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Journal of Information Systems Engineering and Business Intelligence (JISEBI) is an international peer-reviewed open-access journal. JISEBI aims to promote high-quality Information Systems (IS) research among academics and practitioners alike, including computer scientists, IS professionals, business managers, and other stakeholders in the industry. Contributed papers must be original and offer an impactful contribution. At least two independent reviewers will review each manuscript in the relevant field to ensure the publication of only top-quality contributions. JISEBI offers an open-access license (CC-BY) while retaining the copyright for the authors. The Journal of Information Systems Engineering and Business Intelligence has been accredited by the Ministry of Research, Technology, and Higher Education Indonesia with Peringkat 1 (SINTA 1) from 2023 to 2027 with the decree number 79/E/KPT/2023 dated May 11, 2023. The journal accreditation certificate can be downloaded here.
We are pleased to inform you that, as of March 12, 2023, the Journal of Information Systems Engineering and Business Intelligence has been accepted for Scopus.
Current Issue
Articles
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Ensemble Learning Based Malicious Node Detection in SDN-Based VANETs
136-146Abstract : 214PDF : 83 -
Crypto-sentiment Detection in Malay Text Using Language Models with an Attention Mechanism
147-160Abstract : 166PDF : 62 -
Enhancing Multi-Output Time Series Forecasting with Encoder-Decoder Networks
195-213Abstract : 198PDF : 66 -
Systematic Literature and Expert Review of Agile Methodology Usage in Business Intelligence Projects
214-227Abstract : 163PDF : 86 -
Transfer Learning based Low Shot Classifier for Software Defect Prediction
228-238Abstract : 118PDF : 55 -
Fine-Tuning IndoBERT for Indonesian Exam Question Classification Based on Bloom's Taxonomy
253-263Abstract : 134PDF : 49 -
A Systematic Literature Review of Student Assessment Framework in Software Engineering Courses
264-275Abstract : 162PDF : 100 -
Information Quality of Business Intelligence Systems: A Maturity-based Assessment
276-287Abstract : 110PDF : 77 -
A Fast and Reliable Approach for COVID-19 Detection from CT-Scan Images
288-304Abstract : 136PDF : 60