AI ENHANCED SOFT COMPUTING APPROACH TO STATELESS ARCHITECTURE FOR SECURE SCOPUS DATA MINING USING BYOK

ICTACT Journal on Soft Computing ( Volume: 17 , Issue: 3 )

Abstract

Conducting a Systematic Literature Review (SLR) requires highly precise and verified bibliometric data, establishing the Scopus database as the primary academic benchmark. However, relying on generalized open-access search engines such as Google Scholar and Semantic Scholar presents a critical methodological bottleneck. These platforms lack native filtering mechanisms to strictly isolate Scopus-indexed publications, resulting in high data noise and an overwhelming manual verification overhead for researchers. To overcome this limitation, this study proposes a stateless web architecture utilizing a PHP Native Model-View-Controller (MVC) framework integrated directly with the Elsevier Scopus Search API. By adopting a Bring-Your-Own-Key (BYOK) paradigm, the application empowers researchers to authenticate their institutional credentials. Empirical testing of this BYOK integration across live network environments confirms the successful retrieval and extraction of 100% Scopus-verified metadata. The system employs client-side encapsulation via the JavaScript Blob API to process and export this verified data into Research Information Systems (RIS) and Comma-Separated Values (CSV) formats in real-time. While the local database integration is currently maintained as stateless (0 rows) to optimize processing speed and data privacy, the proposed architecture significantly democratizes and streamlines the literature screening process without relying on expensive commercial software.

Authors

Muhammad Furqan Hakim
Universitas Graha Karya Muara Bulian, Indonesia

Keywords

BYOK, Systematic Literature Review, Model-View-Controller

Published By
ICTACT
Published In
ICTACT Journal on Soft Computing
( Volume: 17 , Issue: 3 )
Date of Publication
October 2026
Pages
4445 - 4451
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28
Full Text Views
2