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All Journal Jurnal Pengembangan Teknologi Informasi dan Komunikasi (JUPTIK)
Meilani, Cindy
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Computer Science & IT Control & Systems Engineering Engineering Library & Information Science

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Klasifikasi Jenis Tanaman Obat Herbal Berdasarkan Ciri Daun Menggunakan K-NN Meilani, Cindy; Ambarwati, Rizki; Saputri, Devita; Fujianto
Jurnal Pengembangan Teknologi Informasi dan Komunikasi (JUPTIK) Vol. 3 No. 2 (2025): JURNAL PENGEMBANGAN TEKNOLOGI INFORMASI DAN KOMUNIAKSI (JUPTIK)
Publisher : Prodi Teknologi Informasi Universitas Muhammadiyah Muara Bungo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52060/juptik.v3i2.3028

Abstract

Indonesia has a variety of abundant plants, including medicinal plants. However, many people still do not know about the types of herbal medicinal plants that exist. The process of identifying types of herbal medicinal plants generally relies on the knowledge of botanists with manual methods, which rely on morphological characteristics and vision. With advances in technology, leaf image recognition can be done using computer vision methods. This study aims to identify types of herbal medicinal plants based on leaf image patterns using the K-Nearest Neighbors (K-NN) method. The identification process begins with taking leaf images, then feature extraction is carried out to distinguish plant types. The results of the study show that the K-NN method can provide a fairly good level of accuracy in identifying types of medicinal plants. This system is expected to help the public recognize medicinal plants more effectively and expand knowledge about the benefits of herbal plants. Thus, the application of leaf image recognition technology can be a solution in conserving knowledge about medicinal plants in Indonesia.
Co-Authors Ambarwati, Rizki Fujianto Saputri, Devita