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Jurnal FORTECH
Published by FOERTECH
ISSN : 27209253     EISSN : -     DOI : https://doi.org/10.56795/fortech.v5i1.5107
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
Jurnal ini terbuka untuk kontribusi dari akademisi, peneliti, dan praktisi guna memperkaya diskursus ilmiah dan mendorong penerapan hasil penelitian dalam konteks nyata.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 2 Documents
 1 
Search results for , issue "Vol. 6 No. 2 (2025): In Progress" : 2 Documents clear
Optimasi Pembangkitan Ekonomis Berbasis Whale Optimization Algorithm Pada Sistem Multimesin Nurohmah, Hidayatul; Sula Cakra Buana, Arya; Rukslin, Rukslin; Ruswandi Djalal, Muhammad
Jurnal FORTECH Vol. 6 No. 2 (2025): In Progress
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v6i2.6102

Abstract

This study addresses the problem of generation cost optimization for thermal power plants in the Sulbagsel multimachine power system. An advanced swarm intelligence approach, the Whale Optimization Algorithm (WOA), is employed as the primary optimization technique. WOA, inspired by the bubble-net hunting strategy of humpback whales, has emerged as a promising metaheuristic with strong capabilities in exploration and exploitation. The main objective of this study is to minimize thermal generation costs while ensuring effective performance under real system operating conditions. To provide a comparative benchmark, Particle Swarm Optimization (PSO) is also applied to the same problem. Statistical evaluation is conducted to assess convergence behavior, accuracy, and consistency of both methods. The results indicate that WOA demonstrates superior balance between exploration and exploitation, leading to stable convergence and reliable solutions. Under peak daytime load conditions, PSO achieves a cost reduction of 23.02%, whereas the proposed WOA-based method achieves a comparable reduction of 23.78%. Although PSO yields a slightly higher cost saving, WOA demonstrates stronger robustness and statistical reliability across multiple trials. These findings confirm that WOA is a competitive alternative for generation cost optimization in complex multimachine systems, offering significant potential for future applications in economic dispatch problems with larger-scale renewable energy integration.
Sistem Kontrol Kompor Gas Pintar Berbasis Internet Of Things (IoT) Fahrul Hidayat, Faruq Dwi; Abidin, Zainal; Ilmi, Ulul
Jurnal FORTECH Vol. 6 No. 2 (2025): In Progress
Publisher : FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56795/fortech.v6i2.6106

Abstract

Penggunaan kompor gas dalam rumah tangga memiliki risiko seperti kebocoran gas, kelalaian mematikan api, dan penggunaan gas berlebih yang dapat menyebabkan kebakaran. Penelitian ini bertujuan untuk merancang sistem kontrol kompor gas pintar berbasis Internet of Things (IoT) yang mampu meningkatkan keselamatan dan efisiensi penggunaan. Sistem ini dirancang menggunakan mikrokontroler ESP32, sensor suhu LM35, sensor gas MQ-2, sensor berat Load Cell, valve solenoid, dan modul pemantik otomatis, serta aplikasi Blynk sebagai antarmuka monitoring jarak jauh. Sensor akan mendeteksi suhu, berat tabung, dan keberadaan gas. Jika terjadi kebocoran gas atau suhu melebihi ambang batas, sistem secara otomatis akan mematikan aliran gas dan memberikan notifikasi melalui aplikasi. Berdasarkan hasil pengujian, sistem dapat mendeteksi gas pada konsentrasi 600 ppm, memutus aliran gas dengan waktu respon kurang dari 1 detik, serta dapat dikontrol dengan akurasi tinggi melalui aplikasi Blynk. Sistem ini terbukti efektif dalam meningkatkan keamanan dan memberikan kontrol otomatis terhadap penggunaan kompor gas

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