Journal of Applied Science, Information and Computing最新文献

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Engaging Communities In Renewable Energy Projects For Sustainable Development 让社区参与可再生能源项目,促进可持续发展
Journal of Applied Science, Information and Computing Pub Date : 2024-01-13 DOI: 10.59568/jasic-2023-4-2-06
Afam Uzorka, Ademola Olatide Olaniyan, V. F. Olubusayo
{"title":"Engaging Communities In Renewable Energy Projects For Sustainable Development","authors":"Afam Uzorka, Ademola Olatide Olaniyan, V. F. Olubusayo","doi":"10.59568/jasic-2023-4-2-06","DOIUrl":"https://doi.org/10.59568/jasic-2023-4-2-06","url":null,"abstract":"The pressing need to battle climate change and make the shift to sustainable energy sources has led to the emergence of renewable energy projects as critical solutions. While reducing the negative environmental effects of conventional fossil fuels, these programs hold up the prospect of clean, plentiful energy. However, the effective adoption of renewable energy into our world's energy system involves more than simply technological improvements; it also calls for the support and active participation of local communities. This study examines the value of community involvement and evaluates measures to strengthen local community to support renewable energy projects. With an emphasis on social acceptance, customized project design, and economic potential, the significance of incorporating local communities in the planning, implementation, and management of renewable energy projects are examined. The examination of capacity-building projects also reveals information about education and training activities, community leadership growth, technological transfer, and knowledge exchange. The advantages of combining resources, encouraging innovation, and promoting supportive policies are highlighted in the collaborative partnerships between governments, NGOs, business organizations, and local communities. Renewable energy projects may genuinely become engines for sustainable development by embracing community involvement and capacity-building, meeting local needs and aspirations while paving the path for a greener and more resilient future","PeriodicalId":167914,"journal":{"name":"Journal of Applied Science, Information and Computing","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140509063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Enhanced Student Retention In Open And Distance Education Through Effective Academic Performance Model Using Naïve Bayes And K-Nearest Neighbor Machine Learning Algorithms 利用 Naïve Bayes 和 K-Nearest Neighbor 机器学习算法建立有效的学业成绩模型,提高远程开放教育的学生保留率
Journal of Applied Science, Information and Computing Pub Date : 2024-01-13 DOI: 10.59568/jasic-2023-4-2-04
Ezeanya C. U, Onyeji E. M, Ejimofor I. A
{"title":"Enhanced Student Retention In Open And Distance Education Through Effective Academic Performance Model Using Naïve Bayes And K-Nearest Neighbor Machine Learning Algorithms","authors":"Ezeanya C. U, Onyeji E. M, Ejimofor I. A","doi":"10.59568/jasic-2023-4-2-04","DOIUrl":"https://doi.org/10.59568/jasic-2023-4-2-04","url":null,"abstract":"Improving student performance in an academic pursuit is one of the key concerns of institutions especially open and distance learning institutions where learners are separated from the institution by geographical region. The current observation of low-quality graduates from colleges and universities, particularly in open and distance learning, can be attributed to the lack of mechanisms that could help administrators at universities to forecast the academic achievement of the concerned students in the coming years. The goal of data mining in education is to create models, algorithms, and techniques for analyzing information gathered from learning environments to comprehend and enhance the learning process. The goal of this research is to identify patterns in the measures of academic achievement and how they relate to admission, high school, and personal information about the students. These findings can serve as a solid basis for customizing and enhancing the curriculum for open and distance learning to better suit the needs of individual students. Also, the research work identified factors that had a crucial influence on overall students’ performance. Hybridizing Naïve Bayes and K-Nearest Neighbor were used as Classifiers to develop a model for predicting the performance of students. The new model which is the hybridized model (combined Naïve Bayes and K-Nearest Neighbor) predicts better results than individual Naïve Bayes and K-Nearest Neighbor algorithms which shown itself as the best prediction and classification model.","PeriodicalId":167914,"journal":{"name":"Journal of Applied Science, Information and Computing","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140509141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Lecturers Perception Of Plagiarism Among Undergraduates In Nigeria 讲师对尼日利亚大学生抄袭行为的看法
