eprintid: 54431
rev_number: 10
eprint_status: archive
userid: 12460
dir: disk0/00/05/44/31
datestamp: 2022-10-24 04:41:53
lastmod: 2022-10-24 04:41:53
status_changed: 2022-10-24 04:41:53
type: thesis
metadata_visibility: show
contact_email: muh.khabib@uin-suka.ac.id
creators_name: Friesca Ayazya Nur Faidza, NIM.: 18106020042
title: DIFERENSIASI NILAI RGB CITRA KUAH TERKONTAMINASI MINYAK BABI DAN MINYAK AYAM MENGGUNAKAN HIGH POWER UV-LED FLUORESCENCE IMAGING SYSTEM TERKOMBINASI MACHINE LEARNING BERALGORITMA K-NEAREST NEIGHBOR
ispublished: pub
subjects: F
divisions: jur_fis
full_text_status: restricted
keywords: Diferensiasi, High Power UV-LED Fluorescence Imaging System , Minyak Babi, Minyak Ayam, Nilai RGB
note: Pembimbing: Frida Agung Rakhmadi, S.Si., M.Sc
abstract: In Indonesia, it’s been discovered people made the mistake of mixed lard in the food, one of the food is a broth. Lard-contaminated broth was very difficult to be differentiated from other halal broth. This research aimd to detect and differentiate RGB values in the image of lard and chicken oil-contaminated broth using machine learning. This research was conducted in three stages, that were samples making, data collection, and data processing. In the samples making, it obtained 10 samples of lard-contaminated broth and 10 samples of chicken oil-contaminated broth. In addition, data collection was carried out by detecting lard and chicken oil- contaminated broth using high power UV-LED fluorescence imaging system, so that 100 data were obtained from broth RGB’s values of lard and 100 broth RGB’s values of chicken oil. Data processing was done using RapidMiner software with the K-NN algorithm. The results showed that lard and chicken oil contaminated broth was succesfuly detected using a high power UV-LED fluorescence imaging system and differentiated using machine learning with the K-NN algorithm with accuracy, precision and recall values of 100 %, also an AUC value of 1,0.
date: 2022-08-15
date_type: published
pages: 105
institution: UIN SUNAN KALIJAGA YOGYAKARTA
department: FAKULTAS SAINS DAN TEKNOLOGI
thesis_type: skripsi
thesis_name: other
citation:   Friesca Ayazya Nur Faidza, NIM.: 18106020042  (2022) DIFERENSIASI NILAI RGB CITRA KUAH TERKONTAMINASI MINYAK BABI DAN MINYAK AYAM MENGGUNAKAN HIGH POWER UV-LED FLUORESCENCE IMAGING SYSTEM TERKOMBINASI MACHINE LEARNING BERALGORITMA K-NEAREST NEIGHBOR.  Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.   
document_url: https://digilib.uin-suka.ac.id/id/eprint/54431/1/18106020042_BAB-I_IV-atau-V_DAFTAR-PUSTAKA.pdf
document_url: https://digilib.uin-suka.ac.id/id/eprint/54431/2/18106020042_BAB-II_sampai_SEBELUM-BAB-TERAKHIR.pdf