Indonesian Journal of Artificial Intelligence and Data Mining

Indonesian Journal of Artificial Intelligence and Data Mining (IJAIDM) is an electronic periodical publication published by Puzzle Research Data Technology (Predatech) Faculty of Science and Technology UIN Sultan Syarif Kasim Riau, Indonesia. IJAIDM provides online media to publish scientific articles from research in the field of Artificial Intelligence and Data Mining.

IJAIDM will be published 2 (two) times a year, in March and September, each edition contains 7 (seven) articles. Articles may be written in English with 20% Similarity. Articles submitted to IJAIDM will be reviewed at least by 2 (two) reviewers. The submitted article must meet the assessment criteria and in accordance with the instructions and templates provided by IJAIDM. The author should upload the Statement of Intellectual/ Copyright Rights when submitting the manuscript. Paper must be sent to Open Journal System (OJS) with .doc or .docx format. The entire process until IJAIDM is published will be free of charge. IJAIDM is registered in National Library with Number International Standard Serial Number (ISSN) Printed: 2614-3372 and Online 2614-6150. IJAIDM uses Turnitin plagiarism checks, Mendeley for reference management and supported by Crossref (DOI) for identification of scientific paper. Organization Statement Letter of Chancellor: 2018 | 2019 | 2020 | 2021

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Journal Homepage Image

Journal title: Indonesian Journal of Artificial Intelligence and Data Mining
Initial: IJAIDM
Frequency: 2 Issues per Year
DOI: Crossref
Editor in Chief: Mustakim, S.T., M.Kom. [Scopus | Google Scholar | Sinta]
Publisher: Puzzle Research Data Technology (Predatech) UIN Sultan Syarif Kasim Riau
Accredite: SINTA 3 KEMENDIKBUD
Language: English
Similarity Check: Under 20% Turnitin
Publish Online: March and September
Management References: Mendeley (Min 20 References Intenational Journal)

International Contributor (Editor, Reviewer and Author)

           

Indonesian Journal of Artificial Intelligence and Data Mining (IJAIDM) indexing by:

 

Attention:
Authors who have submitted to IJAIDM and have received assessment results from reviewers, please immediately fix your paper (if revised) within a maximum 30 days. If within that time there is no news, information and notification either via email (ijaidm@uin-suska.ac.id) or via WhatsApp (Fast Response), we from IJAIDM Team will reject the paper and include the author on IJAIDM blacklist.

Vol 7, No 2 (2024): September 2024

In Press for Next Edition

Table of Contents

Articles

Optimizing Performance Random Forest Algorithm Using Correlation-Based Feature Selection (CFS) Method to Improve Distributed Denial of Service (DDoS) Attack Detection Accuracy
DOI : 10.24014/ijaidm.v7i2.24783 | Abstract views : 23 times
Sopian Soim, Sholihin Sholihin, Cahyo Bayu Subianto
Exploratory Data Analysis of Indonesian Presidential Election Candidate Campaign in 2019 on Twitter
DOI : 10.24014/ijaidm.v7i2.26308 | Abstract views : 25 times
Fadlan Bima Hermawan, Taufik Edy Sutanto, Ary Santoso
AI-Generated Misinformation: A Literature Review
DOI : 10.24014/ijaidm.v7i2.26455 | Abstract views : 35 times
Rafharum Fatimah, Auziah Mumtaz, Fauzan Muhammad Fahrezi, Diky Zakaria
Predictive Maintenance for Electrical Substation Components Using K-Means Clustering: A Case Study
DOI : 10.24014/ijaidm.v7i2.26815 | Abstract views : 14 times
Hizkia Raditya Pratama Roosadi, Hughie Alghaniyyu Emiliano, Satria Dina Astari, Nugraha Priya Utama, Rahman Indra Kesuma
Eligibility Study of Targeted Electricity Subsidies Using DBSCAN on 450 VA and 900 VA Households at PLN UP3 Bandung
DOI : 10.24014/ijaidm.v7i2.26818 | Abstract views : 13 times
Randy Zakya Suchardy, Adi Firmansyah, Nugraha Priya Utama, Rahman Indra Kesuma
Data Augmentation Using Test-Time Augmentation on Convolutional Neural Network-Based Brand Logo Trademark Detection
DOI : 10.24014/ijaidm.v7i2.28804 | Abstract views : 54 times
Suyahman Suyahman, Sunardi Sunardi, Murinto Murinto, Arfiani Nur Khusna
Decoding Energy Usage Predictions: An Application of XAI Techniques for Enhanced Model Interpretability
DOI : 10.24014/ijaidm.v7i2.29041 | Abstract views : 46 times
Gregorius Airlangga