Identifikasi Penyakit Tanaman Padi Menggunakan Pengolahan Citra Berdasarkan Fitur Warna, Bentuk Dan Tekstur Dengan Adaptive Neuro Fuzzy Inference System

Tsaqif, Muhammad (2021) Identifikasi Penyakit Tanaman Padi Menggunakan Pengolahan Citra Berdasarkan Fitur Warna, Bentuk Dan Tekstur Dengan Adaptive Neuro Fuzzy Inference System. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Penyakit tanaman padi merupakan salah satu faktor yang menyebabkan menurunnya produktivitas hasil panen padi. Dalam bercocok tanam tanaman padi, diperlukan identifikasi penyakit tanaman padi untuk selanjutnya dilakukan perawatan tanaman padi agar padi tidak terserang penyakit. Selama ini proses untuk mengidentifikasi penyakit tanaman padi dilakukan secara manual. Sehingga identifikasi penyakit tanaman padi secara otomatis dapat memberikan pengaruh dalam upaya pencegahan dan merawat tanaman padi dari terserang penyakit. Pengolahan citra dapat membantu dan mempermudah petani dalam menyelesaikan permasalahan tersebut. Untuk itu, dalam tugas akhir ini dilakukan identifikasi penyakit tanaman padi menggunakan pengolahan citra. Diawali dengan mengumpulkan data lalu melakukan pra-pengolahan citra dilanjutkan proses ekstraksi fitur berdasarkan fitur warna, bentuk dan tekstur. Selanjutnya proses training pada data hasil ekstraksi fitur dengan Adaptive Neuro Fuzzy Inference System. Uji coba dilakukan pada citra daun penyakit blas, citra daun penyakit bercak coklat, dan citra daun padi sehat. Dari hasil uji coba yang dilakukan didapatkan rata-rata akurasi tertinggi yaitu 90% dengan 8 fitur dan rata-rata runtime training data sekitar 25 detik.
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Rice plant disease is one of the factors that causes decreased productivity of rice yields. In cultivating rice plants, it is necessary to identify rice plant diseases for further treatment of rice plants so that rice is not attacked by diseases. So far, the process to identify rice plant diseases has been done manually. So that the identification of rice plant diseases can automatically have an influence in efforts to prevent and treat rice plants from disease. Image processing can help and facilitate farmers in solving these problems. For this reason, in this final project identification of rice plant diseases using image processing is carried out. It begins with collecting data and then pre-processing image followed by the feature extraction process based on color, shape and texture features. Furthermore, the training process on the data from the feature extraction using the Adaptive Neuro Fuzzy Inference System. The experiment was carried out on leaf image of blast disease, leaf image of brown spot disease, and image of healthy rice leaf. From the test results, the highest average accuracy is 90% with 8 features and the average runtime training data is about 25 seconds.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Rice plant disease, Image processing, Adaptive Neuro Fuzzy Inference System, Penyakit tanaman padi, Pengolahan citra
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User:	Muhammad Tsaqif
Date Deposited:	31 Aug 2021 08:05
Last Modified:	31 Aug 2021 08:05
URI:	http://repository.its.ac.id/id/eprint/90934

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