Sistem Klasifikasi Penyakit Tanaman Padi Menggunakan Machine Learning pada Platform Android

Nugroho, Ilham Widhi and , Dedi Gunawan, S.T., M.Sc., Ph.D (2024) Sistem Klasifikasi Penyakit Tanaman Padi Menggunakan Machine Learning pada Platform Android. Skripsi thesis, Universitas Muhammadiyah Surakarta.

	PDF (Naskah Publikasi) Naskah Publikasi.pdf Download (602kB)
	PDF (Surat Pernyataan Publikasi) Surat_Pernyataan_Publikasi_L200200265.pdf Restricted to Repository staff only Download (208kB)

Abstract

Rice is a staple food crop for Indonesian people, but rice production in Indonesia continues to decline from year to year. The decline in production was caused by various factors, one of which was unstable weather which caused an increase in the potential for rice plant diseases. With the current development of information technology, there are many ways to detect diseases in rice plants early, one of which is using machine learning technology implemented on the Android platform. The algorithm used is CNN (Convolutional Neural Network) and succeeded in getting an accuracy rate of 83.49%. In this research, the SDLC model used is waterfall. The black box test went well as evidenced by all the menus, displays and buttons in the application running according to their function. The application designed can help farmers identify rice plant diseases based on the SUS (System Usability Scale) survey which received an average score of 77.5 from 30 respondents, which means this system is suitable for use and can be accepted by users.

Item Type:	Thesis (Skripsi)
Uncontrolled Keywords:	android, black box, machine learning, penyakit tanaman padi.
Subjects:	T Technology > TZ Technical Information T Technology > TZ Technical Information > TA02 Software. Aplication > Pemograman
Divisions:	Fakultas Ilmu Komunikasi dan Informatika > Teknik Informatika
Depositing User:	ILHAM WIDHI NUGROHO
Date Deposited:	06 Aug 2024 01:06
Last Modified:	06 Aug 2024 01:06
URI:	http://eprints.ums.ac.id/id/eprint/125759

Actions (login required)

View Item