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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Tata Kelola dan Kerangka Kerja Teknologi Informasi
Dwinnie, Zairy Cindy
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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AUDIT TATA KELOLA TEKNOLOGI INFORMASI PADA LAYANAN AKADEMIK FAKULTAS SAINS DAN TEKNOLOGI MENGGUNAKAN COBIT 2019 Suryani, Suryani; Dwinnie, Zairy Cindy; Dwynne, Zaira Cindya; Pramana, Jeki Harya; Megawati, Megawati
Jurnal Tata Kelola dan Kerangka Kerja Teknologi Informasi Vol 9 No 2 (2023): November 2023
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jtk3ti.v10i1.11847

Abstract

The development of information technology requires universities to update and improve information technology infrastructure to face competition and take advantage of the times. Service is the main aspect that can facilitate public affairs in the higher education environment. The use of the COBIT 2019 Framework is considered an effective guide for implementing Information Technology in managing the Academic Information System at the Faculty of Science and Technology, Sultan Syarif Kasim Riau State Islamic University. This framework makes a valuable contribution to supporting overall Information Technology management. This research has a specific objective, which is to apply the COBIT 2019 Framework to design effective information technology governance in business and technology management. Hopefully, this research will provide relevant information related to the implementation of such governance. Keywords – Audit, COBIT 2019, Academic Information System
Penerapan Machine Learning Pada Analisis Sentimen Twitter Sebelum dan Sesudah Debat Calon Presiden dan Wakil Presiden Tahun 2024 Dwinnie, Zairy Cindy; Novita, Rice
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 2 (2024): April 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i2.7504

Abstract

The 2024 Presidential Election has become the hottest topic in the past two years. The KPU has confirmed that there are 3 candidates for President and Vice President. For this reason, as a momentum for voters to assess the 2024 Presidential and Vice Presidential candidates, the KPU is holding the 2024 Presidential Choice Debate which is based on Law Number 7 of 2017 concerning General Elections. Based on the information presented on the kpu.go.id page, the debate will be held 5 times with 3 presidential candidate debates and 2 vice presidential candidate debates. For this reason, it is necessary to carry out an analysis to find out how public sentiment is positive, negative, and neutral on Twitter towards the three candidates for President and Vice President in 2024 before and after the debate was held. The aim is to estimate public support or disapproval of the three candidate pairs. This research uses three algorithms as a comparison of classification accuracy, namely the Support Vector Machine algorithm, Random Forest, and Logistic Regression. Where the data used is tweet data on Twitter related to before and after the debate as many as 30 datasets with a total of 9000 data. From the classification results, the average accuracy obtained for the three algorithms, namely SVM and Random Forest, was 78%, and Logistic Regression was 79%. The highest polarity obtained from the classification of the three algorithms is in the positive class. This indicates that the Logistic Regression algorithm provides better performance in classifying Twitter sentiment regarding the 2024 presidential and vice presidential candidate pairs.
Co-Authors Dwynne, Zaira Cindya Megawati - Pramana, Jeki Harya Rice Novita Suryani Suryani