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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal Pengabdian kepada Masyarakat Nusantara eProceedings of Engineering Telkatika: Jurnal Telekomunikasi Elektro Komputasi & Informatika
Rifqi Muhammad Fikri
Telkom University
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Social Sciences

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Research Article EVALUASI EFEKTIVITAS OTOMATISASI IRIGASI DENGAN SENSOR LINGKUNGAN PADA PERTANIAN BROKOLI anggi, anggi amalia; Faisal Candrasyah Hasibuan; Rifqi Muhammad Fikri
Telkatika: Jurnal Telekomunikasi Elektro Komputasi & Informatika Vol. 5 No. 1 (2025): Desember 2025
Publisher : Perpustakaan Universitas Telkom

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Abstract

Penelitian ini membahas pengembangan sistem monitoring dan kontrol irigasi otomatis berbasis Internet of Things (IoT) untuk budidaya tanaman brokoli. Sistem ini menggunakan mikrokontroler ESP32 yang terhubung dengan dua sensor kelembapan tanah, sensor pH tanah, dan sensor pH air, yang mengirimkan data secara real-time ke Firebase Realtime Database. Data divisualisasikan melalui aplikasi Android yang dilengkapi fitur dashboard, grafik monitoring harian dan mingguan, kontrol manual dan otomatis katup selenoid, pencatatan riwayat penyiraman, serta notifikasi otomatis. Pengujian lapangan dilakukan pada dua petak tanaman brokoli seluas ±20 m² dari total lahan petani ±2.500 m². Hasil pengujian pada lahan uji menunjukkan bahwa sistem mampu menjaga kelembapan tanah pada kisaran 60–70%, menurunkan potensi tanaman tidak tumbuh optimal dibanding metode penyiraman manual, serta membantu efisiensi penggunaan air pada area yang diuji. Pengujian white-box dan black-box memastikan seluruh fungsi berjalan sesuai rancangan dan dapat diakses dengan baik oleh pengguna. Sistem ini berpotensi menjadi solusi pendukung bagi petani dalam memantau kondisi lahan brokoli dan mengoptimalkan proses penyiraman pada skala kecil yang dapat dikembangkan lebih lanjut untuk skala lahan yang lebih luas.
LSTM Parameter Optimization with Genetic Algorithm for Stunting Prediction Rifqi Muhammad Fikri; Ayi Purbasari; Arief Zulianto; Fedri Ruluwedrata Rinawan; Ari Indra Susanti
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 1 (2025): Maret 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i1.10761

Abstract

Stunting is caused by a lack of nutrients or sickness, and stunted children may have impaired immune systems, increased mortality rates, and are more prone to endure long-term developmental abnormalities. Stunting prevalence in Indonesia remains concerningly high by the end of 2024. Through the use of integrated health posts, or pos pelayanan terpandu (Posyandu), and the technology-based website iPosyandu, attempts are being made to lower the prevalence of stunting. Using toddler data from iPosyandu, this study proposes a Long-Short Term Memory (LSTM) model for predicting stunting based on WHO standards, categorizing children as tall, normal, stunted, or severly stunted. By using a genetic algorithm (GA) for learning rate hyperparameter tuning, the LSTM model is significantly improved. Five generations, each with five populations, were used for the GA-based optimization, which explored learning rates ranging from 5.23E-04 to 8.83E-03. The results show that 7.82E-03 was the optimal learning rate, producing the greatest accuracy of 91.10%, indicating that this range improves the performance of LSTM models.
Co-Authors Akbar, Maulidiatama anggi, anggi amalia Annisa, Shavira Nur Anugerah, Rey Rizqi Ari indra Susanti Ariasa, Rafif Arief Zulianto Ashri Dinimaharawati Ayi Purbasari Azhar, Ferikho Fatih Burhanuddin Dirgantoro Butar-Butar, Muhammad Raihan Dhesvira Nurseha Putri Dirgantara, Fussy Mentari Dwiyansyah, Muhammad Raflika Dzikra, Iffat Fadhel, Hafiz Muhammad Fadhilah , Muhammad Rizal Faisal Candrasyah Hasibuan Farha S. N, Augyres Fauzaan, Muhammad Rifqi Al Fauzi, Farhan Rizki Fedri Ruluwedrata Rinawan Firdaus, Mohamad Fidi Kalista, Meta Khoerul Umam, Khoerul Malikulmulki, Jaisy Manna, Muhammad Rayyan Aqiilah Meta Kallista Prayoga, Ivan Fernanda Purba Daru Kusuma Putra, Ibrahim Bintang Rismayadi Putti, Fasya Hanifah R. Yunendah Nur Fu’adah Ramadhanti, Tassya Rita Magdalena Roswan Latuconsina Sihaloho, Mutiara Tampubolon, Yosua Gery