Indonesian Journal of Innovation and Applied Sciences (IJIAS)

Teaching accounting for the fourth industrial revolution: ICT integration in South African schools

Mlindeni Celinhlalo Siyaya — 2026-02-27

This study examines the integration of Information and Communication Technology (ICT) in the teaching of accounting in South African secondary schools, focusing on the ILembe District. In the context of the Fourth Industrial Revolution, ICT use is increasingly essential for enhancing pedagogical practices and developing learners’ digital competence. Using a qualitative design, semi-structured interviews were conducted with ten accounting teachers, and the data were analysed thematically. The findings show that although teachers recognise ICT’s value for improving learner engagement and understanding, its effective use is constrained by inadequate infrastructure, limited access to devices, insufficient professional development, and resistance to technological change. Teacher motivation, departmental support, and learner interest were identified as key enablers. To address the uneven integration of ICT across schools, the study recommends targeted and sustained professional development as a central intervention. In response to the identified needs, the study proposes an ICT-Driven Teachers’ Professional Development Model (ICT DTPM) to guide future capacity-building efforts. The findings contribute to ongoing discussions on ICT in education and offer practical insights for strengthening accounting education in line with the demands of the Fourth Industrial Revolution.

Entrepreneurship education and digital skills acquisition in selected federal tertiary institutions in Osun State, Nigeria

Opeyemi Jumoke Zubair — 2026-02-27

This study examines the degree to which entrepreneurship education fosters digital skills among students in the context of ongoing graduate digital illiteracy despite required entrepreneurship courses across three federal tertiary institutions in Osun State, Nigeria. The goals are to evaluate students' inventiveness, digital literacy, and preparedness for online business, as well as to ascertain how exposure to entrepreneurship education and digital competency relate to one another. Using a descriptive mixed-methods methodology, 30 professors chosen by stratified and simple random sampling participated in semi-structured interviews, and 285 students completed questionnaires. Thematic analysis was used to look at qualitative data, while descriptive statistics, one-way ANOVA, and Pearson correlation were used to evaluate quantitative data. The results indicate that while entrepreneurship education is widely used and increases awareness of business opportunities, the curriculum is still mostly theoretical and covers little in the way of digital marketing, e-commerce, and data analytics, which results in students having only a moderate level of digital competency. Digital skills and entrepreneurial education were found to have a substantial positive association (r = 0.63, p < 0.05), although this relationship is limited by curriculum gaps, poor infrastructure, and insufficient lecturer training. In order to guarantee that entrepreneurship education more successfully supports digital empowerment and employability in Nigeria's technology-driven economy, the study suggests curriculum change, enhanced digital infrastructure, and focused capacity building for lecturers.

Spatial analysis of drought-prone locations using geographic information systems in Hulu Sungai Utara Regency

Haji Muhammad Ridha — 2026-02-27

Hulu Sungai Utara Regency is one of the regions in South Kalimantan Province that has a high potential for drought disasters due to the influence of climate variability, the relatively flat physical condition of the region, and limited spatial information regarding drought-prone areas. The absence of accurate vulnerability maps has resulted in mitigation efforts not being optimal. This study aims to map the level of drought vulnerability in Hulu Sungai Utara Regency and identify the main factors that influence it. The method used is a Geographic Information System (GIS)-based spatial analysis with a weighted overlay technique using the Analytical Hierarchy Process (AHP) method. The parameters analyzed include slope gradient, land elevation, rainfall, soil type, land cover, river density, vegetation index (NDVI), wetness index (NDWI), and land surface temperature (LST). The results show that most areas of Hulu Sungai Utara Regency are categorized as moderately drought-prone with a percentage of 95.361%, while the non-vulnerable category only covers 4.639% of the area, and no highly vulnerable areas were found. The most influential factor on drought vulnerability is rainfall, followed by NDWI and NDVI. It is hoped that the resulting vulnerability map can be the basis for mitigation planning and sustainable water resource management.

