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All Journal Insect (Informatics and Security) : Jurnal Teknik Informatika Jurnal Eksplora Informatika Jurnal Teknik Informatika (JUTIF) Journal of Computer and Information System (J-CIS) Bakti Sekawan : Jurnal Pengabdian Masyarakat Nobel Community Services Journal Journal of Computer Science Contributions (Jucosco)
Insani, Chairi Nur
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Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Health Professions Social Sciences Other

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Penerapan Teknologi IoT Pada Tanaman Hidroponik Untuk Monitoring Pertumbuhan Tanaman di Desa Puccadi Heri, Adi; Insani, Chairi Nur; Irianti, Arnita; Rasyid, Nurdina
Journal Of Computer Science Contributions (JUCOSCO) Vol. 4 No. 1 (2024): Januari 2024
Publisher : Lembaga Penelitian, Pengabdian kepada Masyarakat dan Publikasi Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/f0wg5665

Abstract

Technological development is needed for a better development system. Technology can provide basic changes for society, especially in the context of improving the quality of life in society. In general, the hydroponic method is carried out using water as a medium, where the water conditions that need to be considered are the supply of water, oxygen, nutrients, pH, and light intensity. UV light replaces sunlight which can help plants need the photosynthesis process which produces food substances such as carbohydrates so that plants grow faster. From the situation analysis, it is known that most of the people in Puccadi Village. Cultivating plants using a hydroponic system on a household scale by utilizing yards or yards has quite a large potential. Based on this background, IoT-based hydroponic training and assistance were carried out for the people of Puccadi Village, Luyo District. This service activity is implemented in the form of training and mentoring with the aim of participants being able to directly practice applying IoT to hydroponic plants for monitoring plants. The conclusion of the IoT-based hydroponic training activities in Puccadi Village, Luyo District, is that the implementation of IoT-based hydroponic training and mentoring went well and was able to provide knowledge related to the application of IoT technology to the Puccadi village community, Luyo District.
Implementasi MobileNetV2 pada Klasifikasi Penyakit Daun Bibit Kakao Berbasis Pengolahan Citra Digital Sintia, Sintia; Arifin, Nurhikma; Insani, Chairi Nur
Insect (Informatics and Security): Jurnal Teknik Informatika Vol. 12 No. 01 (2026): Maret 2026
Publisher : Universitas Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33506/insect.v12i01.5396

Abstract

Kakao (Theobroma cacao L.) merupakan komoditas perkebunan strategis di Indonesia. Namun produktivitasnya masih menghadapi tantangan serius akibat serangan penyakit daun, khususnya pada fase pembibitan. Penyakit Vascular Streak Dieback (VSD) dan Leaf Blight diketahui dapat menurunkan produktivitas tanaman secara signifikan, sementara proses identifikasi penyakit secara manual masih bersifat subjektif dan berpotensi menimbulkan kesalahan klasifikasi. Penelitian ini bertujuan untuk mengklasifikasikan citra daun bibit kakao kedalam tiga kelas, yaitu Sehat, VSD, dan Leag Blight, menggunakan model MobileNetV2 berbasis transfer learning. Dataset yang digunakan merupakan data primer sebanyak 549 citra daun bibit kakao yang diperoleh dari Desa Riso, Kecamatan Tapango, Kabupaten Polewali Mandar, Sulawesi Barat. Tahapan pre-processing meliputi resize, normalisasi, dan augmentasi data, kemudian dataset dibagi dengan rasio 80% data training dan 20% data testing. Model dilatih selama 30 epoch dan evaluasi menggunakan classification report dan confusion matrix. Hasil pelatihan menunjukkan bahwa model MobileNetV2 mencapai akurasi tertinggi sebesar 98,02% dengan nilai loss yang rendah. Evaluasi menunjukkan bahwa kelas VSD berhasil di klasifikasikan secara sempurna, sementara kelas Leaf Blight dan Sehat juga menunjukkan performa yang sangat tinggi dengan tingkat kesalahan klasifikasi yang sangat kecil. Hasil ini membuktikan bahwa MobileNetV2 efektif digunakan untuk klasifikasi citra daun bibit kakao dan berpotensi dikembangkan sebagai sistem pendukung deteksi dini untuk penyakit tanaman kakao berbasis citra digital.
Co-Authors Arifin, Nurhikma Arifin, Nurhikmah Arsyad, Andi Asy'hary J. Asmaul Husna RS Chairy, Amalia Heri, Adi Irianti, Arnita Ismail Jean Mewanti Runa Juprianus Rusman Mala, Faiqotul Milasari Milasari Muhammad Furqan Rasyid Musyrifah Muzaki Muzaki Permata, Reny Amalia Rasyid, Nurdina Sari, Dian Megah Sintia, Sintia Upa, Samrius Utama, Muhammad Surya Alif Yusuf, Andi M