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All Journal Jurnal Edukasi Elektro JURNAL NASIONAL TEKNIK ELEKTRO JMECS (Journal of Measurements, Electronics, Communications, and Systems) Journal of Applied Electrical Engineering Jurnal Litek : Jurnal Listrik Telekomunikasi Elektronika JURNAL ILMIAH SAINS TEKNOLOGI DAN INFORMASI Media Elektrik Energy Insights
Wirasapta , Andicho Haryus
Universitas Jambi
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology

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Designing a Google Voice-Based Solar Panel Cleaner Control System Tessal, Dasrinal; Marzal, Jefri; Triantini, Dewi; Wirasapta , Andicho Haryus; Fikri , Muhammad Khalis; Saputra , Angga Riyan Trio; Mishi , Salmuna Sajjad
Jurnal Edukasi Elektro Vol. 9 No. 2 (2025): Jurnal Edukasi Elektro Volume 9, No. 2, November 2025
Publisher : DPTE FT UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jee.v9i2.90041

Abstract

Current solar panel maintenance often involves manual, rooftop fieldwork, which introduces significant fall-from-height risks and occupational hazards. To address this, this research investigates the integration of the Internet of Things (IoT) to streamline and enhance operational efficiency. The goal is to develop an IoT-enabled solution for user-driven routine maintenance that can significantly mitigate occupational hazards and reduce maintenance duration. This system is designed to optimize the long-term energy yield of solar panels by preventing the typical efficiency decline caused by neglected upkeep. The study employs a prototype development method (literature review, construction model design, and control system development). The final system leverages common consumer-grade terminal devices (smartphones, laptops) to provide a ubiquitous, real-time control interface, allowing users to manage the system remotely via a stable network connection.
Design and Simulation of a QPSK Demodulator Using Discrete Components Andicho Haryus Wirasapta; Salisa 'Asyarina Ramadhani; Mishi , Salmuna Sajjad; Malik, Zeeshan Hamid
JURNAL NASIONAL TEKNIK ELEKTRO Vol 14, No 3: November 2025
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v14n3.1386.2025

Abstract

Quadrature Phase Shift Keying (QPSK) is a widely adopted digital modulation technique that encodes two bits of information in each symbol by utilizing four distinct phase states separated by 90 degrees. This approach offers high spectral efficiency, making it especially suitable for modern communication systems that demand robust data transmission with limited bandwidth. This investigation details the design process and LTspice-based simulation of a QPSK demodulator constructed entirely from discrete electronic components. This work addresses a gap in previous research, which has largely relied on integrated circuits or software-based algorithms, by focusing on circuit-level implementation using basic analog and digital components. The demodulator was assembled on a prototype PCB, combining fundamental operational amplifiers, mixers, filters, and digital logic gates to perform the required signal processing functions. The evaluation involved testing the demodulator's ability to accurately recover the transmitted data and its operational stability. Simulation results demonstrated reliable performance across all stages, with the demodulator successfully maintaining phase detection accuracy and reconstructing the original 8-bit test sequence with high fidelity. Under test conditions with a 1 MHz carrier frequency and a data transmission rate of 500 kHz, the recovered signal showed an approximate delay of 4.5 microseconds attributable to the sequential parallel-to-serial conversion process. Despite the delay, the demodulator maintained full symbol-level correlation with the transmitted data stream. These findings confirm that a discrete component-based QPSK demodulator can effectively support reliable digital communication, highlighting its practicality for educational purposes, low-cost prototyping, laboratory training, and preliminary hardware development in the field of wireless and wired communication systems.
Banana Ripeness Classification Using Convolutional Neural Network Based on Resnet-50 Khalis Fikri, Muhammad; 'Asyarina Ramadhani, Salisa; Haryus Wirasapta, Andicho; Rabiula, Andre; Anzari, Yandi; Alghifari, Hamzah; Sajjad Mishi, Salmuna
Jurnal Media Elektrik Vol. 23 No. 2 (2026): MEDIA ELEKTRIK
Publisher : Jurusan Pendidikan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/metrik.v23i2.11482

