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All Journal Infotech: Jurnal Informatika & Teknologi Multidiciplinary Output Research for Actual and International Issue (Morfai Journal)
Faisal Muttaqin
Universitas Pembangunan Nasional "Veteran" Jawa Timur
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Social Sciences Other

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DEVELOPMENT OF AN AIoT-BASED COFFEE BEAN CLASSIFICATION AND SORTING SYSTEM USING A VISION TRANSFORMER Dody Pintarko; Basuki Rahmat; Faisal Muttaqin
Multidiciplinary Output Research For Actual and International Issue (MORFAI) Vol. 6 No. 5 (2026): Multidiciplinary Output Research For Actual and International Issue
Publisher : RADJA PUBLIKA

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Abstract

Manual coffee bean sorting is highly prone to subjectivity, inconsistency, and low operational efficiency. This study aims to develop an automated classification and sorting system based on the Artificial Intelligence of Things (AIoT). The method integrates a Vision Transformer (ViT) model, TensorFlow Lite, Firebase, and an ESP32 microcontroller within a Mobile–Cloud–Edge Computing architecture. The ViT model was trained on four coffee roast levels to perform real-time inference on Android devices linked to physical sorting actuators. Experimental results showed that the ViT model achieved a 96.87% classification accuracy, while the automated physical sorting mechanism achieved 95.83% accuracy with an average response time of 462 ms. In conclusion, the integration of Vision Transformer and AIoT provides a fast and reliable post-harvest automation solution tailored for smart agricultural applications.
Sistem inkubator telur berbasis IoT menggunakan Fuzzy Self-Tuning PID Jaguar Deva Nanggalasakti Oktavian; Faisal Muttaqin; Yisti Vita Via
INFOTECH : Jurnal Informatika & Teknologi Vol 7 No 2 (2026): INFOTECH: Jurnal Informatika & Teknologi
Publisher : LPPMPK - Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/infotech.v7i2.2426

Abstract

Keberhasilan penetasan telur bergantung pada kestabilan suhu dan kelembapan di dalam inkubator. Metode kontrol konvensional seperti on-off maupun PID dengan parameter tetap dinilai kurang adaptif terhadap perubahan kondisi lingkungan yang dinamis. Penelitian ini merancang sistem inkubator telur berbasis IoT menggunakan ESP32 dengan metode Fuzzy Self-Tuning PID yang secara otomatis menyesuaikan parameter Kp, Ki, dan Kd, dilengkapi Telegram Bot untuk monitoring dan pengendalian jarak jauh secara real-time. Hasil pengujian menunjukkan metode ini unggul pada pengendalian suhu dengan MAE 0,1185°C, RMSE 0,1387°C, overshoot 0,59%, settling time 10,5 menit, dan penurunan MAE sebesar 32,94% dibandingkan PID Konvensional. Pada kelembapan, metode ini menghasilkan settling time tercepat 4,5 menit dengan MAE 0,8035%RH yang masih dalam batas toleransi inkubasi.
Co-Authors Arif Widiasan Subagio Basuki Rahmat Dody Pintarko Jaguar Deva Nanggalasakti Oktavian yisti vita via