Developing a graph-based machine learning model for identifying money laundering networks associated with sanctioned entities in a bank in Zimbabwe

Belinda Ndlovu — 2026-02-27

Money laundering networks associated with sanctioned entities pose a significant risk to financial systems, often operating through complex relational transaction structures that evade traditional rule-based monitoring. While graph neural networks have demonstrated promise in financial crime detection, limited work has formally modelled sanction-linked transaction networks within highly imbalanced banking datasets under consistent comparative evaluation. This study proposes a directed weighted graph-based learning framework for identifying sanction-associated money laundering networks using real-world banking transaction data. Transactions were modelled as relational graphs, with accounts as nodes and transfers as weighted edges, and evaluated using a Graph Convolutional Network (GCN) against classical and ensemble classifiers. The proposed model achieved an accuracy of 88.18%, F1-score of 0.7345, ROC-AUC of 0.8968, and a superior Matthews Correlation Coefficient compared to baseline methods. Results demonstrate that relational graph modelling improves the detection of structurally coordinated laundering behaviours that are not captured by independent transaction classifiers. These findings support the integration of graph neural network architectures into anti-money laundering systems to enhance sanction-linked detection capabilities in complex financial networks.

Factors influencing youth involvement in the bodaboda transport business in Dodoma City, Tanzania

Titus Tossy — 2026-02-27

This research was conducted in two designated wards, specifically Miyuji and Mnadani, in Dodoma city, with an emphasis on the determinants of youth participation in the Bodaboda transportation enterprise, examining socioeconomic and demographic variables, as well as other motivational factors. This investigation used a sample of 175 participants and employed a cross-sectional research design to collect primary data. Data collection methodologies incorporated interviews and documentary analysis. The gathered data were subjected to both descriptive and inferential statistical analyses. The findings indicated that marital status and household size significantly influence youth engagement in the Bodaboda sector. In contrast, age, educational attainment, breadwinner status, and cohabitation with parents exhibited negligible influence on youth participation in the Bodaboda enterprise. Furthermore, sources of income and employment status significantly affected youth involvement in the Bodaboda business. In contrast, access to credit, initial capital requirements, and Bodaboda loans had minimal influence on youth engagement in this sector. Additionally, activities such as using WhatsApp, engaging with social media, the type of mobile device youths use, watching television, reading newspapers, and listening to the radio were significantly correlated with youth participation in the Bodaboda enterprise. Consequently, it is recommended that the central government establish supportive programs to enhance youth access to education and facilitate their transition from the Bodaboda sector to more formalized business ventures. The government should formulate policies and initiatives to combat poverty by improving educational access and financial resources, investing in youth skill development programs, strengthening job security policies, and promoting youth entrepreneurship.

Ethnopharmacological insights into tropical medicinal plants: biodiversity, bioactive compounds, and therapeutic potential for modern drug discovery

Umar Aminu Mohammed — 2026-02-27

Recent scholarly debates on equitable bioprospecting, intensified since the 2010 Nagoya Protocol, have exposed a critical gap in linking tropical plant biodiversity to validated pharmacological outcomes, particularly where habitat degradation accelerates species loss. Hitherto, ethnobotanical knowledge from the Amazon, Congo, and Southeast Asian basins regions dominated by Asteraceae, Rubiaceae, and Fabaceae has informed drug leads, yet systematic validation lags. This review, adhering to PRISMA-ScR standards, screened a lot of peer-reviewed records (2015–2026) via dual-independent extraction, yielding several studies on plant species with medicinal properties. Indigenous applications, such as Artemisia annua against malaria or Momordica charantia for glycemic control, find partial backing from in vitro assays and select rodent models. Alkaloids like quinine (Cinchona spp.), terpenoids including artemisinin, alongside flavonoids and phenolics, disrupt cancer proliferation, thwart microbial resistance, and mitigate neurodegeneration, evidence drawn from cytotoxicity screens, antimicrobial MICs, and sparse phase I trials. Paradoxically, synergies among co-occurring metabolites enhance efficacy, even as dose-dependent toxicities undermine safety profiles. These patterns challenge reductionist models of single-compound pharmacology, refining instead polyvalent synergy theories contingent upon extraction fidelity. Notwithstanding ethical frictions in benefit-sharing and intellectual property disputes, sustainability threats from anthropogenic deforestation loom large. Bridging ethnobotanical assertions to mechanistic proof demands interdisciplinary conservation pharmacology. Urgent action secures these reservoirs for novel agents.

