RP-Department of Computing & Information Technology

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A Hybrid Machine Learning Model for Detection of Fake Profile Accounts on Social Media Networks
(International Journal of Engineering Research & Technology (IJERT), 2024-11) Karamu, Morris Bosire; Araka, Eric Nyambariga
Most of us nowadays are drawn and motivated to adamantly adopt and get obsessed in every new tech-trend emerging within the social media culture that is mostly virtual, through this there is fast worldwide communication out-reach; on-screen relationships and mediated reality scenarios all over, receiving and sending everything is digital and easy to access. This has drawn the attention and motivation for this research. For instance, this massive interconnection comes with a critical challenge: the ever-growing problem of fashioning fake profile accounts. These dishonest entities, falsely reflecting themselves in auto-scripts, human imitation accounts running on bots and automatically hiding behind a masked user-identity of genuine users, can bring a substantial damage to a wide-range of connections on the internet. This encompass spam and unwanted messages to creation of fake profile accounts that lead to a variety of negative penalties such as internet being used for immoral political agendas, manipulative and misleading information to interrupt the public communication changing public opinion and subverting online communication, political processes, public health initiatives or even financial markets. Social media platforms have become breeding ground for counterfeit profiles, calling for the need for improved and reliable detection and mitigation techniques of fake profiles. This research involves the assessment and development Machine Learning model which in-turn can reveal accurately bogus social media accounts with possible mitigation methods.
A Multi-Agent Monitoring System for Computer Networks
(International Journal of Computer and Organization Trends, 2025-03) Harrison, Amwayi; Mutua, Abraham
In today's business landscape, reliable network infrastructure is essential for uninterrupted operations. As networks increase in complexity, effective monitoring systems become crucial to ensure device performance and availability. This study presents a multi-agent-based system for monitoring computer network devices, utilizing autonomous agents to gather data through the Simple Network Management Protocol (SNMP). The proposed solution addresses scalability and network congestion challenges often seen in centralized monitoring systems by leveraging Apache Kafka to distribute and manage monitoring data efficiently while autonomous agents handle data collection, thereby reducing latency and minimizing network load. The research first examines existing multi-agent applications that leverage SNMP agents, identifying their limitations before introducing a novel model that integrates SNMP agents with Apache Kafka to facilitate scalable data ingestion. The system's performance was tested in a simulated environment, and significant enhancements in scalability and efficiency were observed for real-time monitoring. The findings conclude that combining multi-agent systems with Apache Kafka offers a robust framework for efficient, real-time network monitoring, with improved scalability and reduced latency compared to traditional centralized models.
An Ensemble Feature Selection Model with Machine Learning Model for Detection of Fraudulent Motor Vehicle Insurance Claims.
(TIJER-International Research Journals(TIJER), 2024-04) Wambu, Anthony Mwiti; Araka, Erik
Insurance companies are continuously inventing new competitive insurance products in order to enlarge their market share. This has continuously created opportunities for insurance fraud as well. In motor vehicle insurance, fraudulent claims continue to be a big challenge despite the insurance industry having vast amounts of motor vehicle insurance policy data and claim’s data. Proper analysis of this data can help to develop a more efficient way of detecting fraudulent claims. The challenge is how to extract insightful information and knowledge from this data since by their nature insurance datasets contain noisy features or subsets of data which are of poor quality. In order to achieve an effective machine learning model, one needs to choose the right set of features of data in the pre-processing step. Including noisy and less important features has proven to affect the performance of most of the existing machine learning models being used in the insurance companies. With aid of proper and effective feature selection techniques machine learning models that uses only relevant features of data can be developed in order to detect fraudulent insurance claims effectively. These models can be employed in insurance industry to aid in detecting fraudulent motor vehicle insurance claims. This will result in reduction of loss adjustment expenses and also improve customer satisfaction. Although there exist several other methods and ways of data preprocessing this study employed an ensemble multiple filter feature selection method. This study involved development of motor vehicle fraud detection model using multiple algorithms whose results were combined by use of a voting method.
