DISKRIMINASI POLA AROMA KULIT KUDA DAN KULIT BABI MENGGUNAKAN ELECTRONIC NOSE (e-Nose) YANG TER-COUPLED DENGAN MACHINE LEARNING (ML) DENGAN ALGORITMA SUPPORT VECTOR MACHINE (SVM)

Rakha Saputra, NIM.: 16620006 (2020) DISKRIMINASI POLA AROMA KULIT KUDA DAN KULIT BABI MENGGUNAKAN ELECTRONIC NOSE (e-Nose) YANG TER-COUPLED DENGAN MACHINE LEARNING (ML) DENGAN ALGORITMA SUPPORT VECTOR MACHINE (SVM). Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

[img]
Preview
Text (DISKRIMINASI POLA AROMA KULIT KUDA DAN KULIT BABI MENGGUNAKAN ELECTRONIC NOSE (e-Nose) YANG TER-COUPLED DENGAN MACHINE LEARNING (ML) DENGAN ALGORITMA SUPPORT VECTOR MACHINE (SVM))
16620006_BAB-I_IV-atau-V_DAFTAR-PUSTAKA.pdf

Download (7MB) | Preview
[img] Text (DISKRIMINASI POLA AROMA KULIT KUDA DAN KULIT BABI MENGGUNAKAN ELECTRONIC NOSE (e-Nose) YANG TER-COUPLED DENGAN MACHINE LEARNING (ML) DENGAN ALGORITMA SUPPORT VECTOR MACHINE (SVM))
16620006_BAB-II_sampai_SEBELUM-BAB-TERAKHIR.pdf
Restricted to Registered users only

Download (14MB)

Abstract

An electronic nose (e-Nose) has successfully detected the aroma pattern of horse hide and pigskin. In addition, e-Nose coupled with machine learning (ML) has successfully discriminated the aroma patterns of horse hide and pigskin. The results of e-Nose detection data were pre-processed with the methods of reducing the baseline value and feature extraction of the maximum value. Discrimination of the aroma patterns of horse hides and pigskin using machine learning (ML) with support vector machine (SVM) algorithm. The experimental dataset were divided into three subsets, namely training data (to establish a classification model), testing data, and new testing data. Furthermore, hyperparameter optimization and K-fold cross-validation variants were implemented during the model training procedure to select the best SVM discriminating model and to avoid over-fitting issues. The best predictive discrimination performance of the SVM model obtained 100% discrimination for testing data and 100% discrimination for new testing data.

Item Type: Thesis (Skripsi)
Additional Information: Pembimbing : 1. Frida Agung Rakhmadi, S.Si., M.Sc; 2. Shidiq Nur Hidayat, S.Si., M.Si
Uncontrolled Keywords: aroma patterns of horse hide and pigskin, electronic nose, machine learning, support vector machine.
Subjects: Fisika
Divisions: Fakultas Sains dan Teknologi > Fisika (S1)
Depositing User: H. Latief, SIP
Date Deposited: 08 Sep 2021 12:00
Last Modified: 08 Sep 2021 12:00
URI: http://digilib.uin-suka.ac.id/id/eprint/44042

Share this knowledge with your friends :

Actions (login required)

View Item View Item
Chat Kak Imum