0460 (PM), and Gravity-0321 (O3) sensors. Data is converted into AQI values and displayed via LCD, Telegram, and website. The device is equipped with an early warning system that includes a buzzer, a website pop-up, and Telegram messages. Field testing results over 24 hours at POS KU Cibeureum recorded peak concentrations of PM2.5 (19 μg/m³), PM10 (58 μg/m³), NO₂ (1.375 ppb), CO (238 ppb), SO₂ (0.74 ppb), and O₃ (45 ppb). The device can be operated portably with the following dimensions: enclosure I, 20×20 cm; enclosure II, 7×12 cm; control panel box, 30×40 cm (pre-assembled) and 100×180 cm (post-assembled). The device has proven effective as an adaptive monitoring solution for residential areas surrounding industrial zones.
Co-Authors ADINARA, DERBY BRYLIAN FAUZAN, RAIHAN AHMAD HANI, ABDUL MANAF Hapsoro Agung Nugroho Kurniawan, Hanif Marzuki, Sinambela Nardi, Nardi Prasetyo, Dwi Indra Rachmawardani, Agustina Rawana, Aziz Soekirno, Santoso Sukatmo, Sukatmo Trihadi, Edward Wastumirad, Adi Widiatmoko