Article Per Year (5 Year)
p-Index From 2021 - 2026
1.376
P-Index
This Author published in this journals
All Journal snimed Telematika : Jurnal Informatika dan Teknologi Informasi Techno LPPM Seminar Nasional Informatika (SEMNASIF) Conference SENATIK STT Adisutjipto Yogyakarta Compiler IKRA-ITH ABDIMAS Journal of Information Systems and Informatics Science in Information Technology Letters
Nur Heri Cahyana
Universitas Pembangunan Nasional Veteran Yogyakarta
Aerospace Engineering Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering

Published : 11 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 11 Documents
Search

 1   2 
Implementation of Mel-Frequency Cepstral Coefficient as Feature Extraction using K-Nearest Neighbor for Emotion Detection Based on Voice Intonation Nawasta, Revanto Alif; Cahyana, Nur Heri; Heriyanto, Heriyanto
Telematika Vol 20 No 1 (2023): Edisi Februari 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i1.9518

Abstract

Purpose: To determine emotions based on voice intonation by implementing MFCC as a feature extraction method and KNN as an emotion detection method.Design/methodology/approach: In this study, the data used was downloaded from several video podcasts on YouTube. Some of the methods used in this study are pitch shifting for data augmentation, MFCC for feature extraction on audio data, basic statistics for taking the mean, median, min, max, standard deviation for each coefficient, Min max scaler for the normalization process and KNN for the method classification.Findings/result: Because testing is carried out separately for each gender, there are two classification models. In the male model, the highest accuracy was obtained at 88.8% and is included in the good fit model. In the female model, the highest accuracy was obtained at 92.5%, but the model was unable to correctly classify emotions in the new data. This condition is called overfitting. After testing, the cause of this condition was because the pitch shifting augmentation process of one tone in women was unable to solve the problem of the training data size being too small and not containing enough data samples to accurately represent all possible input data values.Originality/value/state of the art: The research data used in this study has never been used in previous studies because the research data is obtained by downloading from Youtube and then processed until the data is ready to be used for research.
Co-Authors Adhika Noorindra, Adhika Agung Prabowo Agus Sasmito Aribowo Agusdin, Riza Prapascatama Ahmad Taufiq Akbar Arianti, Berliana Andra Awang Hendrianto Pratomo Azizah, Nisa’ul Bambang Yuwono Dreżewski, Rafał Hafsah Hafsah Herdiansyah, Fachrizal Heriyanto Heriyanto Herlina Jayadianti Husaini, Rochmat Indah, Sika Nur Kusumo, Yudhy Widya Nawasta, Revanto Alif Oliver Samuel Simanjuntak Prapcoyo, Hari Rifki Indra Perwira Rustamadji, Heru Saifullah, Shoffan Tahalea, Sylvert Prian Tri Mardiana, Tri Wilis Kaswidjanti Wisnalmawati Wisnalmawati Yenni Sri Utami, Yenni Sri Yuli Fauziah