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All Journal (JELIKU) Jurnal Elektronik Ilmu Komputer Udayana
Khatami, Maula
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Computer Science & IT

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Voice Classification Based on Gender Using Backpropagation and K-Means Clustering Algorithm Khatami, Maula; Gede Suhartana, I Ketut
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 2020
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2020.v08.i03.p08

Abstract

Sound is the identity of all living creature, including Humans. With voice we can do socialize, call people, ask questions, communicate, and even be able to help us to recognize the sex of the person who makes the sound. Nowadays, knowing gender through sound cannot only be done by humans but through a computer. Voice classification using a computer shows increasingly sophisticated technology. Of course this technological advance can also help in terms of security, where the voice can be a key or password in a certain confidentiality. In this study the focus of sound recordings is classified according to the sex of men and women by using the Backpropagation algorithm for training data, then Mel Frequency Cepstral Coefficients (MFCC) will process sound data and get features, and the K-Means Clustering algorithm will classify sound data already processed. The dataset used here is in the form of male and female voice recordings obtained from YouTube videos that have been separated by video sections. There are each 10 male and female voice files for training. As for testing, there are several male and female voice files that are placed in separate folders.
Sebuah PENCARIAN FILE JURNAL DENGAN QUERY KATA PADA LIST KUMPULAN DOKUMEN JURNAL MENGGUNAKAN METODE VECTOR SPACE MODEL Khatami, Maula
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 9 No 1 (2020): JELIKU Volume 9 No 1, Agustus 2020
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2020.v09.i01.p10

Abstract

Journals are articles about research that are very useful among academics and students alike. Every time we learn a new knowledge, we certainly need a guide that is verified and also credible. Students and academics were greatly helped by this journal. With journals help students and academics get references from previous research and get more insights so that they are able to make a related research and can even be improved from previous research. However, there are still many students and academics who find it difficult to find the right journal for their needs. So here the authors make a research system of information retrieval about journal searches by querying words using the vector space model method. In the suffix tree clustering method and the Vector Space Model, each document and keyword that has been carried out by the Text Mining process is then given the weight of each word contained in each existing document with the Term Frequency - Inverse Document Frequency (TF-IDF) weighting algorithm.
Co-Authors I Ketut Gede Suhartana