IMPLEMENTASI TENSORFLOW LITE PADA TEACHABLE MACHINE UNTUK IDENTIKASI TANAMAN AGLONEMA BERBASIS ANDROID

BAGUS BAIHAQI, MUHAMMAD (2022) IMPLEMENTASI TENSORFLOW LITE PADA TEACHABLE MACHINE UNTUK IDENTIKASI TANAMAN AGLONEMA BERBASIS ANDROID. Skripsi (S1) thesis, Universitas Muhammadiyah Ponorogo.

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Abstract

Implementasi Tensor Flow Lite pada Teachable Machine untuk Identifikasi Tanaman Agolema Berbasis Android Muhammad Bagus Baihaqi¹ ,Yovi Litanianda² , Andy Triyanto³ Fakultas Teknik , Teknik Informatika, Universitas Muhammadiyah Ponorogo E- mail Korespondensi : bagusbaihaqi8@gmail.com ABSTRACT Aglonema or sri fortune has various types with various shapes, patterns and colors. Various types and more and more due to the many crossing processes carried out by owners and lovers of aglonema plants. For ordinary people who do not have insight into aglonema, it will be difficult to distinguish aglonema plants because the shapes, patterns and colors have similarities. It takes a Teachable Machine system with a complex but more sophisticated method that is able to recognize plants with a higher level of accuracy. The machine learning process is carried out on a computer to identify image data into classification results in the form of predictions. Tensorflow lite is a machine learning library specially designed for object recognition. Therefore, researchers are encouraged to create an Android-based mobile application that is able to recognize aglonema plants quickly, easily and accurately. Keywords: Aglonema, Android, TensorFlow, Identifica

Item Type:	Thesis (Skripsi (S1))
Uncontrolled Keywords:	Kata kunci : Aglonema, Android, TensorFlow, Identifika
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Engineering > Department of Informatic Engineering
Depositing User:	ft . userft
Date Deposited:	22 Mar 2022 01:16
Last Modified:	22 Mar 2022 01:16
URI:	http://eprints.umpo.ac.id/id/eprint/8898

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