Abstract

The manual assessment of banana ripeness on an industrial scale is subjective, time-consuming, and inconsistent. This necessitates an automated computer vision system. Previous studies have used shallow Convolutional Neural Networks (CNNs) for binary classification, but these networks often struggle with complex ripening stages and degrade in deeper networks. This study addresses this gap by implementing a deep learning algorithm using the ResNet-50 architecture. The residual block mechanism extracts fine-grained visual features without vanishing gradient issues. The model was evaluated using a diverse dataset of 13,478 digital images spanning four stages of banana ripeness: overripe, ripe, rotten, and unripe. Using a 95-5 train and test-validation split, the model was optimized over 50 epochs with a categorical cross-entropy loss function. The proposed model achieved outstanding accuracy (98.13%), minimal loss (0.1237), and average precision, recall, and F1-scores of 98.09%, 98.20%, and 98.14%, respectively. This study scientifically validates the robustness of deep residual networks in complex agro-industrial pattern recognition. Furthermore, with an inference time of approximately 50 ms per image, the system is ready for seamless integration into an automated sorting line.
Simulation-Based Analysis of Packet Scheduling Strategies and Traffic Load Effects on Network QoS Wirasapta, Andicho Haryus; Pamungkas, Tiara Deta; Mishi , Salmuna Sajjad
Energy Insights Vol. 1 No. 2 (2026): Energy Insights
Publisher : Teknik Elektro, Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/ei.v1i2.11311

Abstract

This study addresses a significant gap in quality of service (QoS) simulation research by evaluating the impact of packet scheduling mechanisms on network performance under varying traffic loads and link capacities. Using MATLAB simulations, we introduce a novel framework to assess the performance of FIFO, Priority Scheduling, and Weighted Round Robin (WRR) mechanisms in a network supporting voice, video, and data traffic. The results highlight that WRR provides the most balanced performance, achieving lower delay (59 ms), reduced jitter (11 ms), higher throughput (4.18 Mbps), and lower packet loss (3.2%) compared to FIFO and priority scheduling. This study fills a critical gap by offering new insights into QoS performance across heterogeneous network environments, with practical implications for optimizing network performance. Furthermore, the findings contribute to theoretical research by demonstrating the need for adaptive scheduling strategies in real-time communication networks, especially under high-traffic conditions.
Integrating Green IT into IS/IT Strategic Planning: A Ward and Peppard Framework for Sustainable Digital Transformation in Higher Education Pujiono, Agung; Samopa, Febriliyan; Rabiula, Andre; Haryus Wirasapta, Andicho; Fikri Muhammad , Khalis Fikri
Jurnal Media Elektrik Vol. 23 No. 2 (2026): MEDIA ELEKTRIK
Publisher : Jurusan Pendidikan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/metrik.v23i2.11875

Abstract

The development of information systems and information technology (IS/IT) has significantly transformed higher education; however, inadequate strategic planning often leads to inefficiencies and environmental impacts, such as high energy consumption and electronic waste. Despite the growing importance of sustainability, existing IS/IT strategic planning approaches generally do not explicitly integrate environmental considerations, thus creating a gap between digital transformation and sustainability objectives. This study aims to develop an IS/IT strategic planning framework that integrates green IT principles within the Ward and Peppard methodology. A qualitative case study approach was applied at Akademi Farmasi Yarsi Pontianak using data collected through interviews, observations, and questionnaires. The analysis incorporated multiple frameworks, including the Balanced Scorecard, PEST, Porter’s Five Forces, SWOT, and Critical Success Factors. The results produced integrated IS/IT strategies that align organizational goals with sustainability principles, including the development of information systems, environmentally oriented IT infrastructure, and governance mechanisms that support green IT implementation. The findings indicate that integrating green IT into IS/IT strategic planning can enhance operational effectiveness while contributing to environmental sustainability. This study contributes by extending the Ward and Peppard framework through the explicit incorporation of environmental sustainability as a strategic dimension, providing a practical and replicable model for higher education institutions pursuing sustainable digital transformation.
Real-Time IoT Temperature Monitoring Using Xiaomi Mijia BLE, ESP32, MQTT, and EMQX Andicho Haryus Wirasapta; Tiara Deta Pamungkas
Journal of Applied Electrical Engineering Vol. 10 No. 1 (2026): JAEE, June 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaee.v10i1.12012

