Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal International Journal of Social Service and Research Bulletin of Data Science
Ragil, Muhammad
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Bulletin of Data Science

 1 
Analisa Sentimen Terhadap Transisi Dari Work From Home ke Work From Office Menggunakan Metode Text Mining Dan TF-IDF Ragil, Muhammad
Bulletin of Data Science Vol 3 No 1 (2023): October 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletinds.v3i1.5694

Abstract

The implementation of the WFH(Work From Home) and WFO(Work From Office) work schemes has problems related to the adjustment of the work system by workers. Every company or industrial world always prioritizes the value of productivity in any circumstances to prevent a significant decrease in profits. In this sentiment analysis, the researcher uses the Text Mining and TF-IDF methods based on data collected from the Orange DataMining Twitter application by entering the Twitter Key Secret Token API to retrieve the data from the Twitter social networking platform. And continued with the Text Mining process which is used to select the data that has been taken through the Orange application so that it becomes text that is regularly in accordance with the Transformation, Tokenization, Stemming and Stopword stages, it will continue to the tf-idf or weighting process where the sentence weights are in accordance with the criteria certain, if it is necessary to use a descriptive method to percentage the positive and negative values that evaluate negatively to the transition in the WFH to WFO transition period by 76.05%.
Co-Authors Khaerudin Imawan Kusuma, Wahyu Dwa