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All Journal Agents: Journal of Artificial Intelligence and Data Science
Andi Muhammad Nurul Ilham
Universitas Muhammadiyah Makassar
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Rancang Bangun Pendeteksi Formalin dan Boraks pada Makanan berbasis Internet of Things (IoT) RIDWANG RIDWANG; Abd gafur; Andi Muhammad Nurul Ilham; Adriani
AGENTS: Journal of Artificial Intelligence and Data Science Vol 3 No 2 (2023): Maret - Agustus
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/jagti.v3i2.69

Abstract

Consumption of unsafe food can lead to foodborne illness, a significant threat to our health. The use of formalin and borax in food can cause degenerative diseases and other health problems. To address this issue, a new study has focused on developing an IoT-based food detection tool for formaldehyde and borax. With IoT integration, this device can provide real-time and portable information via LCD screens and Android smartphones. The advantage of this tool is that it can quickly and accurately detect formaldehyde and borax in food, helping to prevent the consumption of unsafe food. Through formalin testing on meatballs and food samples containing borax, using instant noodle and egg samples and the results obtained from the addition of 1-5 drops of borax, all of which were detected as dangerous. The application of this detection tool is expected to increase the awareness of food producers and the public about the importance of food safety. It can also help control food stocks in markets, thereby reducing the risk of formaldehyde and borax induced in food products. Overall, this IoT-based food detection tool is an essential tool for ensuring the safety and quality of our food supply
Co-Authors Abd Gafur Adriani Ridwang Ridwang