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All Journal Infotech Journal JUPITER (Jurnal Pendidikan Teknik Elektro) JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jiko (Jurnal Informatika dan komputer) Indonesian Journal of Applied Informatics Jurnal Teknologi Progresif: Jurnal Ilmiah Komputer International Journal of Economics, Business and Accounting Research (IJEBAR) bit-Tech JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) JUKI : Jurnal Komputer dan Informatika Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Infotek : Jurnal Informatika dan Teknologi Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Jurnal Teknik Informatika Duta.com : Jurnal Ilmiah Teknologi Informasi dan Komunikasi Prosiding Seminar Nasional Hasil-hasil Penelitian dan Pengabdian Pada Masyarakat Duta Abdimas: Jurnal Pengabdian Masyarakat Proceeding of International Conference Health, Science And Technology (ICOHETECH) Politeknosain Adopsi Teknologi dan Sistem Informasi Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Innovative: Journal Of Social Science Research Equivalent : Journal of Economic, Accounting and Management Journal of Information Technology
Afu Ichsan Pradana
Universitas Duta Bangsa Surakarta
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

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Otomatisasi Pemberian Pakan Ikan Koi Berbasis IoT dengan ESP8266 dan Aplikasi Blynk Ila Aulia Rahmah; Joni Maulindar; Afu Ichsan Pradana
IJAI (Indonesian Journal of Applied Informatics) Vol 9, No 2 (2025)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v9i2.95848

Abstract

Abstrak : Ikan koi merupakan salah satu jenis ikan hias yang memerlukan perawatan intensif, khususnya dalam hal pemberian pakan secara rutin agar tumbuh dengan optimal. Kendala dalam menjaga jadwal pemberian pakan sering dialami oleh pemelihara, terutama yang memiliki mobilitas tinggi. Oleh karena itu, penelitian ini bertujuan merancang dan membangun prototype sistem otomatisasi pemberian pakan ikan koi berbasis Internet of Things (IoT) yang dapat dikontrol melalui aplikasi Blynk pada perangkat mobile. Sistem ini menggunakan mikrokontroler ESP8266 untuk mengatur mekanisme pengeluaran pakan yang dioperasikan dengan motor servo. Dengan sistem otomatis ini, pemberian pakan dapat dilakukan pada waktu yang telah ditentukan secara konsisten, sehingga kesehatan dan pertumbuhan ikan koi dapat terjaga. Prototype ini dirancang menggunakan metode waterfall yang mencakup tahap analisis sistem, perancangan, implementasi, dan pengujian. Hasil pengujian menunjukkan bahwa sistem ini dapat bekerja secara efektif sesuai jadwal yang diatur dari jarak jauh dengan tingkat keberhasilan sistem sebesar 95% dan keterlambatan koneksi pada jaringan rata-rata 1 detik.===================================================Abstract :Koi fish are a type of ornamental fish that require intensive care, particularly in maintaining a regular feeding schedule to support optimal growth. Maintaining a consistent feeding schedule is often a challenge for keepers, especially those with high mobility. Therefore, this research aims to design and build a prototype of an automated koi fish feeding system based on the Internet of Things (IoT) that can be controlled through the Blynk application on mobile devices. The system uses the ESP8266 microcontroller to regulate the feed dispensing mechanism operated by a servo motor. With this automated system, feeding can be performed consistently at predetermined times, ensuring the health and growth of the koi fish. The prototype is designed using the waterfall method, which includes the stages of system analysis, design, implementation, and testing. The test results show that the system can operate effectively according to the remotely set schedule, with a system success rate of 95% and an average network connection delay of 1 second.
Deteksi dan Klasifikasi Sampah Organik dan Anorganik Menggunakan Algoritma Yolo di Solo Technopark Rafel Fernando; Afu Ichsan Pradana; Sopingi
J-INTECH ( Journal of Information and Technology) Vol 14 No 02 (2026): Journal of Information and Technology
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v14i02.2362

Abstract

The advancement of artificial intelligence (AI) technology, particularly in the area of computer vision, has encouraged the use of automatic object detection methods for various needs, including the classification of organic and inorganic waste. The problem of waste management in the Solo Technopark area which is still carried out manually causes the waste sorting process to not run optimally. This research focuses on developing and evaluating the performance of several YOLO models for detecting and classifying organic and inorganic waste types in real-time. The research dataset contains 6,758 waste images categorized into 10 object classes, obtained from Roboflow. The preprocessing stages include annotation, auto-orientation, and image resizing to 640×640 pixels. The dataset is then divided into 70% training data, 20% validation, and 10% testing. This study used three YOLO models, namely YOLOv11, YOLOv12, and YOLOv26 with epoch variations of 10, 30, 50, and 100. Model evaluation was carried out using precision, recall, mAP50, mAP50-95, and inference time metrics. The results showed that the best model was obtained on YOLOv26 epoch 100 with a precision value of 0.92, recall of 0.847, mAP50 of 0.892, mAP50-95 of 0.741, and inference time of 3.0 ms. These findings indicate that the YOLOv26 model has good capabilities in detecting and classifying organic and inorganic waste accurately and quickly, so it has the potential to be used as a basis for developing a real-time waste detection system.
Co-Authors Aines Nafis Husna Andriani Kusumaningrum Areta Reza Pradana Arif Eko Fitrianto Arif Wicaksono Septyanto Bachtiar Estu Saputro Bambang Soedijono WA Dessy Ambarsari Divangga Revansa Arya Pradhana Dwi Hartanti Eko Pranoto Saputro Ema Utami Farrois Qithfirul Aziz Frisca Tri Arumsari Hafid Affan Wahid Harsanto Harsanto harsanto harsanto Hartanti, Dwi Hasanah, Herliyani Ika Suryani Ila Aulia Rahmah Ilham Tristadika Saputra Indah Nofikasari Joko Endriyanto Kumaratih Sandradewi Lestari, Retna Dewi M. Qurdi Ari Setiawan M. Syafri Lamato Malika Harsanto Maulindar, Joni Moh Muhtarom Muhamad Alwi Kurniawan Muhamad Ilhamsyah Amara Ramadana Muhammad Ridho Assyifa Muhammad Yasir Bintang Nugraha Nanang Setiawan Nurchim Nurchim Nurmalitasari Nurmalitasari Pahlevi, Khumaira Anin Aliya Pamekas, Bondan Wahyu Permatasari, Hanifah Purwanto, Eko Raditya Koesyan Dipo Pramukti Radya Prameswari Putri Rafel Fernando Renata Gilang Saputra Reza Mar Hendra Putra Ricky Ardiansah Rifqi Mizan Aulawi Rina Arum Prastyanti Rudi Susanto Saputra, Abetranda Saputra Defa Sigit Prabawa Sopingi Sri Lestari Sri Sumarlinda Subastian Wibowo Sudarmawan Sudarmawan Supardi Tiur Bunga Gadissa Toto Indriyatmoko Wiji Lestari Wijiyanto