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All Journal Jurnal F. Teknik : RESULTAN Paradigma : Journal of Science, Religion and Culture Studies Techno.Com: Jurnal Teknologi Informasi PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic JREC (Journal of Electrical and Electronics) DEVOSI Journal of Students‘ Research in Computer Science (JSRCS) Journal of Computer Science Contributions (Jucosco)
Malikus Sumadyo
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Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Social Sciences

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Journal : Journal of Students‘ Research in Computer Science (JSRCS)

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Analisis Sentimen Masyarakat Terhadap Kebijakan Pemerintah Selama Pandemi Covid-19 Menggunakan Algoritma Naïve Bayes Emeraldi, Muhammad Aqil; Ekawati, Inna; Sumadyo, Malikus
Journal of Students‘ Research in Computer Science Vol. 3 No. 1 (2022): Mei 2022
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/ycx3jc57

Abstract

The increase in data is very large, one of the sources comes from social media, especially Twitter which talks a lot about Covid-19 . The news through Twitter media regarding the impact of the Covid-19 virus is widely discussed because it causes unrest for the public which has led to the issuance of various government policies with the aim of preventing the spread of Covid-19 . Related to this, it is necessary to conduct a sentiment analysis of the text contained in the Twitter media. In this study, a sentiment analysis process was carried out related to public sentiment towards government policies during the Covid-19 pandemic in Indonesia on Twitter social media using the Naive Bayes Classifier method where the data used was classified into 2 sentiment values, namely positive and negative sentiment. The data used are 300 positive tweets data and 300 negative tweets data, where 80% of the total data is used as training data and 20% data is used as test data. Based on the test results, the data with a total of 120 tweets obtained the results of measuring the recall value of 93.33%, precision 93.33%, F-Score 93.33% and an average accuracy of 93.33%.
Konversi ke Microservices Untuk Peningkatan Layanan Perpustakaan Sumadyo, Malikus; Handayanto, Rahmadya Trias; Setiawan, Ramdhani
Journal of Students‘ Research in Computer Science Vol. 5 No. 2 (2024): November 2024
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/vr275f23

Abstract

Most web-based applications are applications that provide services to users. The services themselves often change according to policies that are usually based on user satisfaction information. Unfortunately, existing applications are mostly based on open-source which is mostly monolithic. If there is an addition of a new service, it requires development from the beginning again. Especially when there is an imbalance between one service and another where one service requires large resources while other services do not require too many resources such as processors, network speed, or database size. This study tries to propose a system change in the library based on PHP-MySQL to be based on microservices.
Co-Authors Ainur Rofieq Anita Setyowati Srie Gunarti Dadan Irwan Ekawati, Inna Emeraldi, Muhammad Aqil Endang Retnoningsih Harun Alrasyid Haryono Haryono Hendharsetiawan, Andy Achmad Herlawati Herlawati Lucky Purwantini Maimunah, Maimunah Prima Dina Atika Qussay Rizhain, Yufi Tuesriza Rahmadya Trias Handayanto Rahmat Nuryono Retno Nugroho Whidhiasih Seta Samsiana Setiawan, Ramdhani Tama, Annafi Indra