Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi)
Vol 3 No 1 (2019): JANUARY-JUNE 2019

Mengidentifikasi Tanaman Beracun pada Pola Daun dengan Jaringan Syaraf Tiruan Learning Vector Quantification

Muhammad Jurnalies Habibie (Universitas Trilogi)



Article Info

Publish Date
30 Jun 2019

Abstract

Technology nowadays is starting to go very fast, so that all people can use it. Toxic plants are very dangerous if consumed. Therefore to avoid undesirable events, an introduction to the community is needed to find out which plants are poisonous. Plants have many different types to recognize poisonous plants can be seen from the recognition of leaf patterns in these plants. For this reason, in order to determine the use of Learning Vector Quantification artificial neural networks. In this study, the use of input photos obtained from the camera. Photos will be processed later to extract the characteristics. Next, the process of pattern recognition can get the features in the photo. So that later it gets its characteristics. then the classification process uses the Learning Vector Quantification artificial neural network method. This research was conducted to be able to distinguish poisonous plants from those that are not. Which later the data is collected for grouping in accordance with the same data, so that information can be set about the plant.

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Journal Info

Abbrev

jtik

Publisher

Subject

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

Description

Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi), e-ISSN: 2580-1643 is a free and open-access journal published by the Research Division, KITA Institute, Indonesia. JTIK Journal provides media to publish scientific articles from scholars and experts around the world related to Hardware ...