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Identification Food Nutrition and Weight Prediction using Image Processing Sani, Abdullah; Silitonga, Ricky; Mishthafiyatillah, Mishthafiyatillah; Lalu Kaisar Wisnu Kita; Ika Karlina Laila Nur Suciningtyas; Ririn Humaera; Budiana , Budiana
Journal of Applied Electrical Engineering Vol. 9 No. 1 (2025): JAEE, June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaee.v9i1.9492

Abstract

Obesity is a global issue with rising prevalence each year, driven partly by excess nutrient and calorie intake. Identifying nutrient content in food is vital to prevent obesity. This research employs image processing, specifically the YOLO (You Only Look Once) algorithm, to classify and identify fruits and vegetables quickly and accurately. YOLO is advantageous for its speed and ability to classify multiple objects simultaneously. The goal is to develop a system that recognizes, classifies, and predicts the weight of fruits and vegetables, providing nutritional and calorie information. Tests showed that the system accurately detects produce under various lighting conditions—achieving 100% accuracy with additional ring light (600–650 lux) and 99.2% without extra lighting. Beyond object detection, the system predicts weight with an average error of 5.6% when illuminated. This technology has the potential to aid users in monitoring nutritional intake by providing reliable identification and calorie data, contributing to obesity prevention efforts.
Rancang Bangun dan Monitoring Sistem Pengering Sepatu Menggunakan Logika Fuzzy  Berbasis Mikrokontroler ESP8266 Lalu Kaisar Wisnu Kita; Mishthafiyatillah; M. Surya Bagus Rangkuti; Febran Danuarta
Journal of Golden Generation Engineering Vol. 2 No. 1 (2026): Januari 2026 : Journal of Golden Generation Engineering
Publisher : PT. Lembaga Penerbit Penelitian Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65244/jggengineering.v2i1.361

Abstract

Di Indonesia, pengeringan sepatu sering bergantung pada sinar matahari yang tidak selalu tersedia, terutama saat cuaca buruk. Penelitian ini mengembangkan alat pengering sepatu berbasis Internet of Things (IoT) yang andal dan efisien. Alat ini dilengkapi pemanas PTC, kipas DC, sensor DHT untuk memantau suhu dan kelembapan, serta sensor beban HX711 untuk mendeteksi kadar air. Sistem fuzzy digunakan untuk mengatur suhu dan kelembapan secara otomatis agar tetap optimal selama proses pengeringan. Hasil pengujian menunjukkan alat ini mampu mengurangi kadar air hingga 99,7% pada suhu 50 °C. Waktu pengeringan bervariasi tergantung bahan sepatu: kain (65% kelembapan) selama 120 menit, kanvas (85,5%) selama 125 menit, dan kulit (91%) selama 145 menit. Alat ini juga mendukung pemantauan dan pengendalian secara real-time melalui aplikasi web berbasis IoT, sehingga memudahkan pengguna dalam mengontrol proses pengeringan sepatu kapan saja dan di mana saja.