Abstract

This paper proposes a low-cost IoT-based real-time temperature and humidity monitoring system as a Bluetooth Low Energy (BLE) to MQTT bridge using an ESP32 microcontroller, Xiaomi Mijia LYWSD03MMC sensor, and EMQX broker. The key novelty of this work lies in the quantification of end-to-end communication performance of a BLE–Wi-Fi–MQTT bridge architecture using commercial off-the-shelf components. Five repeated measurement trials were conducted to evaluate system performance. Results show a mean end-to-end latency of 318 ms (standard deviation: 16,4 ms, max: 342 ms), a packet delivery ratio of 99,6%, and a sensor accuracy of RMSE=0,22°C against a calibrated digital reference thermometer. The system operated continuously for 48 hours with 99,6% uptime and a single automatic reset. Compared to HTTP-based counterparts, the proposed BLE–MQTT bridge achieves 36,6% lower latency. These results confirm the feasibility of integrating proprietary BLE sensors into mainstream MQTT-based IoT platforms using a lightweight and replicable architecture.
Adaptive Control Optimization for Solar Energy Storage Systems Using Fuzzy Logic, Genetic Algorithms, and State of Charge Estimation Andicho Haryus Wirasapta; Tiara Deta Pamungkas
JMECS (Journal of Measurements, Electronics, Communications, and Systems) In Press Papers
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jmecs.v12i2.10090

Abstract

The intermittent nature of solar energy results in a generation versus load curve, thus becoming a significant challenge for reliable utilization. The use of a battery energy storage system, on the other hand, plays a vital role in uninterrupted power supply; however, it requires advanced control techniques for smooth functionality. The use of conventional techniques, such as a classical Maximum Power Point Tracking scheme based on Constant Current/Constant Voltage, becomes inefficient for dealing with nonlinear dynamics associated with system functionality, thereby reducing battery life. The proposed composite approach incorporates fuzzy logic decision-making, Genetic Algorithm optimization, and adaptive Extended Kalman Filter estimation for quantifying real-time battery state. A comprehensive PV-BESS model has been developed in the environment of a MATLAB/Simulink toolbox, using actual load as well as actual solar irradiance. The results based on the proposed approach indicate improvement in energy efficiency of 20% along with 5% accuracy in battery state estimation while extending battery life to 18-25% compared to conventional battery energy storage systems. The proposed approach provides a robust, optimizing, as well as a viable solution set for the PV-BESS system, thereby paving the way for future micro-grid development.
Simulasi Keputusan Handover Cerdas berbasis Support Vector Machine pada Jaringan Nirkabel Menggunakan Matlab Andicho Haryus Wirasapta; Tiara Deta Pamungkas
Jurnal Litek : Jurnal Listrik Telekomunikasi Elektronika Vol. 23 No. 1 (2026): Jurnal Litek, Maret 2026
Publisher : Jurusan Teknik Elektro Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/litek.v23i1.104

