Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Vol 13 No 3 (2023): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)

Deep Learning Untuk Klasifikasi Kematangan Buah Mangrove Berdasarkan Warna

Harun Mukhtar (Universitas Muhammadiyah Riau)
Febrian Alfanico (Universitas Muhammadiyah Riau)
Hasanatul Fu’adah Amran (Universitas Muhammadiyah Riau)
Fitri Handayani (Universitas Muhammadiyah Riau)
Reny Medikawati Taufiq (Universitas Muhammadiyah Riau)



Article Info

Publish Date
24 Dec 2023

Abstract

Plants that live between land and sea, such as mangroves, are influenced by the tides and tides. Indonesia has the largest mangrove forest in the world and a variety of biodiversity and structure. People currently detect mangrove maturity by looking directly at the fruit. This study proposes to classify the maturity of mangrove fruit using artificial intelligence techniques, making it easier for farmers to determine the ripeness of the fruit. This proposal uses data from 200 images for mangroves taken directly from Lukit Village, Merbau District, Meranti Islands Regency. This research improves the Convolutional Neural Network (CNN) method to classify mangrove fruit maturity. The results obtained from this research were by classifying ripe and unripe fruit. Based on this research, accuracy reaches a maximum of 96%.

Copyrights © 2023






Journal Info

Abbrev

JIK

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management

Description

Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) is expected to be a media of scientific study of research result, a thought and a study criticial analysis to a System engineering research, Informatics Engineering, Information Technology, Computer Engineering, Informatics Management, and ...