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Ananda Aulia
Universitas Pembangunan Pancabudi
Computer Science & IT

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Application of the C45 Algorithm to Predict Student Academic Scores Andi Ernawati; Zulham Sitorus; Ananda Aulia; Ayu Ofta
Bulletin of Information Technology (BIT) Vol 5 No 2 (2024): Juni 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i2.1251

Abstract

Student grades are the results of teaching and learning activities on a campus. So you can know your target for completing your studies. This research uses the C4.5 Algorithm which can help predict the results of student assessments. The dataset consists of student achievement index, place of residence, discipline, lecturer's role in lectures. From 40 datasets we have obtained a decision on student academic achievement and obtained performance results from accuracy results of 86.36% with class precision predicate Yes=84.62%, No=88.89% and class recall Yes=91.67%, No=80.00%.
Implementasi Algoritma Naïve Bayes Dalam Menganalisis Jumlah Live Stream VTuber Skem Ananda Aulia; Miftah Rusydi Tanjung; Muhammad Iqbal; Rian Farta Wijaya
Bulletin of Information Technology (BIT) Vol 4 No 4: Desember 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i4.899

Abstract

YouTube is evidence of the development of leading digital technology in the media and entertainment sector. YouTuber is a term for those who create content or broadcast live on YouTube media. Not all YouTubers are able to express themselves directly in the content they create. For this reason, Virtual YouTubers were created, which are 2-dimensional or 3-dimensional virtual characters created using computer software to make it easier for YouTubers to interact with viewers. This research aims to analyze the live broadcasts of VTuber HoloH3ro, namely Kaela Kovalskia, Vestia Zeta, and Kobo Kanaeru, which contain schemes during the live streaming. With a large amount of data for each live stream time, a Naïve Bayes algorithm is needed through the use of range and frequency features, so accuracy results will be obtained which will be tested using the Confusion Matrix. The dataset used was taken from the kaggle.com site regarding the scheme live stream schedule conducted by HoloH3ro.
Co-Authors Andi Ernawati Ayu Ofta Miftah Rusydi Tanjung Muhammad Iqbal Rian Farta Wijaya Sitorus, Zulham