Abstract

Manajemen mobilitas merupakan tantangan utama dalam jaringan seluler nirkabel akibat dinamika kanal dan mobilitas pengguna, di mana skema handover konvensional berbasis ambang RSS atau SINR sering memicu handover tidak perlu dan efek ping-pong. Penelitian ini mengusulkan mekanisme keputusan handover cerdas berbasis kecerdasan buatan menggunakan Support Vector Machine (SVM) dengan integrasi fitur RSS, SINR, kecepatan pengguna, dan beban base station. Evaluasi melalui simulasi MATLAB pada kondisi kanal dan mobilitas yang realistis menunjukkan bahwa pendekatan yang diusulkan mampu mengurangi jumlah handover dan kejadian ping-pong lebih dari 50%, menurunkan probabilitas packet loss sekitar 6%, serta meningkatkan effective throughput sekitar 6% dibandingkan dengan skema berbasis threshold konvensional. Hasil ini menegaskan kontribusi ilmiah utama penelitian dalam merumuskan dan mengevaluasi mekanisme keputusan handover berbasis SVM yang mengintegrasikan parameter kanal dan mobilitas secara simultan, serta secara kuantitatif menunjukkan peningkatan kinerja jaringan dibandingkan dengan skema handover berbasis threshold konvensional.
Klasifikasi Tinggi Awan dari Citra Satelit Himawari-8 Menggunakan Fuzzy C-Means, GLCM, dan KNN. Togi Simarmata; Elsa Lolita Anggraini; Abdul Manab; Muhammad Khalis Fikri; Andicho Haryus Wirasapta; Elsi Alfionita Syawal
JURNAL ILMIAH SAINS TEKNOLOGI DAN INFORMASI Vol. 4 No. 3 (2026): Juli : Jurnal Ilmiah Sains Teknologi dan Informasi
Publisher : CV. ALIM'SPUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59024/jiti.v4i3.2204

Abstract

Monitoring ketinggian awan merupakan parameter penting dalam observasi meteorologi yang berperan strategis dalam analisis dinamika atmosfer serta prediksi cuaca ekstrem. Penelitian ini bertujuan mengembangkan sistem klasifikasi otomatis untuk mengategorikan awan rendah, awan menengah, dan awan tinggi menggunakan citra satelit Himawari-8. Metodologi penelitian mencakup empat tahapan utama: pre-processing untuk standardisasi data, segmentasi menggunakan metode Fuzzy C-Means (FCM) untuk memisahkan objek awan, ekstraksi fitur tekstur berbasis Gray Level Co-occurrence Matrix (GLCM) dengan sembilan parameter, serta klasifikasi menggunakan algoritma K-Nearest Neighbor (K-NN). Data penelitian bersumber dari BMKG Stasiun Meteorologi Cengkareng, Tangerang. Pengujian sistem dilakukan melalui empat skenario eksperimen dengan volume data uji sebanyak 20, 30, 40, dan 50. Hasil penelitian menunjukkan bahwa sistem mampu mendeteksi kategori awan rendah dengan tingkat akurasi yang sangat tinggi, bahkan mencapai performa sempurna pada beberapa parameter efektivitas. Fenomena tumpang tindih (overlapping) pada nilai parameter fitur tekstur antar kelas menyebabkan algoritma K-NN sulit menentukan batas keputusan yang optimal. Secara keseluruhan dari 3 ketinggian awan yang dilakukan, awan rendah dapat diklasifikasikan dengan baik dibanding dengan awan tengah dan awan tinggi. Dari 4 percobaan hasil akurasi untuk awan rendah adalah 100%. Sedangkan untuk awan tengah akurasi yang dihasilan 72,45% dan awan tinggi 90,95%. Penelitian ini merekomendasikan adanya integrasi yang lebih adaptif antara tahap segmentasi dan ekstraksi ciri guna meminimalisir bias klasifikasi pada satu kelas tertentu dan meningkatkan akurasi sistem secara menyeluruh pada seluruh tingkatan awan.
Co-Authors Abdul Manab Alghifari, Hamzah Andre Rabiula Dasrinal Tessal Dewi Triantini Elsa Lolita Anggraini Elsi Alfionita Syawal Febriliyan Samopa Fikri , Muhammad Khalis Fikri Muhammad , Khalis Fikri Jefri Marzal Khalis Fikri, Muhammad Malik, Zeeshan Hamid Mishi , Salmuna Sajjad Muhammad Khalis Fikri Pamungkas, Tiara Deta Pujiono, Agung Ramadhani, Salisa 'Asyarina Sajjad Mishi, Salmuna Saputra , Angga Riyan Trio Tiara Deta Pamungkas Tiara Deta Pamungkas Togi Simarmata Yandi Anzari