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Destriana, Rachmat
Universitas Muhammadiyah Tangerang
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences Other

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Journal : Building of Informatics, Technology and Science

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Implementasi Metode Linear Discriminant Analysis (LDA) Pada Klasifikasi Tingkat Kematangan Buah Nanas Rachmat Destriana; Desi Nurnaningsih; Dedy Alamsyah; Alfry Aristo Jansen Sinlae
Building of Informatics, Technology and Science (BITS) Vol 3 No 1 (2021): Juni 2021
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (588.903 KB) | DOI: 10.47065/bits.v3i1.1007

Abstract

Pineapple is a fruit commodity that is Indonesia's flagship. This is because pineapple is a fruit that has the highest export volume in Indonesia. To obtain pineapples with perfect ripeness, generally manually selected, this becomes inefficient if large numbers of pineapples are selected. So, in this study, an image processing system will be developed that can classify pineapple ripeness based on its image. In this study, the color feature extraction used is feature extraction based on hue and saturation values. Color feature extraction with hue and saturation is used to obtain various information from the colors in the image so as to facilitate the identification process. Furthermore, Linear Discriminator Analysis will obtain optimal projections to be able to enter spaces with smaller dimensions by performing pattern recognition that can be separated so that they can be grouped based on boundary lines obtained from linear equations. Based on the results of the accuracy test, the accuracy rate reaches 83%, it is in the good category
Co-Authors Aditya Prayoga Suyitno Aditya Tegar Siswanto Alexander, Allan D Alfry Aristo Jansen Sinlae Algadri, Wulandari Angga Aditya Permana Asep Suhendar Atmojo, Wahyu Tisno Bintang Eka Suryana Dedy Alamsyah Denis Chandra Prabowo DESI NURNANINGSIH Desi nurnaningsih Desi Nurnaningsih Desy Nurnaningsih Dirgahayu Erri Djamaludin Syahlan Mubaroq3 Dyas Yudi Priyanggodo Figo Rachel Hengki Rusdianto Herdiansah, Arief Hidayatullah, M. Fajri Indra Nanda Jordy Lasmana Putra Jully Triansyah Liesnaningsih Liesnaningsih Liesnaningsih Liesnaningsih Mayatopani, Hendra Nora Fitriawati Nurdiana Handayani Nurhasan Nugroho Paweloi, Fatahillah Prastyawan, Bayu Enggar Reynaldy, Deva Alfian RIFQI RIADHI Rina Pratiwi Pudja I. A Rini Nuraini Rochmat Taufiq Rohmat Taufiq Rusdianto, Hengki Sofian Sidiq Syepry Maulana Husain Tamam, Gusti Syihabuddin Taufiq, Rochmat Tia Ernawati Umar Darmawan Yani Sugiyani Yanuardi Yanuardi Yeni Daniarti