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Egg Incubator Control System: A Review Zakaria, Diky; Hamzah, Muhammad Bilal; Nazhif, Dany Syauqi; Prayudha, Rezka Bunaiya; Wahid, Muhammad Rizalul; Ramelan, Agus; Muttaqin, Muhammad Husni; Nugraha, Adi
Journal of Electrical, Electronic, Information, and Communication Technology Vol 5, No 1 (2023): JOURNAL OF ELECTRICAL, ELECTRONIC, INFORMATION, AND COMMUNICATION TECHNOLOGY
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jeeict.5.1.72718

Abstract

Chicken or duck farming is one of the businesses that has good prospects. Conventional hatching of chicken or duck eggs has its own risks with a hatching success percentage of <81%. The hen or duck also needs time for further breeding because they have to incubate the eggs first. Egg incubators on the market usually use on-off controls to regulate incandescent lights which can cause the temperature to fluctuate. Air humidity settings are also manually set by the user. Researchers have conducted studies related to temperature and humidity settings. This article reviews articles from the Scopus database related to control systems in egg incubator with research questions: controlled parameters, sensors used, control theory, methods, and research results that have been carried out. The result of this article can provide an overview of the research development related to egg incubator control systems.
Dress Code Selection Recommender System Based on Smartphone Adhitya, Venus Lidzikri; Irsan, Muhamad; Fathoni, Muhammad Faris; Zakaria, Diky
Journal of Electrical, Electronic, Information, and Communication Technology Vol 6, No 1 (2024): JOURNAL OF ELECTRICAL, ELECTRONIC, INFORMATION, AND COMMUNICATION TECHNOLOGY
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jeeict.6.1.82934

Abstract

In the era of rapidly developing information technology, the existence of smartphones has become an integral part of everyday life. Appearance and choice of dress code play a crucial role in a person's self-image. Therefore, this research aims to design a smartphone-based dress code selection recommendation system. This system will use clothing usage data, user preferences, and event context to provide relevant dress code recommendations. With this solution, it is hoped that users can easily and efficiently choose the appropriate dress code, increase self-confidence, and create a pleasant dressing experience. This research contributes to the development of smartphone-based applications to support users' lifestyle and personal appearance. This application not only provides dress code inspiration, but also makes it easier for users to make decisions regarding clothing choices. Model testing using Machine Learning with the K-Nearest Neighbor (KNN) algorithm shows satisfactory accuracy, precision and recall, namely 83.67%, 83.82% and 99.34%. This application has the potential to be a useful tool helping users live an informed fashion lifestyle and according to personal preferences, and also minimize the waste of time that would occur when choosing clothes.
Automated Bird Deterrent System: A Review Hernadi, Muhammad Fauzan; Timur, Yusuf Haryo; Manalu, Roy Dongan Putra; Khairunnisa, Nabilah; Zakaria, Diky
Journal of Electrical, Electronic, Information, and Communication Technology Vol 7, No 1 (2025): JOURNAL OF ELECTRICAL, ELECTRONIC, INFORMATION, AND COMMUNICATION TECHNOLOGY
Publisher : Universitas Sebelas Maret (UNS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jeeict.7.1.95184

Abstract

Bird pests pose a significant threat to agriculture, causing extensive crop damage and economic losses. Traditional bird repellent methods, such as scarecrows and loud noises, often lose their effectiveness over time as birds adapt. This paper reviews the development and effectiveness of an automated bird repellent system, integrating Internet of Things (IoT) and Artificial Intelligence (AI) technologies. The study used a systematic literature review (SLR) methodology, analyzing 20 articles published between 2015 and 2024. Key findings show that automated systems, utilizing sensors and AI algorithms such as YOLO, DenseNet, and Mask R-CNN, significantly improve bird detection and repellent accuracy. The DenseNet model, in particular, achieved a detection accuracy of 99.65%. The review highlights the need for further research to optimize sensor placement and assess the long-term impacts of this technology on bird behavior and agricultural ecosystems. This comprehensive review underscores the potential of automated bird repellent systems to improve crop protection and sustainability in agriculture.
Co-Authors Abdullah, Cep Ubad Ade Gafar Abdullah, Ade Gafar Adhi, Himmawan Sapta Adhitya, Venus Lidzikri Adi Nugraha Adi Nugraha Afika, Afika Agung Satria Pamungkas Ahmad Fauzi Alif Chandra Wijaya Alimudinsyah Alrasyid Arasid, Wildan Arditya Baskara Mahbubi Arifin, Riyadhil Haqqy Arlya, Zaky Khairul Fajar Asradinto, Faris Fathan Dany Syauqi Nazhif Dede Irawan Saputra Diana Eka Putri Edgard Altamerano Ferdinand Elysa Nensy Irawan Endah Setyowati Excel Thrive Valerian Haryanto Fahrezi, Fauzan Muhammad Fatimah, Rafharum Fauzi Ahmad Muda Fauziah, Dini Fauzie Salman Galura Muhammad Suranegara Geralda Livia Nugraha Hadi Putri, Dewi Indriati Haffiyan Putra Pratama Hafiziani Eka Putri, Hafiziani Eka Hamzah, Muhammad Bilal Hamzah, Muhammad Bilal Bilal Hanopa Abdul Hidayah Hernadi, Muhammad Fauzan Hidayat, Endang Himmawan Sapta Adhi Ichwan Nul Ichsan Isma Widiaty Jamilah, Dewi Siti Jelita Permatasari Khairunnisa, Nabilah Liptia Venica Maharani, Aisyah Aira Putri Makna A’raaf Kautsar Manalu, Roy Dongan Putra Maria Bestarina Laili Miftah Fauzi Januarta Muchtar Ali Setyo Yudono Muhamad Ajis Muhamad Fajar Imanul Haq Muhamad Irsan Muhammad Bilal Hamzah Muhammad Faris Fathoni Muhammad Husni Muttaqin Muhammad Raihan Ramadhan Muhammad Rizalul Wahid Mumtaz, Auziah Muttaqin, Muhammad Husni Nazhif, Dany Syauqi Nina Herlina Nugraha, Geralda L. Nugraha, Rifki Destrizal Nuur Wachid Abdul Majid Pamungkas, Agung Satria Prayudha, Rezka Bunaiya Ramelan, Agus Reyhan Praditya Bagaskara Rezka Bunaiya Prayudha Rifki Destrizal Nugraha Saputra, Dede Irawan Sembiring, Vladio Sada Arihta Sri Subekti Steven, Michael Sunardi, Egi Tasya Syabila Taufik Ridwan Taufik Ridwan, Taufik Timur, Yusuf Haryo Tri Seda Mulya Yohanes Adi Nugroho Yohanes Adi Nugroho