Analysis of Determinants of M-Commerce Adoption by Online Consumers
(Center for Promoting Ideas, USA, 2014) Gitau, L.; Nzuki, D. M.
M-Commerce is the making of payments for products and services through the use of mobile devices. The proliferation of mobile devices has resulted to into substantial growth of M-commerce. This is as a result of anytime anywhere connectivity, low cost of business, increased new sales avenues and customer loyalty. But even with the high penetration rate of Mobile phones, a relatively low adoption rate of M-Commerce has been observed in the developing countries. This study provides the theoretical underpinning for various interventions to promote M-Commerce Adoption. The study uses the literature review to identify the factors which influence the adoption of M-Commerce by consumers. The results from this study will be useful to m-commerce companies in formulating appropriate marketing strategies, as well as developing appropriate applications that address the needs and resources of various stakeholders. The outcome of this study will guide companies that offer MCommerce related products in the selection of digital products and in pursuance of future commercial opportunities. The finding of this study recommends that the government should set up legislation that would ensure customer security in order to enhance trust and hence enhance M-Commerce adoption.
Big data and personal information privacy in developing countries: insights from Kenya
(frontiers, 2025) Masinde Johnson; Mugambi Franklin; Muthee Daniel Wambiri
The present study examined the correlation between big data and personal information privacy in Kenya, a developing nation which has experienced a significant rise in utilization of data in the recent past. The study sought to assess the effectiveness of present data protection laws and policies, highlight challenges that individuals and organizations experience while securing their data, and propose mechanisms to enhance data protection frameworks and raise public awareness of data privacy issues. The study employed a mixed-methods approach, which included a survey of 500 participants, 20 interviews with key stakeholders, and an examination of 50 pertinent documents. Study findings show that the regulatory and legal frameworks though present are not enforced, demonstrating a gap between legislation and implementation. Furthermore, there is a lack of understanding about the risks posed by sharing personal information, and that more public education and awareness activities are required. The findings also demonstrate that while people are prepared to trade their personal information for concrete benefits, they are concerned about how their data is utilized and by whom. The study proposes the establishment of a National Data Literacy Training and Capacity Building Framework (NADACA), that should mandate the training of government officials in best practices for data governance and enforcement mechanisms, educate the public on personal data privacy and relevant laws, and ensure the integration of data literacy into the curriculum, alongside the provision of regular resources and workshops on data literacy. The study has significant implications for policymakers, industry representatives, and civil society organizations in Kenya and globally.
Critical Literature Review on Current State-of-the Art in Predicting Students’ Performance using Machine Learning Algorithm in Blended Learning Environment
(AJOEI, 2023) Ofori, Francis; Matheka, Abraham; Maina, Elizaphan
Background of the study: Predicting and analyzing the performance of the student in a blended learning environment is important to help educators identify poor performing students and improve their academic score. Meanwhile, achieving accurate predictions require selecting machine learning techniques that can produce optimum score. However, there seems to be no critical literature review on current state of art in predicting students’ performance using machine learning algorithms in blended learning environment. Methodology: This critical literature review focuses on, studies on the current state of the art in predicting students’ performance in the blended learning for past 10 years, sources of dataset used by various authors and the machined learning algorithm with high prediction accuracy. Findings: Naïve Bayes was the most frequently used algorithm for predicting students’ performance. Authors mostly used online data for their student’s performance prediction. Finally, artificial neural network was found to give higher prediction accuracy of 98.7%.
Customers Perception on Prior Knowledge of Technology and Its Effect on Usage of Internet Banking in Commercial Banks in Kenya
(Paper Publications, 2015) Waithaka, Stephen Titus; Muthengi, Kilembwa; Nzeveka, Joseph
Internet banking allows banks to provide information and offer services to their customers conveniently using the internet technology. However, studies have shown that customers have perceptions that impact on the uptake and continuous usage of the platform. The purpose of this study is to understand the effect of customer perceptions on usage of internet banking in commercial banks in Kenya. This study used descriptive research design while a stratified random sampling technique was used to select subjects to represent the target population which was made up of 1,837,312 customers of commercial banks within Nairobi County. An estimated 384 respondents were targeted to participate in the study. 272 questionnaires representing a 71% response rate were received and analysed. Based on the findings of the research it was concluded that customers perceptions have an effect on usage of internet banking. Prior knowledge of technology was forund to have an impediment in using internet banking by customers. Not all customers are well versed in using systems used in accessing internet banking- both software and hard ware.
