Garuda - Garba Rujukan Digital

Wandi Syahindra

Institut Agama Islam Negeri (IAIN) Curup Bengkulu, Indonesia

Author-ID : 837837

Religion Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences Other

Published : 18 Documents Claim Missing Document

Claim Missing Document

Articles

Title

1

Matrix Integration with Jitsi Conference Server for Online Learning Rini Widyastuti; Karmila Suryani; Ade Fitri Rahmadani; Triadmoko Denny Fatrosa; Wandi Syahindra
Knowbase : International Journal of Knowledge in Database Vol 1, No 2 (2021): December 2021
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

The current online learning process requires virtual face-to-face media to interact between lecturers and students. However, currently available media requires lecturers to pay a fee to communicate indefinitely. Therefore, we need a media that can facilitate lecturers to do learning easily. This study aims to integrate jitsi with matrix conferences as a real-time online communication medium in learning. This type of research is development research (R&D) with the waterfall method. The steps taken are analysis, design, coding and testing. The analysis is carried out on the system development needs, then the design stage of the Jitsi architecture with a matrix, then coding using PHP and testing through QoS. QoS testing has very good throughput results, poor packet loss, very good delay, and excellent jitter for small-scale applications. It shows that picking video conferencing can be used as a medium of communication in online learning.

Application of the Naïve Bayes Algorithm in Classifying the Reading Interests of Regional Library Visitors Murlena, Murlena; Syahindra, Wandi
Knowbase : International Journal of Knowledge in Database Vol. 4 No. 1 (2024): June 2024
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v4i1.8680

Reading interest is a key indicator in assessing the success of library services. However, manually understanding visitors' preferences poses a challenge for library managers. This study aims to classify the reading interests of regional library visitors by employing the Naïve Bayes algorithm, a widely-used classification method in data mining. The research data includes visit records and book borrowing data from a regional library. Through a quantitative approach, this study analyzes reading interest patterns and evaluates the performance of the Naïve Bayes algorithm in classifying these interests. The analysis results show that the algorithm achieves an accuracy of 65%, with a precision of 62%, recall of 63%, and F1-score of 63%. These findings are expected to assist libraries in formulating better-targeted collection management and service policies, contributing to the overall improvement of reading interest in the community. This study contributes to the field by providing a practical, data-driven solution for libraries to enhance service quality through a better understanding of visitor preferences. Furthermore, it demonstrates the applicability of the Naïve Bayes algorithm in a non-commercial context, encouraging future research on data-driven approaches in library management to support literacy and educational development

Application of the Naïve Bayes Algorithm in Classifying the Reading Interests of Regional Library Visitors Murlena, Murlena; Syahindra, Wandi
Knowbase : International Journal of Knowledge in Database Vol. 4 No. 1 (2024): June 2024
Publisher : Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/knowbase.v4i1.8680

Reading interest is a key indicator in assessing the success of library services. However, manually understanding visitors' preferences poses a challenge for library managers. This study aims to classify the reading interests of regional library visitors by employing the Naïve Bayes algorithm, a widely-used classification method in data mining. The research data includes visit records and book borrowing data from a regional library. Through a quantitative approach, this study analyzes reading interest patterns and evaluates the performance of the Naïve Bayes algorithm in classifying these interests. The analysis results show that the algorithm achieves an accuracy of 65%, with a precision of 62%, recall of 63%, and F1-score of 63%. These findings are expected to assist libraries in formulating better-targeted collection management and service policies, contributing to the overall improvement of reading interest in the community. This study contributes to the field by providing a practical, data-driven solution for libraries to enhance service quality through a better understanding of visitor preferences. Furthermore, it demonstrates the applicability of the Naïve Bayes algorithm in a non-commercial context, encouraging future research on data-driven approaches in library management to support literacy and educational development

Title Search

Found 3 Documents Search Journal : Knowbase : International Journal of Knowledge in Database

Abstract

Abstract

Abstract

Title

Found 3 Documents
Search
Journal : Knowbase : International Journal of Knowledge in Database