Tren Teknologi dan Mikrokontroler pada Sistem Pakan Ikan Otomatis Berbasis IoT: Tinjauan Sistematis 2022–2026

Faiz Abdurrahman Mustofa (Universitas Sains dan Teknologi Komputer, Jawa Tengah)
Dani Sasmoko (Universitas Sains dan Teknologi Komputer, Jawa Tengah)
Sumaryanto Sumaryanto (Universitas Sains dan Teknologi Komputer, Jawa Tengah)

TIN: TERAPAN INFORMATIKA NUSANTARA
Vol 7 No 5 (2026): October 2026

This study aims to analyze technology trends and microcontrollers in automatic fish feeding systems based on the Internet of Things (IoT) through a Systematic Literature Review (SLR) of publications from 2022–2026. The method used is SLR with the PRISMA 2020 protocol, bibliometric analysis assisted by VOSviewer, and content analysis. Data were taken from the ScienceDirect database, with an initial search yielding 200 articles for Research Question 1 (RQ1) and 50 articles for RQ2. After identification, screening, and eligibility assessment, 32 articles for RQ1 and 17 articles for RQ2 were included for further analysis. The results show a shift from simple timer-based systems toward intelligent architectures integrated with AI and machine learning, with IoT+AI dominating at 35%. The Arduino platform dominates at 60%, followed by ESP32/NodeMCU, which is increasing due to wireless connectivity. The most critical sensors are temperature (30%), pH (25%), and dissolved oxygen (25%), while feeder actuators dominate at 30%. Publications peaked in 2025 with 26 articles. For RQ2, Arduino family microcontrollers (Uno, Mega, Nano) are the most dominant, covering two-thirds of articles, but there is a gradual shift toward ESP32 and ESP8266. An important finding reveals a reporting gap where 70% of articles do not explicitly list hardware specifications, hindering research replication and technology adoption. This study provides a current technology trend map and evidence-based recommendations for researchers and farmers in selecting the most mature technology for sustainable automatic feeding systems in the aquaculture sector.