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All Journal JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI)
Haryanto
Universitas Islam Syekh Yusuf
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering

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Implementation of Artificial Intelligence for User Behavior Prediction in Digital Information Systems Asep Abdul Sofyan; Arif Rahman; Sukisno; Haryanto; Dede Irawan
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 5 No. 1 (2026): Juni 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v5i1.1058

Abstract

The rapid advancement of digital information systems has increased the need for intelligent technologies capable of analyzing and predicting user behavior effectively. Artificial Intelligence (AI) has emerged as one of the most significant technologies for enhancing system intelligence, personalization, operational efficiency, and data-driven decision-making processes. This study aims to analyze the implementation of Artificial Intelligence for user behavior prediction in digital information systems. The research employs several AI algorithms, including Decision Tree, Random Forest, Support Vector Machine (SVM), Artificial Neural Network (ANN), and Long Short-Term Memory (LSTM), to evaluate predictive performance in analyzing user interaction data. The datasets used in this study consist of browsing history, transaction records, click frequency, session duration, login activities, and user preferences collected from digital platforms. The research process includes data collection, preprocessing, algorithm implementation, predictive analysis, and performance evaluation. The results indicate that AI-based predictive systems successfully improve behavioral prediction accuracy, personalization capabilities, cybersecurity monitoring, and operational effectiveness. Among all implemented algorithms, the Long Short-Term Memory (LSTM) model achieved the highest predictive accuracy due to its capability in analyzing sequential behavioral patterns. Furthermore, the findings demonstrate that AI implementation significantly contributes to the development of adaptive and intelligent digital information systems. Despite challenges related to privacy, computational complexity, and model interpretability, Artificial Intelligence provides substantial advantages for modern digital ecosystems and supports the advancement of intelligent user-centered services in the era of digital transformation.
The Empowering Village Coffee Farmers through Website Optimization with Predictive RankMath SEO Nia Komalasari; Haryanto; Fauzi; Abdul Azis; Adila Yuansa
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 2 (2025): Jurnal Teknologi dan Open Source, December 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i2.5143

Abstract

This research is motivated by the low visibility and limited marketing of Kopi Kobaki MSME products, managed by the Kobaki Coffee Farmers Association in Banten. Although the community has significant potential to produce high-quality local coffee, the lack of digital literacy and online marketing efforts has caused sales to rely mainly on local intermediaries. This study aims to develop a village economic model based on a website integrated with predictive SEO strategies using the RankMath plugin, expand the market, and support farmers' economic independence. The research methods include needs analysis through surveys and interviews, website design and development using the WordPress platform, implementation of on-page and off-page SEO, and monitoring and evaluation through Google Search Console. The research results show that the kopikobaki.com website can increase the digital visibility of village coffee, even in communities with low digital literacy. The integration of a user-centered design approach, RankMath Pro optimization techniques, and Google Search Console metrics-based evaluation results demonstrates strong digital performance with high CTR and competitive search positions. These findings demonstrate that website-based digitalization can be an effective model for strengthening marketing, improving farmers' digital literacy, and supporting village economic independence through the use of sustainable technology.
Co-Authors Abdul Azis Adila Yuansa Arif Rahman Asep Abdul Sofyan Dede Irawan Fauzi Nia Komalasari Sukisno