Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
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This Author published in this journals
All Journal Journal of Information Systems and Informatics International Journal of Artificial Intelligence and Science
George Matto
Moshi Co-operative University
Computer Science & IT

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Association Rule Mining for Uncovering Co-occurring Skill Sets in Multi-Portal ICT Job Advertisements Erick Samwi; George Matto; Mercy Mbise
Journal of Information System and Informatics Vol 8 No 4 (2026): August
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i4.1671

Abstract

Rapid changes in the ICT labour market require stakeholders to understand not only which skills are demanded but also how these skills occur together. However, existing studies provide limited insights into co-occurring skill demands in ICT jobs. This study addresses this gap by uncovering skill sets that frequently appear together in ICT job descriptions. A total of 15,653 unique ICT job advertisements published between 2020 and 2025 were collected from LinkedIn, AjiraYako and Mabumbe to capture regional and international contexts. Guided by the Cross-Industry Standard Process for Data Mining (CRISP-DM), association rule mining using the Apriori algorithm identified frequent itemsets and generated rules evaluated using support, confidence and lift. The analysis revealed strong co-occurrences among programming skills, such as C# and C++ (confidence = 1.00; lift = 2.41), although this combination occurred in a small proportion of advertisements (support = 0.0096). Java and Python showed the highest support (0.1818), with confidence values of 0.51 and 0.42 and a lift of 1.19, which indicate a positive association despite belonging to different application domains. By uncovering skill associations beyond individual skill frequencies, the study provides richer labour market intelligence for workforce development and policy formulation.
Awareness and Adoption of Big Data Technology in Public Sector Auditing in Tanzania: Mediation Effect of Knowledge Management Practices. Albert Raymond Moshi; Alfre Sife; George Matto
International Journal of Artificial Intelligence and Science Vol. 3 No. 1 (2026): March
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/IJAIS.v3i1.60

Abstract

Big data technology enables auditors to identify patterns and anomalies across extensive datasets, supporting improved audit quality. However, its adoption in Tanzania’s public sector auditing remains limited. This study examines the mediating role of knowledge management practices in the relationship between awareness and readiness to adopt big data technology. Drawing on Diffusion of Innovation (DOI) theory and Knowledge Management Theory (KMT), it proposes that awareness provides the foundation for adoption readiness, while knowledge creation, sharing and application translate awareness into practical capabilities. Data were collected from 221 randomly selected respondents and analysed using descriptive statistics and binary logistic regression. The findings indicate that knowledge management practices mediate the relationship between awareness and adoption readiness, highlighting their role in developing skills for technological adoption. Descriptive results reveal high operational awareness but low technical awareness among auditors, indicating a technical skills gap. These findings suggest that awareness alone is insufficient without mechanisms for acquiring, sharing and applying relevant knowledge. Public sector auditing institutions in Tanzania should strengthen knowledge management through targeted training programmes and knowledge sharing platforms. The study contributes an integrated DOI–KMT perspective explaining how awareness and knowledge management jointly support readiness for big data adoption in public sector auditing.
The Cyber Kill Chain Model and Its Applicability on The Protection of Students Academic Information Systems (SAIS) in Tanzanian HEIs George Matto
Journal of Information System and Informatics Vol 6 No 1 (2024): March
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i1.676

Abstract

Security threats are constantly evolving in various computerized systems. As in many other systems, security threats and attacks have been directed to Students Academic Information System (SAIS) in Higher Education Institutions (HEIs). The seven steps cyber kill chain model offers preventive defense against such security threats. Little is known, however, on how well the model is applicable in the protection of SAIS. This study was therefore carried out to investigate the applicability of the cyber kill chain model on the protection of SAIS. The study was qualitative in which empirical evidence from literature was employed to gather data which were then analysed thematically through content analysis. Results showed that the cyber kill chain model is very relevant and applicable in the protection of SAIS. Each of the seven steps of the model practically applies differently in SAIS which entails for distinct protective measures as detailed in the paper. The study calls upon HEIs stakeholders to leverage the proposed preventive measures against security threats in SAIS.
Co-Authors Albert Raymond Moshi Alfre Sife Erick Samwi Mercy Mbise