Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal International Journal of Social Science, Educational, Economics, Agriculture Research, and Technology (IJSET)
Muhammad Hibrian Wiwi
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
MILKFISH CULTIVATION SUPPORTS AUTOMATION OF FISH FEEDING IN THE PEN CULTURE SYSTEM Hamar, Bahtiar; Muhammad Hibrian Wiwi; Muhammad Fazrun
International Journal of Social Science, Educational, Economics, Agriculture Research and Technology (IJSET) Vol. 5 No. 5 (2026): APRIL
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.20093249

Abstract

This study presents the design and implementation of an Internet of Things (IoT)-based automated fish feeding system for milkfish cultivation using the pen culture method. The research employed a prototype methodology, integrating microcontroller-based hardware with sensors, servo motors, and RTC modules to enable precise, scheduled, and remotely monitored feeding. Initial stages included problem identification, literature review, and system requirement analysis, followed by system design connecting multiple microcontroller devices for automatic data processing and feed distribution. The developed prototype was tested both indoors and outdoors, with monitoring via laptops and mobile devices through the Blynk application. Results demonstrate that the system efficiently automates feed distribution, reduces feed waste, minimizes manual labor, and facilitates real-time monitoring, thus enhancing operational efficiency and productivity in milkfish farming. The implementation of this IoT-based solution offers a cost-effective, sustainable, and practical approach to optimize aquaculture management, improve fish growth, and support data-driven decision-making for farmers. This study contributes to advancing smart aquaculture technologies in Indonesia.
Co-Authors Bahtiar Hamar Muhammad Fazrun