Data Protection in Healthcare Information Systems Using Cryptographic Algorithm with Base64 512 bits
(Journal of the Kenya National Commission for UNESCO, 2024) Muthaura, Agnes K.; Kandiri,John
Due to the recent advancement in technology in Healthcare Information Systems, data leakages at the data level has been on the rise. Therefore, there is need to analyze the existing data protection techniques using cryptographic algorithms in Healthcare systems at the data level. Existing data-level protection techniques that are developed to ensure data-level protection in Healthcare Information Systems lack integration of key security models and database security approaches such as enhanced cryptographic algorithms in the design and development of data protection techniques. In this study, design science research methodology was used to design and develop a cryptographic algorithm with Base64 512 bits to enhance data protection at the data level. Python programming language was used to develop a simulation program for experiment. The performance of the developed algorithm was tested in a healthcare information system. The results were compared with the existing cryptographic algorithms to evaluate encryption and decryption process, strength on brute force attack and plain text vulnerability. The results showed that the developed algorithm with Base64 and fixed length of 512 bits achieved optimal performance. In conclusion, healthcare data is very sensitive and critical thus enhanced cryptographic algorithms are necessary to reduce data leakages at the data level.
Determinants of Mobile Banking Adoption by Customers of Microfinance Institutions in Nairobi County in Kenya
(International Journal of Science and Research (IJSR), 2015) Wamai, John; Kandiri, John M
Mobile technology usage has had various impacts on individuals and enterprises at different levels. Several factors have been sighted by different researchers as contributing either positively or negatively to the adoption of Mobile banking technology. Banks have implemented this technology to enable them reach more customers due to its ubiquitous nature and to reduce the cost of putting up new branches in their areas of operations. For this effort to be felt and for the technology to be implemented effectively, there is need to understand the factors contributing to its adoption by the customers. This study was carried out to investigate the effects of important factors that affect adoption of mobile banking technology by customers of Microfinance Institutions in Nairobi County, Kenya. A sample of 210 customers were selected randomly and the researcher extended the Technology Acceptance Model (TAM) framework. The study found that both perceived usefulness and perceived ease of use positively correlate and affects adoption of mobile banking technology positively. On the other hand, Perceived Risk and Perceived transaction costs were found to have negative correlation with the adoption of mobile banking technology
The Effect of Customers Perception on Security and Privacy of Internet Banking on Its Usage in Commercial Banks in Kenya
(Paper Publications, 2015) Waithaka, Stephen Titus; Muthengi, Kilembwa; Nzeveka, Joseph
Internet banking allows banks to provide information and offer services to their customers conveniently using the internet technology. However, studies have shown that customers have perceptions that impact on the uptake and continuous usage of the platform. The purpose of this study is to understand the effect of customer perceptions on usage of internet banking in commercial banks in Kenya. This study used descriptive research design while a stratified random sampling technique was used to select subjects to represent the target population which was made up of 1,837,312 customers of commercial banks within Nairobi County. An estimated 384 respondents were targeted to participate in the study. 272 questionnaires representing a 71% response rate were received and analysed. Based on the findings of the research it was concluded that customers have perception that have an effect on usage of internet banking. Customers both users and potential, are still apprehensive about the security of internet banking transactions and privacy of their sessions while online. Due to increased phishing, on online scams and frauds perpetrated online customers are reluctant to adopt or continue using internet banking. It is the responsibility of commercial banks to sensitize their customers and assure them that it is safe to access internet banking from both a private and public network. They should provide customers with guidelines on how to safe guard their information and secure their log on credential while using both private and public network
