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All Journal Jurnal Ilmiah Matrik Journal of Information Technology Ampera International Journal of Social Science, Education, Communication and Economics
Al Qorni, Qois
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Religion Arts Humanities Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

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Pendekatan Algoritma Naïve Bayes dan Support Vector Machine dalam Menganalisis Tanggapan Terhadap Penutupan Tik Tok Shop kurniawan, Fandi; Al Qorni, Qois
Jurnal Ilmiah Matrik Vol. 25 No. 3 (2023): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/jurnalmatrik.v25i3.2732

Abstract

The development of information technology, especially in social media such as TikTok, has had a significant impact on people's shopping behavior patterns. Sentiment analysis is aimed at understanding general views regarding the closure of the TikTok Shop, describing positive or negative opinions. The algorithms used are Naïve Bayes and Support Vector Machine (SVM) to analyze responses to the closure of the TikTok Shop. The research methodology involves the process of crawling the Twitter dataset with the keyword "Tik Tok Shop", data cleaning, sentiment labeling, model building, and performance testing. The results of the sentiment analysis are parsed and analyzed to describe the general sentiment towards the closure of the Tik Tok Shop. The conclusion results show that the Naïve Bayes algorithm achieved an accuracy level of 97.91%, with positive recall of 100%, positive precision of 96.30%, negative recall of 95.42%, and negative precision of 100%. Meanwhile the SVM algorithm achieved an accuracy of 91.29%, with a positive recall of 100%, positive precision of 86.19%, negative recall of 80.92%, and negative precision of 100%. Overall, Naïve Bayes provides the highest accuracy results of 97.91%, while SVM provides an accuracy of 91.29%.
Exploring Sentimen Analysis Using Machine Learning: A Case Study on Partai Demokrasi Indonesia Perjuangan (PDIP) in the 2024 General Election Kurniawan, Fandi; Al Qorni, Qois
International Journal of Social Science, Education, Communication and Economics (SINOMICS JOURNAL) Vol. 2 No. 4 (2023): October
Publisher : Lafadz Jaya Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/sj.v2i4.194

Abstract

General elections have an important role in democratic systems in all countries. In this context, sentiment analysis plays an important role in revealing the public's views on political parties. This study analyzes sentiment towards the Partai Demokrasi Indonesia Perjuangan (PDIP) in the 2024 General Election using the Naive Bayes algorithm. This method classifies social media content related to PDIP into positive (support) or negative (criticism) categories. The analysis results show 100% precision in identifying positive sentiment, but recall is only 97.11%, indicating that some positive sentiment was missed. For negative sentiment, the precision was 94.33% with a recall of 100%, indicating the ability to recognize negative sentiment but little negative prediction error. This study provides an in-depth understanding of the PDIP's perception in the 2024 General Election, supports better political decision making and provides insight to the PDIP in understanding the public's views.
Analisis Manajemen Pelayanan Da’i Pemkot Palembang Pada SILTANUS Berbasis TI Menggunakan Framework ITIL V3 Al Qorni, Qois; Sutabri, Tata
Journal of Information Technology Ampera Vol. 5 No. 1 (2024): Journal of Information Technology Ampera
Publisher : APTIKOM SUMSEL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalita.v5i1.511

Abstract

SILTANUS, sebuah Layanan Teknologi Informasi (TI) yang diinisiasi oleh pemerintah kota Palembang untuk membantu Da'i (pendakwah Islam) dalam menyebarkan ajaran agama di seluruh kota. Masalah utama yang dibahas dalam penelitian ini adalah identifikasi kekurangan SILTANUS untuk secara efektif mengevaluasi fungsionalitas sistem dan kinerja aplikasi secara keseluruhan. Untuk mengatasi ini, studi menggunakan Kerangka Kerja ITIL V3, sebuah kerangka kerja manajemen layanan IT yang diakui secara global, menawarkan pendekatan terstruktur untuk merencanakan, mengimplementasikan, dan mengelola layanan TI agar sesuai dengan kebutuhan spesifik. Melalui penerapan kerangka kerja ITIL V3, penelitian ini bertujuan untuk meningkatkan pengelolaan layanan TI oleh pemerintah kota Palembang, meningkatkan efisiensi operasional, dan mendukung pencapaian tujuan program. Temuan menunjukkan bahwa sementara SILTANUS memiliki potensi untuk secara signifikan meningkatkan manajemen layanan untuk Da'i, saat ini terhambat oleh beberapa keterbatasan, termasuk kurangnya fitur, kinerja yang tidak stabil, dan kebutuhan untuk meningkatkan kualitas layanan. SILTANUS, an Information Technology (IT) Service initiated by the Palembang city government to aid Da'is (Islamic preachers) in disseminating religious teachings throughout the city. The main issue addressed in this research is the identification of SILTANUS's shortcomings to effectively evaluate the system's functionality and overall application performance. To address this, the study employs the ITIL V3 Framework, a globally recognized framework in IT service management, offering a structured approach for planning, implementing, and managing IT services to align with specific needs. Through the application of the ITIL V3 framework, this research aims to enhance the Palembang city government's IT service management, improve operational efficiency, and support the attainment of program objectives. The findings reveal that while SILTANUS holds the potential to significantly improve service management for Da'is, it is currently hindered by several limitations, including a lack of features, unstable performance, and a need for improved service quality.
Co-Authors Kurniawan, Fandi Tata Sutabri