Hanin Latif Fuadi
Institut Teknologi Telkom Purwokerto

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Klasifikasi Kematangan Tanaman Hidroponik Pakcoy Menggunakan Metode SVM Lukman Priyambodo; Hanin Latif Fuadi; Naura Nazhifah; Ibrohim Huzaimi; Angga Bagus Prawira; Tasya Enjelika Saputri; Mas Aly Afandi; Eka Setia Nugraha; Agung Wicaksono; Petrus Kerowe Goran
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 1 (2022): Februari 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (430.551 KB) | DOI: 10.29207/resti.v6i1.3828

Abstract

Pakcoy is a type of vegetable plant belonging to the Brassica family. Pakcoy plants can be cultivated using hydroponic techniques, namely plant cultivation techniques without soil media. The advantage of cultivating Pakcoy plants using hydroponic techniques is that it does not require a large area of ‚Äč‚Äčland, so it is easy to apply in the yard. However, cultivation with hydroponic techniques has drawbacks such as farmers need to make regular observations to determine the harvest readiness of each plant. This causes a lack of effectiveness of farmers in cultivating Pakcoy plants. With the development of Machine Learning technology, a model can classify the maturity of Pakcoy plants based on digital image data. By applying the Support Vector Machine (SVM) Algorithm, the Machine Learning model can learn to classify a digital image of Pakcoy plants with the category "Small" to represent immature Pakcoy plants and "Large" to represent mature Pakcoy plants which results in an accuracy level of above 79%. It can be concluded that Machine Learning can be implemented in Pakcoy cultivation activities to support hydroponic farmers.