An Enhanced Service Flow Management Scheme for IEEE 802.16 Broadband Wireless Access Systems
(International Journal of Computer Theory and Engineering, 2012-08) Musau, Felix; Kipkorir, Sang; Mwamafundo, Juma Modie
 Abstract—While the protocols have been proposed to support QoS (quality of service) guarantees for a variety of applications, the WiMax/IEEE 802.16 standard does not specify a mandatory scheduling architecture to fulfill stringent QoS requirement for the different classes of traffic. Only the framework is established in the standard which provides an opportunity for developers to design efficient scheduling mechanism to fulfill stringent QoS requirement for the different classes of traffic. The scheduling scheme requires catering for rigorous QoS guarantee for all types of service flows as specified in the standard, enabling fairness and facilitating the traffic of lower priority. In this paper, we propose a Service Flow Management Scheme for the IEEE 802.16 Broadband Wireless Access systems that can provide QOS support that enhances performance through a scheduler that performs optimally and efficient
Enhancing Exploratory Learning Using Computer Simulation in an E-learning Environment: A Literature Review
(Center for Open Access in Science, 2020) Kanyaru, Paul; Maina, Elizaphan
Computer simulation has been shown to elicit exploratory behavior and creativity in learners. Various researches have indicated that during an exploratory learning process students can acquire knowledge either through inquiring or exploring an open learning environment. Further, the research shows that as opposed to instruction-based learning, exploratory learning is mainly based on self-motivation by learners. Therefore, computer simulation when used to enhance exploratory learning concept especially in an e-learning platform, has been seen to achieve the learning objectives as explained by Bloom taxonomy. In this regard, computer simulation has been seen to help learners conceptualize important concepts especially in science subjects. Additionally, the use of simulation is regarded as an aid to improving understanding of various concepts as well, as helping increase breadth of knowledge.
Enhancing Service Delivery in Public Sector by Leveraging on Digital Transformation: A Case of Kiambu Level Five Hospital
(Reviewed Journal of Social Science & Humanities, 2024-09) Wachira, Purity Wamuyu; Kandiri, John
In the publ ic sector, the main goal of service delivery is to make sure that people can get to and use important tools and services in a way that meets their needs. Service delivery is very important in the healthcare field, especially in state hospitals, because it has a direct effect on how well patients do and on the health of the people as a whole. Digital change has a big effect on service delivery because it lets companies use flexible organizational structures and connect digital business communities. The goal of this study was to look into how going digital has changed the way services are provided at Kenya's Kiambu Level 5 hospital. The study looked at how customer relationships, growing skills, and constant improvement affect the digital change process. Resou rce - based view, identify, distinguish, connect, and modify theories, as well as dynamic capability theories, were used to guide the study. Based on a detailed study approach, the study was carried out. The target group was made up of 282 Kiambu Level 5 hos pital workers. A group of 165 individuals was used as a sample. Structured surveys and an interview plan were used to gather the data. The study looked at how accurate and reliable research tools were. Descriptive statistics and regression analysis were us ed to look at quantitative data. Content analysis, on the other hand, was used to look at qualitative data. A strong link (r=0.822, p<.001) was found between the digital change factors and service performance. The study found that the three digital transfo rmation factors can explain about 66.9% of the differences in service performance. Continuous growth (p<.001) and customer interaction (p<.001) were both important. The study found that going digital has a big and good impact on service delivery at Kenya's Kiambu Level 5 Hospital, mainly through bettering relationships with customers and always making things better. The study said that Kiambu Level 5 Hospital should use digital tools to try to keep customers they already have. It was also suggested that the hospital spend money on digital technology to make the hospital more productive and find technology that guarantees on-ti me delivery of health services.
