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All Journal Jurnal Teknologi Elektro PROtek : Jurnal Ilmiah Teknik Elektro Jurnal Pengabdian Kepada Masyarakat Emitor: Jurnal Teknik Elektro
Andriani Andriani
Universitas Pamulang
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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APLIKASI MIKROKONTROLER BERBASIS REAL-TIME CLOCK (RTC) UNTUK AKURASI WAKTU IBADAH DI MUSHOLLA Gaguk Firasanto; Andriani Andriani; Ronald Pakan; Raka Muhammad Hazli; Muhammad Rizky Ramadhan; Rakha Akbar Andikha
Jurnal Pengabdian kepada Masyarakat Vol. 13 No. 1 (2026): JURNAL PENGABDIAN KEPADA MASYARAKAT 2026
Publisher : P3M Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/abdimas.v13i1.9822

Abstract

The primary problem faced by the Musholla congregation is the lack of accurate prayer time indicators due to manual clocks experiencing time drift, causing inconsistencies with official schedules. Additionally, there is limited interactive information media. This community service aims to implement a microcontroller-based Running Text system integrating the DS3231 Real-Time Clock (RTC) module. This module offers high precision and internal temperature compensation to maintain long-term time stability. The system automatically displays five daily prayer schedules based on geographical coordinates and serves as a dynamic information medium. The methods involved field surveys, hardware and software design, installation in the mosque, and training for mosque officials on operation and maintenance. The outcomes include a modern, accurate worship schedule system, increased congregation discipline in timely prayers, and improved information dissemination. Through this activity, the congregation directly benefits from easy access to precise worship times and the cultivation of appropriate technology utilization in a sustainable place of worship.
Sistem Proteksi Aktif Berbasis Logika OR Perangkat Lunak Untuk Mencegah Overheat Dan Overcurrent Pada Power Amplifier Kelas D Andriani Andriani; Gaguk Firasanto
Jurnal Teknologi Elektro Vol. 17 No. 2 (2026)
Publisher : Electrical Engineering, Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/jte.2026.v17i2.006

Abstract

Abstrak— Perangkat penguat daya audio (Power Amplifier) kelas D memiliki efisiensi tinggi namun rentan mengalami kerusakan fatal akibat panas berlebih (overheat) dan arus pendek (short circuit) pada beban speaker. Sistem proteksi konvensional yang mengandalkan sekring (fuse) dinilai memiliki respon lambat, bersifat pasif, dan tidak menyediakan data historis untuk analisis pasca-kegagalan. Penelitian ini bertujuan merancang sistem proteksi aktif yang cerdas dan informatif berbasis mikrokontroler Arduino Nano. Sistem dirancang mengintegrasikan sensor LM35 untuk mendeteksi suhu heatsink dan sensor INA219 untuk memantau arus beban secara digital via protokol I2C. Untuk mengatasi fluktuasi sinyal sensor (noise), diterapkan metode hybrid filtering yang menggabungkan resistor pull-down 10kΩ pada perangkat keras dan algoritma Outlier Rejection pada perangkat lunak. Pengambilan keputusan pemutusan arus dilakukan menggunakan Gerbang Logika OR pada antarmuka Python. Hasil pengujian menunjukkan sistem mampu memutus arus (cut-off) secara otomatis saat suhu heatsink melampaui 60°C atau arus beban melebihi 2.0 A. Berdasarkan hasil kalibrasi, sensor suhu LM35 memiliki rata-rata kesalahan (error) sebesar 0.35% dan sensor arus INA219 memiliki rata-rata kesalahan sebesar 1.29% dibandingkan alat ukur standar. Sistem proteksi ini terbukti efektif mencegah kerusakan komponen amplifier akibat panas berlebih dan lonjakan arus.
Performance Analysis of Logic Gate-Based Power Amplifier Protection with Hybrid Filtering gaguk firasanto; Andriani Andriani; Kiswanta Kiswanta
PROtek : Jurnal Ilmiah Teknik Elektro Vol 13 No 2 (2026): Protek : Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v13i2.11567

