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All Journal Teknika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Informatika Kaputama (JIK) Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) JINAV: Journal of Information and Visualization Rambideun : Jurnal Pengabdian Kepada Masyarakat International Journal of Engineering, Science and Information Technology Jurnal Tika jeti Brilliance: Research of Artificial Intelligence Aptekmas : Jurnal Pengabdian Kepada Masyarakat Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Teknologi Terapan and Sains 4.0 Jurnal Pendidikan Sains Indonesia (Indonesian Journal of Science Education) MEUSEURAYA : JURNAL PENGABDIAN MASYARAKAT Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Rini Meiyanti
Universitas Malikussaleh
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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

 1 
Determining Eligibility for Smart Indonesia Program (PIP) Recipients Using the Backpropagation Method Rizkya, Ghinni; Nurdin, Nurdin; Meiyanti, Rini
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9733

Abstract

The government provides financial assistance, educational opportunities, and expands access for students from poor or vulnerable families through the Smart Indonesia Program (PIP). At Madrasah Ibtidaiyah Negeri 20 Bireuen, the selection process for underprivileged students is still carried out manually by homeroom teachers by collecting data on students and their parents. This study aims to design, implement, and evaluate a classification method using the Backpropagation Neural Network to determine the eligibility of PIP scholarship recipients. The dataset consists of 309 entries, comprising 217 training data and 92 testing data, collected from MIN 20 Bireuen students between 2021 and 2023. The attributes used include father's occupation, mother's occupation, father's income, mother's income, number of dependents, number of vehicles, home ownership status, and card ownership status. Prior to training, the data were normalized using Min-Max scaling. The model was built with one hidden layer using a hard-limit activation function and a learning rate of 0.01. The classification results are categorized as "Eligible" and "Not Eligible". The model achieved an accuracy of 98%, precision of 100%, recall of 95%, and F1-score of 97%.
Method Design of an IoT-Based Automatic Pest Repellent System Prototype for Agriculture Kamaruzzaman, Hilda Zulfira; Ula, Munirul; Meiyanti, Rini
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10632

Abstract

Indonesia, as an agricultural country, still faces serious challenges in the farming sector, particularly pest attacks from birds and insects that significantly reduce rice productivity and may lead to crop failure. The use of traditional methods and chemical pesticides is considered ineffective and has negative impacts on health and the environment. This study aims to design a prototype of an automated pest repellent system for agriculture based on the Internet of Things (IoT) that is environmentally friendly, energy-efficient, and easy to operate by local farmers. The research method employed a prototyping approach, which includes problem identification, hardware and software design, testing, and system evaluation. The device consists of a NodeMCU ESP32 microcontroller, a PIR sensor to detect pest movement, relay, ultrasonic speaker, electric net, and solar panel as the main power source. Testing on a miniature rice field model showed that the system could detect pest movement at a distance of approximately 5 meters and automatically activate the ultrasonic speaker with a range of 50–100 meters to repel birds, and the electric net to catch insects at night. Energy consumption is primarily supplied by the solar panel, and a fully charged battery can power the system for about 3 hours without sunlight. The detection success rate reached more than 85% with consistent actuator response. This system has proven to reduce pesticide dependency, is environmentally friendly, and has the potential to increase rice farming efficiency.
Co-Authors Agam Muarif Aidilof, Hafizh Al Kautsar Andri Alfitra Angga Pratama Anggara, Aji Ar Razi Arief Rahman Asrianda Asrianda Azmi, Win Bagaswara, Faris Bustami Bustami Chaliza Nur, Wan Amalia Cut Agusniar Cut Lika Mestika Sandy Cut Lika Mestika Sandy Dahlan Abdullah Eva Darnila Fasdarsyah Fasdarsyah Fatayati, Nufus Fitri*, Zahratul Fuadi, Wahyu Hafidh Rafif, Teuku Muhammad Hamsi, Widia Harahap, Ilham Taruna Harahap, Lina Mardiana Hasan Dalimunthe, Amir Kamaruzzaman, Hilda Zulfira Kautsar, Al Khairul Anshar Lidya Rosnita Lina Mardiana Harahap Mamat, Rizalman Bin Maryana Maryana, Maryana Muhammad Muhammad Faisal Muhammad Ikhwani Muhammad Muaz Munauwar Muhammad Muhammad Mulyawan, Rizka Munirul Ula Muthalib, Muchlis Abd Mutia Zahara Na'syakban, Irvan Nunsina, Nunsina Nurdin Nurdin Rahma Fitria Rahma Fitria, Rahma Ramadhani, Putri Yesi Ramazani, Ayu Rara Audia Utami Rizkya, Ghinni Ruzanna, Arina Safriana Safriana Safwandi Safwandi Sandy, Cut Lika Mestika Sujacka Retno Syibral Malasyi, Syibral Wahyu Fuadi Yesy Afrillia Zainuddin Ginting Zalfie Ardian Zara Yunizar