Article Per Year (5 Year)
p-Index From 2020 - 2025
1.556
P-Index
This Author published in this journals
All Journal JSI: Jurnal Sistem Informasi (E-Journal) Annual Research Seminar JPSriwijaya Sistemasi: Jurnal Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA The IJICS (International Journal of Informatics and Computer Science) Jurnal Tekno Kompak Jurnal Pengabdian Masyarakat Bumi Raflesia Indonesian Journal of Electrical Engineering and Computer Science
Fathoni -
Information Systems Universitas Sriwijaya Palembang, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Neuroscience Public Health Other

Published : 14 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : JURNAL MEDIA INFORMATIKA BUDIDARMA

 1 
Analisis Sentiment Pelanggan Terhadap Penilaian Produk Pada Toko Online Shop Amreta Menggunakan Metode Naïve Bayes Classification Alisia Silver Stone; Fathoni Fathoni
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 3 (2022): Juli 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i3.4436

Abstract

Sentiment analysis or opinion mining is an analysis that aims to see the sentiment of people or groups regarding certain entities. The sentiments expressed by society can be in positive, negative and neutral form. One media that can be given an opinion by the public is in the e-commerce application,  namely the shopee application, shopee has a comment or assessment feature on the product that has been purchased. Toko which was used as a sample of researchersis an amreta online shop store  , based on the results of the identification of the problem, it was found that the fact was that many comments did not match the stars given so it can be said that the rating cannot represent that the store's performance is good or not. Therefore, to increase the profit of shop work, the amreta still needs to evaluate the store. In conducting an evaluation, the store needs to classify positive, negative or neutral comments. Analysis of customer sentiment towards product assessments in amreta online shop stores using the naive bayes classification method. The use of test data in this study was obtained from the sentiment of amreta online shop consumers as much as 2014 data,then the data was processed through  the data cleaning process  resulting in net data of 1899 data. Furthermore, the data preprocessing process is divided into 3 stages, namely Tokenize Data, Transform case and Stopword removal. After that, the analysis of data for the automatic labeling stage using Text Vectorize from the process obtained data division into 3 data groups of 71% or 1343 positive data, 3% or 52 negative data and 26% or 504 neutral data.  furthermore, it is processed using rapidminer tools while for operators in the form of algorithms using the Sentiment Naïve Bayes Classification model  through automatic calculations.  The results of the study can be concluded that the test data obtained have an accuracy level of 97.16% using the Naive Bayes Classification model.
Sentiment Analysis Pada Masyarakat Terhadap LRT Kota Palembang Menggunakan Metode Improved K-Nearest Neighbor Siti Nur Arafah; Fathoni Fathoni
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 3 (2022): Juli 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i3.4434

Abstract

The LRT is a sustainable fast transportation system, which was built to overcome the congestion problem in the city of Palembang. In order to attract people's interest to switch to using public transportation compared to private transportation, one of them is by improving the quality of services provided. Sentiment analysis is used to classify positive and negative opinions on users of Palembang City LRT transportation services. In addition to retrieving data through crawling data on tweet data, the researchers also distributed questionnaires. In conducting the classification process of sentiment analysis, this study uses the Improved K-Nearest Neighbor method which is a modification of the K-Nearest Neighbor method. The results of this research are testing and training data on 1617 data records and the highest accuracy of 74.07% on 90% training data and 10% testing data, with 70% precision, 56% recall and 59% f-1 score, while the lowest accuracy with an accuracy of 63.04% on 50% training data and 50% testing data, with 44% precision, 42% recall and 42% f-1 score
Co-Authors Abdiansah, Abdiansah Ahmad Rafid Rizqullah Ahmad Rifai Ali Ibrahim Alisia Silver Stone Allsela Meiriza, Allsela Alzaini, Akbar Apriansyah Putra Apriansyah Putra Ari Wedhasmara Dedy Kurniawan Endang Lestari Ruskan Erwin, Erwin Ken Ditha Tania M Ihsan Jambak Maharani Maharani Mira Afrina Pacu Putra Rahmat Fadli Isnanto Rahmat Izwan Heroza Rezqe, Beriadi Agung Nur Rio Abdi Sucipta Rizka Dhini Kurnia Sanjaya, M. Rudi Siti Nur Arafah Sultan Arba'i Syamsuryadi Syamsuryadi Tika Octri Dieni Yadi Utama