Evaluating Cybersecurity Threats, Mitigation Measures, and Key Determinants of Security for Kenya’s eCitizen Platform
(Kenyatta University, 2025-11) Sitienei, Jennifer Chebet
This research explored the cybersecurity threats on security of Kenya's eCitizen platform, a crucial digital platform for accessing government services in the face of rising global cyber threats. The study focused on protecting sensitive governmental data, with objectives that included analyzing cybersecurity threats, evaluating mitigation measures, assessing the effectiveness of cybersecurity measures put in place and providing actionable recommendations. The literature review thoroughly examined each objective through the lens of established cybersecurity theories such as defense in Depth, Zero Trust, and the Integrated Theories of Cybercrimes. The research utilized a descriptive research design with a case study approach and multi-stage sampling technique to obtain a sample of 216 participants. Primary data was collected using questionnaires and interview schedules. SPSS 24 software was used to compute descriptive statistics and inferential statistics. Thematic analysis was also used to analyze qualitative data from open-ended questions and presented along quantitative data. The results from questionnaire and tools were triangulated to obtain a thick descriptionThe Descriptive statistics indicated that Phishing was seen as the most severe threat, Hacking was also ranked high in severity, Malicious software and Denial of Service attacks were viewed as moderately severe, Insider threats and cyberstalking were considered less severe. And regarding the cybersecurity measures on eCitizen platform the results revealed that User education and awareness programs, Regular security audits, Firewalls and intrusion detection systems were rated moderately effective while Data backup and recovery measures were rated lower, Access control measures, Encryption was rated the highest at 3.65, indicating a strong consensus on its critical role in data protection. The regression model revealed that predictors such as cybersecurity threats, security measures, and effectiveness factors are significantly correlated with the eCitizen platform’s security. The conclusions emphasized the need for improved governance, enhanced risk management practices, updated legislation, and increased international cooperation to address evolving cyber threats effectively. The study recommends for proactive measures, transparent communication, and collaborative efforts across sectors to improve security and public confidence in digital services.
Evaluation of intelligent grouping based on learners’ collaboration competence level in online collaborative learning environment
(Athabasca University, 2016-02) Maina, E.M.; Oboko, R.; Waiganjo, P.W.
In this paper we explore the impact of an intelligent grouping algorithm based on learners’ collaborative competency when compared with (a) instructor based Grade Point Average (GPA) method level and (b) random method, on group outcomes and group collaboration problems in an online collaborative learning environment. An intelligent grouping algorithm has been added in a Learning Management System (LMS) which is capable of forming heterogeneous groups based on learners’ collaborative competency level. True experiment design methodology was deployed to examine whether there is any association between group formation method and group scores, learning experiences and group problems. From the findings, all groups had almost similar mean scores in all group tests, and shared many similar group collaboration problems and learning experiences. However, with the understanding that GPA group formation method involves the instructor, may not be dynamic, and the random method does not guarantee heterogeneity based on learner’s collaboration competence level, instructors are more likely to adopt our intelligent grouping method as the findings show that it has similar results. Furthermore, it provides an added advantage in supporting group formation due to its guarantee on heterogeneity, dynamism, and less instructor involvement.
Facilitating Group Learner Participation using Intelligent Agents in Collaborative M-Learning
(IEEE, 2018) Njenga, Stephen; Oboko, Robert; Omwenga, Elijah; Maina, Elizaphan
Most Leaning Management Systems provide a facility for online group discussions. Grouping members together does not give a surety of their participation in those online discussions. However, intelligent agents can facilitate group participation to motivate members to participate effectively in group discussions leading to enhanced levels of group knowledge construction. This paper discusses an experimental design for evaluating agent-based facilitated group learner participation for online group discussions in mobile learning environments. The experiment uses two treatment groups and one control group. We compared the levels of group knowledge construction amongst the three groups. The findings showed improved levels of group knowledge construction in the treatment groups compared to the control group. Thus, we recommend the use of intelligent agents in facilitating group participation and subsequently improving the group knowledge construction in collaborative m-learning.
