Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
I Made Budi Surya Darma
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Penerapan Sentimen Analisis Acara Televisi Pada Twitter Menggunakan Support Vector Machine dan Algoritma Genetika sebagai Metode Seleksi Fitur I Made Budi Surya Darma; Rizal Setya Perdana; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 3 (2018): Maret 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1037.703 KB)

Abstract

Rating is one approach method that can be used to find out about audience satisfaction of a TV show. In Indonesia, rating was calculated by using AGB Nielsen services. However, rating that AGB Nielsen produced was based on the people watching bahavior in 10 major cities in Indonesia. Therefore, rating in Indonesia requires another method to get the watching behavior of the whole people in Indonesia. Twitter, can be used to get Indonesia people watching behavior. Through the published tweets, it can be applied the process of extracting information by using classification techniques to get the opinions. One of the classification techniques that can be applied to text categorization is the Support Vector Machine (SVM) it`s suitable for multiple dimension data. By optimizing the features that will be used, it can provide optimal results with less features used. One of the feature selection methods that can be applied to SVM is the genetic algorithm (GA). System calculates the rating, based on positive and negative sentiments about the TV show and divided by the population of the tweet used. The rating comparison test that produced by AGB Nielsen and system shows an average error value of 0.562. In testing the accuracy before and after the feature selection method is applied, showed results with average error value 0.62%.
Co-Authors Indriati Indriati Rizal Setya Perdana