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All Journal Jurnal Masyarakat Informatika Jurnal Transformatika African Multidisciplinary Journal of Sciences and Artificial Intelligence
Aimufua, Gilbert
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Environmental Science Materials Science & Nanotechnology

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MOBILE PRIVACY AWARENESS OF HIGHER EDUCATION STUDENTS IN PLATEAU STATE NIGERIA Jegede, Abayomi; Chagga, Chagga Aku; Aimufua, Gilbert; Mazadu, Jesse; Oloyede, Ayodele; Olubodun, Kolawole
Jurnal Transformatika Vol. 20 No. 2 (2023): January 2023
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v20i2.5444

Abstract

The ubiquitous nature of mobile devices and wide array of applications (and services) they offer make them useful in virtually all areas of human endeavours. Owners of mobile devices store large amounts of vital and sensitive personal information on their devices. Unauthorized access to such information by third parties can violate the privacy of users and expose individuals and businesses to huge financial loses and damage to reputation. This makes it imperative for owners of technology service providers and owners of mobile devices to take proactive steps that prevent privacy violation. One of such critical steps is privacy awareness, which is the knowledge and consciousness of the need for privacy, an understanding of actions that promote or compromise privacy and the consequences of irresponsible online behaviour. The aim of this study is to assess the level of awareness of tertiary institution students with respect to privacy issues associated with the use of mobile communication devices. The research uses questionnaires to obtain data on the privacy awareness of users of mobile devices in some tertiary institutions in Plateau State. The paper investigates the current status of mobile privacy issues and awareness of users in these tertiary institutions. It also attempts to expose the gaps in privacy awareness of mobile device users, the factors responsible for limited privacy awareness and strategies for addressing the low level of privacy awareness of mobile device users. The results from this study show that high level of literacy does not necessarily imply high-level privacy awareness. Many respondents who are privacy aware do not possess the necessary skills or knowledge to ensure data and user privacy on their mobile devices. Others who possess this knowledge are will to engage in practices that compromise privacy in exchange for financial gain. Overall, the study exposes the actual level of privacy awareness and defeat the assumption that high level of education automatically results in high-level privacy awareness. It also contradicts the assumption that being privacy-aware guarantees responsible online behaviour and adherence to practices that promote online privacy.
Parameter-Efficient Few-Shot Sentiment Analysis Using LoRA-Enhanced Transformers Jibrin, Nurudeen; Aimufua, Gilbert; Onyedikachi, Okorie Sunday; Anthony, Alegbe Adesola; Chukwunwike, Ugbai Solomon; Aliyu, Fadila Dantalle
Jurnal Masyarakat Informatika Vol 17, No 1 (2026): May 2026 (Ongoing)
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.17.1.81053

Abstract

Sentiment analysis in low-resource languages is often limited by scarce annotated data and the high computational cost of fine-tuning large language models. This study proposes a parameter-efficient framework that integrates Low-Rank Adaptation (LoRA) with lightweight transformer architectures, including AfriBERTa, DistilBERT, and MiniLMv2, for Hausa sentiment analysis using the NaijaSenti dataset. The framework is designed to address three key challenges: effective few-shot learning, robustness under extreme data scarcity, and mitigation of language-specific linguistic errors. Experimental results demonstrate that AfriBERTa-LoRA achieves 69.0% accuracy, only 4.8 percentage points below a fully fine-tuned XLM-RoBERTa baseline, while utilizing just 1.06% of trainable parameters and reducing GPU memory consumption by approximately 50%. Performance improves consistently with increasing data, indicating strong scalability under few-shot conditions. Linguistic error analysis reveals four dominant Hausa-specific failure modes accounting for 71.5% of misclassifications. Targeted mitigation strategies yield an 8.7 percentage point reduction in error rate (28% relative reduction, p < 0.01), with each individual strategy demonstrating statistical significance. These findings establish LoRA as an effective and efficient paradigm for low-resource natural language processing, providing a scalable and reproducible framework for sentiment analysis in underrepresented African languages.
Comparative Analysis of Theoretical Models for Digital Forensic Readiness (DFR) in Nigerian Banking Akujobi, Chibuzor; Ogwueleka, Francisa; Aimufua, Gilbert; Bassey, Steven
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 3 No 1 (2026): African Multidisciplinary Journal of Sciences and Artificial Intelligence
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/amjsai.v3i1.8322

Abstract

The increasing shift to digital banking in Nigeria has accelerated cyber fraud losses, prompting banks to adopt proactive forensic readiness measures. Recent industry reports show that Nigerian banks lost more than N300 billion ($833 million) in a single quarter of 2023, a 534% increase year-on-year. Digital Forensic Readiness (DFR) is a proactive cybersecurity strategy that ensures digital evidence is preserved and ready for analysis before a breach occurs. This paper reviews leading forensic readiness models, including Locard’s Exchange Principle, the Diamond Intrusion Model, and the NIST Risk Management Framework, and compares their applicability to Nigerian banking. We integrate these theories into a proposed DFR framework tailored for Nigeria’s banking sector, drawing on local and global studies. Key components of DFR (such as policies, technology, people, and legal compliance) are discussed with illustrations. Current challenges, notably reactive culture, evidentiary gaps, and regulatory compliance, are highlighted. Finally, best practices and a synthesis framework are presented to guide Nigerian banks toward a more resilient forensic posture.
Co-Authors Akujobi, Chibuzor Aliyu, Fadila Dantalle Anthony, Alegbe Adesola Bassey, Steven Chagga, Chagga Aku Chukwunwike, Ugbai Solomon Jegede, Abayomi Jibrin, Nurudeen Mazadu, Jesse Ogwueleka, Francisa Oloyede, Ayodele Olubodun, Kolawole Onyedikachi, Okorie Sunday