Gamification Model for E-Learning Platforms
(IST-Africa, 2019) Kamunya, Samuel; Maina, Elizaphan; Oboko, Robert
The use of gamification in education has been viewed as an innovative approach to introduce benefits of games in a non gaming context. Instructively, for a successful gamification process in learning, motivational theories and behavioral outcomes for the learner have to be incorporated in design framework. Observably gamification projects particularly within the education domain for e-learning platforms have encountered challenges key amongst them, emanating from lack of appropriate gamification design framework. Subsequently the study sought through systematic literature review to investigate types of gamification design frameworks. 16 design frameworks were evaluated and only 2 frameworks were designed for gamification within an e-learning environment. However the two frameworks did not address motivational affordances, behavioral Outcomes and evaluations rigor. In view of this the study proposes a framework identifying games elements as motivational affordances that influence behavioral outcome of the learner
Gamified Blood Donors System Based on Intelligent Agents
(OJIT, 2021) Karanja, James Mugi; Njoroge, Harrison
The population of the country of Kenya is drastically increasing thus causing the number of possible blood donors to rise. Despite this, the blood collected and stored in most blood banks is not enough to cater for the huge demand. The demand has been due to increase of number of accidents experienced in the country and the advancement in medical procedures which calls for organ transplant and blood transfusion. Even though systems have been developed which can connect the donors and recipients and location tracking, most people are dying because they don`t get this vital commodity in good time. The process of donating blood has not been enticing. There is nothing that prompts a person to donate blood. This call for developing a gamified blood donor management system based on intelligent agents so as to increase the number of donors and keep the system performance at optimal level. The project adopts Goal-Oriented Methodology in the system development process. Two agents are developed: donors’ agent and the blood admin agent. The intelligent agents help in profiles personalization thus improving the system performance. Gamification technique is implemented in the system so as to increase the traffic of blood donors interacting with the system and participating in the donation exercise. This increase the number of blood donors hence enough blood is collected to cater for the huge demand
Hospital Information Systems Capability and End-User Satisfaction in Hospitals of Nairobi County, Kenya
(IAJIST, 2018) Omune, Onyando George; Kandiri, John M.
Hospitals in Nairobi County, Kenya continue to automate their processes to improve service delivery to their clients by implementing hospital Information Systems (HIS). As studies have revealed, end user satisfaction plays an important role in information systems acceptance, and ultimate success. The study focused on HIS capability and how it affects end user satisfaction in the hospitals by use of descriptive and observations techniques. The scope of this study was hospitals in Nairobi County, Kenya with bed capacity of at least 100 and had used HIS for a period of not less than a year. Stratified sampling method was preferred for sampling of study respondents from the selected ten hospitals of Nairobi County that met inclusion criteria and simple random sampling technique, to select respondents respectively. Semi structured questionnaires were used to collect primary data from a population of 374 respondents. The data collected was analyzed quantitatively using descriptive statistics comprising of the mean, standard deviation and P-values. Statistical Package for Social Sciences (SPSS) version 22, Microsoft Office Excel 2013 and descriptive statistics were the main tools used to analyze the data. The results have shown that systems quality, information quality and service quality of HIS positively affect end user satisfaction.
How Perceived Usefulness of Mobile Banking Affects Financial Performance of Commercial Banks in Nairobi City, Kenya
(Journal International of Business Management, 2024-07-24) Munyasia, Rose Nelima; Waithaka, Stephen Titus
he shift from traditional branch banking to mobile banking has seen banks employ mobile banking. Use of mobile banking seeks to attract new customers while retaining existing ones minimize operational and management costs and sustaining competition. The Kenyan banking sector has seen significant advances in technology, but investment in technology is expensive and still not monetized to contribute to financial performance outcomes. This study sought to assess how perceived usefulness (PU) on mobile banking affected the financial performance of commercial banks in Nairobi County, Kenya. The study was anchored on technology acceptance model (TAM). The survey was based on descriptive research design and targeted 200 customers from the top-five rated banks on performance of mobile banking. The sample size was 133 after applying the Yamane formula and these respondents filled the questionnaire. The quantitative data was analyzed using descriptive, correlation and regression analysis. The descriptive analysis results show that perceived usefulness had mean score of (M=3.94) and financial performance (M=4.191). The correlation analysis show that perceived usefulness was closely associated to financial performance as r = 0.699 and the two variables were positively and significantly related based on regression beta coefficient of β=.545. The findings showed that 62.9% of financial performance was influenced by perceived usefulness of mobile banking application. The study concluded that financial performance with aspects like increased customer numbers, profit margins and cash flows was improved by perceived usefulness of mobile banking. The study recommended upgrading of the mobile banking apps so as to perform services such as financial transactions, speedy processing of transactions and provide multiple services to users

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