Journal of Applied Science, Information and Computing Pub Date : 2024-01-13 DOI: 10.59568/jasic-2023-4-2-05
Iyanu Omotunde Oluwatobi, Abigail Ajie Ifeoma, Mayowa-Adebara Okeoghene, Loveth Ogoegbulam
{"title":"Lecturers Perception Of Plagiarism Among Undergraduates In Nigeria","authors":"Iyanu Omotunde Oluwatobi, Abigail Ajie Ifeoma, Mayowa-Adebara Okeoghene, Loveth Ogoegbulam","doi":"10.59568/jasic-2023-4-2-05","DOIUrl":"https://doi.org/10.59568/jasic-2023-4-2-05","url":null,"abstract":"The advent of the internet and the ensuing free access to increasingly available information resources and possibilities for students’ ‘copying and pasting’ text from online documents has raised so much concern. There is therefore a growing need for lecturers to address the underlying causes. Thus, this study examines faculty perception of plagiarism among Undergraduates. The study adopted a survey research design. A simple and total enumeration sampling techniques was adopted to cover all the entire lecturers in the faculty of education, Federal University Oye-Ekiti (FUOYE). The instrument use for data collection was the questionnaire titled “Faculty Perception of Plagiarism among Undergraduates’’ (FPPU). Reliability and validity test was conducted on the instrument. A total of 63 copies of questionnaire (97%) were returned and found usable. Data collected were analyzed with the use of descriptive analysis. The findings shows that the reasons for plagiarism among undergraduates includes students laziness (mean=3.44), easy access to materials via the internet (mean=3.27) and not understanding the rules of referencing (mean= 3.27). However, lecturers perception of plagiarism among undergraduates indicates that undergraduates copying of few paragraph of an essay from books without citation (mean= 3.48). Furthermore, lecturers put up some strategies in detecting plagiarize work which includes; using the library shelves to provide evidence (mean =1.84), using specialized plagiarism detecting tools (mean= 1.40), and using online searching tools to provide evidence (mean= 1.38). Consequences for plagiarism among undergraduates include; scoring the students 0% on the assignment (mean= 1.56) and cannot attend classes for a specific amount of time (mean = 1.81). The study therefore, concluded that lecturers understand the offence of plagiarism and therefore have some punitive measures towards the act of plagiarism. It was further recommended that undergraduates should be enlightened adequately on research methodology courses to be taught at various levels of study and handled by experienced lecturers.","PeriodicalId":167914,"journal":{"name":"Journal of Applied Science, Information and Computing","volume":"26 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140509197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Review Of Cluster Under-Sampling In Unbalanced Dataset As A Methods For Improving Software Defect Prediction 非平衡数据集中的集群欠采样作为改进软件缺陷预测方法的综述
Journal of Applied Science, Information and Computing Pub Date : 2024-01-13 DOI: 10.59568/jasic-2023-4-2-03
Sani Abdulhamid, Manjula V. S, Zayyad Musa Ahmed
{"title":"A Review Of Cluster Under-Sampling In Unbalanced Dataset As A Methods For Improving Software Defect Prediction","authors":"Sani Abdulhamid, Manjula V. S, Zayyad Musa Ahmed","doi":"10.59568/jasic-2023-4-2-03","DOIUrl":"https://doi.org/10.59568/jasic-2023-4-2-03","url":null,"abstract":"In many real-world machine learning applications, including software defect prediction, detecting fraud, detection of network intrusion and penetration, managing risk, and medical dataset, class imbalance is an inherent issue. It happens when there aren't many instances of a certain class mostly the class the procedure is meant to identify because the occurrence the class reflects is rare. The considerable priority placed on correctly classifying the relatively minority instances—which incur a higher cost if incorrectly categorized than the majority instances—is a major driving force for class imbalance learning. Supervised models are often designed to maximize the overall classification accuracy; however, because minority examples are rare in the training data, they typically misclassify minority instances. Training a model is facilitated by balancing the dataset since it keeps the model from becoming biased in favor of one class. Put another way, just because the model has more data, it won't automatically favor the majority class. One