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Moh. Diqi
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ASTEEC Headquarters: Jl. Tajem, Kregan, Maguwoharjo, Depok, Sleman Yogyakarta, 55281, Indonesia
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INDONESIA
International Journal of Informatics Engineering and Computing
Published by ASTEEC Publisher
ISSN : -     EISSN : 30909112     DOI : https://doi.org/10.70687/ijimatic
Core Subject : Science,
Computer Science & IT
International Journal of Informatics Engineering and Computing (IJIMATIC) is an international, peer-reviewed, open-access journal that publishes original theoretical and empirical work on the science of informatics and its application in multiple fields. Our concept of informatics encompasses technologies of information and communication, as well as the social, linguistic, and cultural changes that initiate, accompany, and complicate their development. IJIMATIC aims to be an international platform to exchange novel research results in simulation-based science across all computer science disciplines.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 22 Documents
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Design of Automatic Metal and Non-metal Waste Sorting Based on Internet of Things (IoT) Diqi, Mohammad; Hasta Mulyani, Sri; Wijaya S, R Nurhadi; Junia Sipit, Marselina
International Journal of Informatics Engineering and Computing Vol. 2 No. 2 (2025): International Journal of Informatics Engineering and Computing [Preview]
Publisher : ASTEEC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70687/31bqbr09

Abstract

Ineffective waste management, especially in the process of sorting between metal and non-metal waste, is still a serious environmental problem. This research aims to design and build a prototype of an Internet of Things (IoT)-based automatic waste sorting device that is able to identify and separate types of waste independently. The system uses an ESP32 microcontroller integrated with ultrasonic sensors, inductive proximity sensors, and MQ135 gas sensors, as well as the Blynk application as an IoT-based monitoring interface. The method used is Research and Development (RnD) with six stages: literature study, system design, tool making, testing, evaluation, and conclusion. The test results show that the system is able to classify metal and non-metal waste with an accuracy rate of 90%, precision reaches 85.71% for metals, and 95.45% for non-metals. The integration of IoT technology in waste sorting tools is proven to increase the efficiency of waste processing from the source and provide innovative solutions in smarter and more sustainable environmental management.
Automatic Detection of Cabbage Pest Attacks Based on Leaf Images with Machine Learning Approach Ni Wayan Surya Wardhani; Prayudi Lestantyo; Atiek Iriany; Nur Silviyah Rahmi
International Journal of Informatics Engineering and Computing Vol. 2 No. 2 (2025): International Journal of Informatics Engineering and Computing [Preview]
Publisher : ASTEEC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70687/3szcd282

Abstract

Farmers in cabbage farming face many problems, one of which is pest attack. Plutella xylostella L. is a major pest on cabbage (known as cabbage leaf caterpillar) which can cause a decrease in production of up to 100 percent. Decision Support System (DSS) was developed to classify the attack rate of Plutella to reduce the negative effects of using various types of high doses of pesticides and short spraying intervals but causing residual effects and killing natural enemies. DSS has a role in helping farmers to make decisions regarding the time of pesticide treatment needed to minimize negative effects and increase productivity. In this study, DSS was developed to detect damage to cabbage (Brassica oleracea L) crops so that farmers can determine pesticide doses and spraying intervals based on a website. The results of the system is presented in the form of images and the percentage of damage to cabbage plants. Therefore, the CART method can be used to analyze the level of damage to plants that are attacked by pests.

Page 3 of 3 | Total Record : 22

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