Undergraduate Project (UG)

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End date: 2024Subject: search.filters.subject.Nigeria

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    INFLUENCE OF ARTIFICIAL INTELLIGENCE ON SOCIAL MEDIA POLITICAL CAMPAIGN AMONG POLITICAL PARTY MEMBERS IN OFFA
    (2024) ABUBAKAR, Moronranti Khadijah
    The study examined the influence of Artificial Intelligence on social media among political party members in Offa. Artificial Intelligence (AI) has become increasingly prevalent in various aspects of our lives, including politics. The objectives of this study are (i) to assess the level of awareness of AI for social media political campaigns among political party member in Offa. (ii) to investigate the perception of political party members in using Artificial Intelligence for social media political campaign. (iii) to examine the influence of Artificial Intelligence on social media political campaigns among political party members in Offa. This study made use of Cross-sectional research design and Self-administered questionnaire was administered to a sample size of three hundred and seventy-seven political party member using 20961 populations. Questionnaires were used to collect data which was analysed with statistical method indicating frequency, percentages, mean and standard deviation. The study found out that there is low awareness about using AI in social media political campaign and as a result there is low perception of AI in campaign and limited influence on AI on social media political campaign. Lastly, the study therefore recommends that; there should be effective and thorough awareness on the use of AI role in motivating citizen to participate in politics,set clear goal and objectives for their social media campaign to identify areas where AI can be most useful, choose AI tools that suit their needs considering factors like ease of use, cost and technical support, train their campaign teams to use AI tools effectively and interpret AI- generated insights, focus on ensuring high-quality data as AI algorithm’s effectiveness depends on the data they analyze.
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    AWARENESS AND ADOPTION OF ARTIFICIAL INTELLIGENCE IN NEWS PRODUCTION AMONG JOURNALISTS IN KWARA STATE
    (2024) IBITOYE, Faith
    The integration of Artificial Intelligence (AI) in journalism is transforming news production processes globally. However, in developing regions like Kwara State, Nigeria, the adoption of Artificial Intelligence based tools among journalists, remains limited due to various factors such as lack of awareness, limited resources, and ethical concerns. This study aimed to investigate the awareness and adoption of AI in news production among selected journalists in Kwara State. The research employed a cross-sectional quantitative design, utilizing a structured questionnaire to collect data from a sample of 139 journalists affiliated with the Nigerian Union of Journalists (NUJ) in Kwara State. Stratified random sampling was used to ensure representation across different media types. Data were analysed using descriptive statistics, including frequency distributions, percentages, means, and standard deviations. Findings revealed varying levels of awareness and adoption of Artificial Intelligence based tools among journalists in Kwara State. While respondents demonstrated high awareness of AI’s potential in production and data analysis, knowledge of specialized applications like content creation and personalization was lower. Perceived benefits included increased efficiency and improved real-time updates, while challenges encompassed high implementation costs and lack of technical skills. The study found moderate adoption of AI tools for fact-checking and assisted writing, but lower usage rates for automated content generation and news personalization. In conclusion, AI integration in journalism in Kwara State is in a transitional phase, with some technologies being more readily embraced than others. To facilitate broader adoption, it is recommended that media organizations and educational institutions prioritize AI skills development through specialized training programs tailored to the local context. Additionally, efforts should be made to address cost barriers and develop comprehensive ethical guidelines for AI use in journalism.
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    ENHANCING EFFICIENCY OF ACCOUNTING INFORMATION SYSTEM AND NON-FINANCIAL PERFORMANCE IN THE AGRO-ALLIED COMPANIES IN NIGERIA USING AI.
    (2024) AKANNI MUHAMMED TOHA OLATUNBOSUN
    In this study, we assessed the effectiveness of nonfinancial performance measures and Accounting Information System (AIS) in Agro-allied Industries in Nigeria using Artificial Intelligence (AI). The efficiency of accounting information systems in tracking accounting Operations in the performance of Agro-allied enterprises has not been thoroughly demonstrated Since the debut of these systems. Thus, the goal of this study is to investigate the effects of Accounting Information System (AIS) on the Agro-allied companies and non-financial and Financial performance in Nigeria. An emerging technology in agriculture is artificial intelligence. In reality, tools and equipment Powered by artificial intelligence have raised the bar for the agriculture industry. This innovative Technology has enhanced instantaneous monitoring, processing, and collection as well as crop productivity. The most current computerized structures that use drones and remote sensing have significantly improved the Agro-based sector. Furthermore, through providing cyclic data on yield status during study periods at varied degrees and for diverse characteristics, remote sensing has the potential to promote the development of farming technologies aimed at overcoming this primary challenge. Different computer-supported, high-tech structures are developed to identify various central factors, including crop quality, yield recognition, plant detection, and several other techniques. This paper presents the methods used to analyze the data gathered in order to increase output, anticipate potential risks, and lighten the work load for growers.
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    ENHANCING EFFICIENCY OF ACCOUNTING INFORMATION SYSTEM AND NON-FINANCIAL PERFORMANCE IN THE AGRO-ALLIED COMPANIES IN NIGERIA USING AI.
    (2024) AKANNI MUHAMMED TOHA OLATUNBOSUN
    In this study, we assessed the effectiveness of nonfinancial performance measures and Accounting Information System (AIS) in Agro-allied Industries in Nigeria using Artificial Intelligence (AI). The efficiency of accounting information systems in tracking accounting Operations in the performance of Agro-allied enterprises has not been thoroughly demonstrated Since the debut of these systems. Thus, the goal of this study is to investigate the effects of Accounting Information System (AIS) on the Agro-allied companies and non-financial and Financial performance in Nigeria. An emerging technology in agriculture is artificial intelligence. In reality, tools and equipment Powered by artificial intelligence have raised the bar for the agriculture industry. This innovative Technology has enhanced instantaneous monitoring, processing, and collection as well as crop productivity. The most current computerized structures that use drones and remote sensing have significantly improved the Agro-based sector. Furthermore, through providing cyclic data on yield status during study periods at varied degrees and for diverse characteristics, remote sensing has the potential to promote the development of farming technologies aimed at overcoming this primary challenge. Different computer-supported, high-tech structures are developed to identify various central factors, including crop quality, yield recognition, plant detection, and several other techniques. This paper presents the methods used to analyse the data gathered in order to increase output, anticipate potential risks, and lighten the work load for growers.
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    COMPARATIVE ANALYSIS OF PREDICTIVE POWER OF TRADITIONAL ECONOMETRICS AND A.I BASED MODELS OF EXCHANGE RATE IN NIGERIA
    (2024) ALYELESO ABDULWARITH OLUSHOLA
    This paper presents a comparative analysis of the predictive power of traditional econometric models and AL- based models in forecasting exchange in Nigerian. The exchange is one of the macroeconomics variable which are interest rate, inflation. The traditional models including Auto regression integrated moving average (ARIMA) Where the AL MODELS including artificial neutral network (ANN), GRU, LSTM model to model and predict the real exchange data. The purpose of the study is to show the effectiveness and compare the best predictive for forecasting the exchange in Nigerian. The paper evaluates the performance of each model in term accuracy, robustness and computational efficiency. The data under was collected from ranging from 1997 to 2023 and the data base was collected by Nigeria statistic s bulletin. This study split the data set into training and testing and applied all stated models. The study selects a model that meets the key performance indicators (KPI) criteria .this model was selected as the best candidate model to predict the behavior of the exchange rate data.