Article: Web server log data pre-processing for mining zakat user profile using association rules Journal: International Journal of Business Intelligence and Data Mining (IJBIDM) 2025 Vol.26 No.1/2 pp.46 - 65 Abstract: The internet's transformative impact on businesses and marketing strategies underscores the pivotal role of websites in establishing credibility and disseminating information to customers. To measure website effectiveness, tracking visitor behaviour is essential. This study focuses on web log data from Lembaga Zakat Negeri Kedah (LZNK), a Malaysian government institution managing zakat, which utilises web analytics and mining to gain insights into website usage. The objectives of this paper are two-fold: firstly, to detail the pre-processing of web log data to ensure reliability for data mining. Secondly is to employ association rule mining to extract user patterns from pre-processed web log data. To achieve this, the web logs were obtained from the LZNK's website spanning from 2016 to November 2020 with a focus on user access in 2020. The findings reveal critical aspects of user behaviour including the most visited pages, popular page combinations, user interests, relationships between pages, and the impact of the entry page. Implementing these insights can enhance the LZNK website's usability, user satisfaction, and highlighting the importance of adapting to evolving user preferences and technological advancements. Inderscience Publishers - linking academia, business and industry through research

Title: Web server log data pre-processing for mining zakat user profile using association rules

Authors: Mohamad Farhan Mohamad Mohsin; Wan Hussain Wan Ishak; Yuhanis Yusof; Jastini Mohd Jamil; Alwi Ahmad

Addresses: School of Computing, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia ' School of Computing, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia ' School of Computing, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia ' School of Quantitative Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia ' Lembaga Zakat Negeri Kedah, Menara Zakat, Jalan Teluk Wanjah, 05200 Alor Setar, Kedah, Malaysia

Abstract: The internet's transformative impact on businesses and marketing strategies underscores the pivotal role of websites in establishing credibility and disseminating information to customers. To measure website effectiveness, tracking visitor behaviour is essential. This study focuses on web log data from Lembaga Zakat Negeri Kedah (LZNK), a Malaysian government institution managing zakat, which utilises web analytics and mining to gain insights into website usage. The objectives of this paper are two-fold: firstly, to detail the pre-processing of web log data to ensure reliability for data mining. Secondly is to employ association rule mining to extract user patterns from pre-processed web log data. To achieve this, the web logs were obtained from the LZNK's website spanning from 2016 to November 2020 with a focus on user access in 2020. The findings reveal critical aspects of user behaviour including the most visited pages, popular page combinations, user interests, relationships between pages, and the impact of the entry page. Implementing these insights can enhance the LZNK website's usability, user satisfaction, and highlighting the importance of adapting to evolving user preferences and technological advancements.

Keywords: association rule; data pre-processing; user profile; web log; web mining.

DOI: 10.1504/IJBIDM.2025.143925

International Journal of Business Intelligence and Data Mining, 2025 Vol.26 No.1/2, pp.46 - 65

Received: 20 Nov 2023
Accepted: 07 May 2024
Published online: 14 Jan 2025 *

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Title: Web server log data pre-processing for mining zakat user profile using association rules

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