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International Journal of Informatics and Data Science
Published by ADA Research Center
ISSN : -     EISSN : 30267315     DOI : -
Core Subject : Science,
Computer Science & IT
International Journal of Informatics and Data Science publishes manuscripts of Computer Science, but is not limited to the fields of: 1. Natural Language Processing Pattern Classification, 2. Speech recognition and synthesis, 3. Robotic Intelligence, 4. Big Data, 5. Informatics Techniques, 6. Image and Speech Signal Processing, 7. Data Mining 8. Decision Support System, 9. Experts System, and 10. Cryptography
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 3 Documents
 1 
Search results for , issue "Vol. 1 No. 2 (2024): June 2024" : 3 Documents clear
Clustering of YouTube Viewer Data Based on Preferences using Leiden Algorithm Erlin Windia Ambarsari; Aulia Paramita; Desyanti
International Journal of Informatics and Data Science Vol. 1 No. 2 (2024): June 2024
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/ijids.v1i2.45

Abstract

This study aims to analyze YouTube viewer engagement patterns by applying the Leiden algorithm for clustering based on user interactions such as likes, dislikes, and subscription behaviors in correlation with video duration. Therefore, the method that we used begins with data cleaning to ensure completeness, followed by selecting relevant features and applying z-score normalization to equalize their contributions. A similarity graph is constructed using cosine similarity, representing instances as nodes and their relationships as edges. The Leiden algorithm is then applied to optimize modularity and extract clusters, with results integrated into the original dataset for analysis. Dimensionality reduction using PCA facilitates cluster visualization, while statistical summaries and distribution plots provide deeper insights into cluster characteristics. Subsequently, we obtained a dataset sourced from the YouTube content creator @ArmanVesona, which includes 237 instances with ten features: Shares, Comments Added, Dislikes, Likes, Subscribers Lost, Subscribers Gained, Views, Watch Time (hours), Impressions, and Click-Through Rate (%). The analysis reveals two distinct clusters: Cluster 0, characterized by lower engagement and stable audience, and Cluster 1, exhibiting higher engagement but higher subscriber churn. The findings highlight the effectiveness of the Leiden algorithm in detecting well-connected communities and provide insights into viewer behavior, aiding in the development of improved content strategies and targeted marketing approaches.
Customer Service Recruitment Decision Support System Applying MAUT Method Ruziana binti Mohamad Rasli; Mesran; Febrianus Gea; Setiawansyah
International Journal of Informatics and Data Science Vol. 1 No. 2 (2024): June 2024
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/ijids.v1i2.46

Abstract

Customer service is a service provided by the company to consumers who are controlled online or offline by employees of the company, either before or after purchasing products or services. Eligibility in recruitment is very important where a customer service must be able to have good and clear public speaking so that it has an impact on customers. The expected labour problem is not easy and simple, this is because the process is still manual and only based on career level, age and experience. Where, these problems also lack qualified human resources and this makes the recruitment process inaccurate and in accordance with the desired demands.  So the solution is provided through a decision support system, a highly interactive computer-based system that assists in making a decision to utilise data and models in solving unstructured and semi-structured problems. In making decisions apply the MAUT method. In this research conducted using the Multi Attribute Utility Theory (MAUT) Method which is able to obtain maximum results to obtain superior recruitment personnel, namely alternative A1 with a result of 0.8975 as the top alternative after going through the method application stage.
Application of EDAS Method with Entropy Weighting in Performance Assessment of the Best Student Activity Unit Uswatun Hasanah; Mesran; Rian Syahputra
International Journal of Informatics and Data Science Vol. 1 No. 2 (2024): June 2024
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/ijids.v1i2.52

Abstract

The Student Activity Unit (UKM) is an institution formed as a forum for all student activities in developing the interests, talents, creativity and expertise of its members. Performance appraisal is needed to evaluate every achievement and motivate SMEs. Based on the results of interviews conducted with the Vice Chancellor III for Student Affairs at Budi Darma University, he explained that the performance assessment of SMEs at Budi Darma University is still based on the activity of SMEs on campus and has not used other criteria that are clearer and more structured when assessing the performance of the best SMEs at Budi Darma University. . This is certainly less effective and prone to errors. Therefore, a Decision Support System (DSS) is needed as a solution to overcome these problems. In this study, the Entropy method and the EDAS method were applied to 5 criteria and 8 alternatives. Then the alternative chosen according to the criteria for evaluating the performance of the best UKM at Budi Darma University is in alternative A4 with a score of 0.9685, namely SSBD (Sanggar Seni Budi Darma).

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