Abstract

Class-D audio power amplifiers deliver high operational efficiency but remain highly susceptible to catastrophic failures induced by thermal runaway and overcurrent events. Conventional protection mechanisms, such as passive fuses, typically exhibit delayed response times and lack the capability to record historical diagnostic data. This study designs and implements an active, intelligent protection framework driven by an Arduino Nano microcontroller and a Python-based interface. The methodology integrates an LM35 thermal sensor and an INA219 digital current monitor, strictly validated through a one-point calibration procedure and enhanced by a hybrid filtering technique to eliminate signal noise. A digital OR logic gate algorithm is applied to execute rapid decision-making. Experimental results demonstrate exceptional measurement precision, achieving an average relative error of only 0.43% for temperature and 1.16% for current. The logic-based actuator successfully and instantaneously disconnected the power load during simulated fault conditions whenever the predefined safety thresholds (60°C or 2.0 A) were exceeded. Furthermore, the integrated data logger effectively captured real-time failure telemetry for post-incident evaluation. In conclusion, the proposed digital logic framework provides a highly responsive, data-driven, and superior preventive alternative to traditional passive audio amplifier protection.
Implementation of Centralized IoT Safety Latching for Class-D Amplifiers: QoS Analysis and OTA Integration Gaguk Firasanto; Andriani Andriani; Donie Agus Ardianto; Zainin Widadi; Donal Karyano
Emitor: Jurnal Teknik Elektro Vol 26, No 2: July 2026
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/emitor.v26i2.17831

Abstract

Class-D audio power amplifiers deliver high operational efficiency but remain exceptionally vulnerable to catastrophic failures induced by thermal runaway and output overcurrent. While traditional passive protections and localized active systems isolate faults, they often lack centralized remote monitoring capabilities and seamless software maintainability. This research proposes a Centralized Internet of Things (IoT) protection system using an ESP32 microcontroller as a telemetry node, integrated with INA219 and LM35 precision sensors. Unlike decentralized systems, the core Safety Latching algorithm (OR logic) is processed centrally on a Python-based Graphical User Interface (GUI) server via the MQTT protocol. Furthermore, an Over-The-Air (OTA) firmware update mechanism is integrated for wireless software maintenance. Experimental results demonstrate high measurement accuracy, yielding average errors of less than 1% for temperature and 2% for current. The centralized safety latching algorithm operated robustly, successfully disconnecting the amplifier load at critical thresholds (75.1°C and 3.48 A) and effectively preventing destructive power oscillation by enforcing a manual reset state. The integration of OTA updates proved successful for remote firmware deployment without physical hardware intervention. In conclusion, the proposed centralized IoT framework significantly enhances the diagnostic reliability, safety, and long-term maintainability of high-power audio systems.
Hybrid Bayesian Optimization and Deep Reinforcement Learning for Enhanced MPPT in PV Systems Under Dynamic Conditions Firas Maulana Lasidi; Jangkung Raharjo; Basuki Rahmat; Andriani Andriani
Emitor: Jurnal Teknik Elektro Vol 26, No 2: July 2026
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/emitor.v26i2.18469

Abstract

Abstract − Conventional Maximum Power Point Tracking (MPPT) methods in photovoltaic (PV) systems frequently suffer from significant efficiency degradation when subjected to dynamic weather and Partial Shading Conditions (PSC). To address this issue, this study proposes a novel hybrid control algorithm integrating Bayesian Optimization (BO) and Deep Reinforcement Learning (DRL). The primary contribution of this research is the development of an adaptive MPPT system architecture that leverages the global exploration capabilities of BO alongside the high-precision local tuning of DRL to maximize solar energy extraction. The methodology evaluates the proposed BO-DRL agent through an ablation study within a Python simulation environment across four distinctive environmental profiles: uniform irradiance, light partial shading, heavy partial shading, and extreme dynamic conditions. In this framework, the BO component executes a probabilistic global search via Gaussian Processes to prevent the system from getting trapped in local maxima, while the DRL agent performs continuous duty cycle adjustments to minimize steady-state oscillations. Simulation results demonstrate that the hybrid approach significantly outperforms the conventional Perturb and Observe (P&O) method. Under heavy partial shading, the hybrid algorithm achieves a tracking efficiency of 96.08%, whereas the P&O method drops to 62.24% due to local peak entrapment. Under extreme dynamic scenarios, the hybrid efficiency remains robust at 93.22%, while the P&O performance drastically degrades to 39.07%. Furthermore, the ablation validation proves that standalone DRL agents fail to initialize optimally without the global search assistance from the BO unit. In conclusion, the synergistic integration of BO-DRL yields a highly robust, efficient, and adaptive MPPT control solution capable of optimizing PV energy harvesting in highly volatile environments.
Co-Authors Basuki Rahmat Donal Karyano Donie Agus Ardianto Firas Maulana Lasidi Gaguk firasanto Jangkung Raharjo Kiswanta Kiswanta Muhammad Rizky Ramadhan Raka Muhammad Hazli Rakha Akbar Andikha Ronald Pakan Zainin Widadi