Potential of Cupressus lusitanica sawdust for pellet production using natural binding agents

Tegene Tantu — 2026-02-27

This study explored the potential of Cupressus lusitanica Sawdust for the production of pellets from carbonized sawdust using different natural binding agents (molasses, starch flour, fruit waste, and waste paper). The impacts of particle size and the type of binding agent used on the fuel qualities of pellets were investigated. The experimental results highlight that pellets produced from waste paper and starch flour binders exhibit high calorific values, high fixed carbon, and low moisture content. In contrast, molasses and fruit waste binders lower the fixed carbon and calorific value of pellets. As a result, the maximum calorific values were obtained using starch flour and waste paper, with respective values of 7052 and 7046 (cal/g). Maximum fixed carbon contents were 79.5% and 76.67% for waste paper and starch flour bonded pellets. Fruit waste and molasses binders result in lower calorific values, with respective values of 4831 cal/g and 5034 cal/g respectively. Pellets produced from fruit waste and waste paper showed lower ash contents of 1.53% and 1.67% respectively, indicating their environmental advantages. Therefore, starch flour, waste paper, molasses, and fruit waste are effective binders for biomass pellet production with improved quality.

Qualitative and quantitative screening of coprophilous fungi for cellulase production

Olusegun Richard Adeoyo — 2026-02-27

Filamentous fungi, especially the herbivore dung-inhabiting (coprophilous), are widely explored for cellulase production owing to their ability to secrete abundant extracellular enzymes, rapid growth, and adaptability to diverse substrates. Microbial enzymes are favoured over plant and animal-derived enzymes due to their ease of production, cost-effectiveness, and genetic manipulation potential. This study isolated, identified, and determined cellulase activity of fungal species from cow dung. Three composite cow dung samples were collected from Ikare-Akoko, Oka-Akoko, and Supare-Akoko. The macroscopic and microscopic features of fungal isolates were used to identify them. Screening for cellulase-producing fungi was assessed using the carboxymethyl cellulose (CMC) agar plate screening method. Cellulase is produced by submerged fermentation, quantified by dinitrosalicylic acid (DNSA) enzyme assay methods, and all experiments were performed in triplicate. The results revealed that the sample from Supare (SUP) had the highest fungal counts of 2.9 × 10⁵CFU/g, followed by Oka-Akoko (2.7 × 10⁵CFU/g), and the lowest fungal count of 1.8 × 10⁵CFU/g was obtained from Ikare-Akoko. A total of nineteen (19) fungal species belonging to 12 genera (Acremonium, Alternaria, Aspergillus, Byssochlamys, Candida, Curvularia, Eurotium, Fusarium, Geomyces, Penicillium, Rhizopus, and Trichoderma) were identified. Thirteen (13) fungal species demonstrated cellulolytic activity with varying efficiencies. Alternaria tenuissima had the highest cellulase activity of 5.79 U/mL, followed by Aspergillus fumigatus (5.31 U/mL) and Penicillium sp (5.14 U/mL). Moderate activity was observed in Trichoderma harzianum, Curvularia geniculata, and Byssochlamys nivea, while Aspergillus glaucus showed the least activity (0.88 U/mL). This study revealed that cow dung harbours diverse cellulolytic fungi with cellulase-producing capacity. Therefore, these fungi are promising candidates for sustainable cellulase production in biofuel generation, waste management, and related biotechnological applications.