method of reducing the issue of class imbalance before training classification models is data sampling; however, the majority of the methods now in use introduce additional issues during the sampling process and frequently overlook other concerns related to the quality of the data. Therefore, the goal of this work is to create an effective sampling algorithm that, by employing a straightforward logical framework, enhances the performance of classification algorithms. By providing a thorough literature on class imbalance while developing and putting into practice a novel Cluster Under Sampling Technique (CUST), this research advances both academia and industry. It has been demonstrated that CUST greatly enhances the performance of popular classification techniques like C 4.5 decision tree and One Rule when learning from imbalance datasets.","PeriodicalId":167914,"journal":{"name":"Journal of Applied Science, Information and Computing","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140509462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Utilization Of Blockchain Technology By Updf For Supply Chain Transparency And Traceability Updf 利用区块链技术提高供应链透明度和可追溯性
Journal of Applied Science, Information and Computing Pub Date : 2024-01-13 DOI: 10.59568/jasic-2023-4-2-01
Tabu Ale Sulle, Manjula V. S
{"title":"Utilization Of Blockchain Technology By Updf For Supply Chain Transparency And Traceability","authors":"Tabu Ale Sulle, Manjula V. S","doi":"10.59568/jasic-2023-4-2-01","DOIUrl":"https://doi.org/10.59568/jasic-2023-4-2-01","url":null,"abstract":"To sustain ethical sourcing practices, prevent the sale of counterfeit goods, and increase consumer confidence, organizations must provide transparency and traceability in their supply chains. This case study focuses on the Uganda People's Defense Forces (UPDF) and examines the creation and implementation of a blockchain-based application for improving supply chain transparency and traceability. The main goal is to look into how a blockchain application may enhance supply chain management, decrease corruption, and increase accountability in the UPDF's logistics and procurement procedures. The project will involve designing, creating, and assessing a blockchain-based application specifically catered to the needs and supply chain procedures of the UPDF. In order to provide transparency, immutability, and decentralized control, the app will use blockchain technology to record and verify each stage of the supply chain, from purchase through delivery. The investigation will take into account whether the UPDF has access to the infrastructure and training required to use blockchain technology. A mixed-methods approach will be used to combine quantitative data from transaction logs and supply chain records with qualitative data from stakeholder interviews and observations. The study will evaluate the app's effects on supply chain efficiency, transparency, and traceability as well as any risks and rewards of integrating blockchain technology into the UPDF's supply chain ecosystem. Finally, this technique seeks to advance knowledge of how blockchain technology might enhance supply chain management in governmental and military contexts by examining the adoption of a blockchain-based app within the UPDF's supply chain. The results will advise policymakers, procurement officers, and R researchers on the applicability of blockchain-based apps for boosting supply chain transparency. They will offer insights into the viability, effectiveness, and potential barriers of using blockchain solution","PeriodicalId":167914,"journal":{"name":"Journal of Applied Science, Information and Computing","volume":"23 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140509209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Impact of digitization of sustainable agriculture in Uganda: a case study 乌干达可持续农业数字化的影响:案例研究
Journal of Applied Science, Information and Computing Pub Date : 2023-07-10 DOI: 10.59568/jasic-2023-4-1-01
Ali Nabulongo, V. S. Manjula, Fatou Marega
{"title":"Impact of digitization of sustainable agriculture in Uganda: a case study","authors":"Ali Nabulongo, V. S. Manjula, Fatou Marega","doi":"10.59568/jasic-2023-4-1-01","DOIUrl":"https://doi.org/10.59568/jasic-2023-4-1-01","url":null,"abstract":"Uganda has made outstanding progress in agricultural output, which is crucial for preserving the safety of the country's food supply. The role of technology and digitization in promoting sustainable agriculture practices in Uganda. The case study will focus on various innovative initiatives and solutions that have been implemented in the country to enhance agricultural productivity, reduce environmental impact, and improve livelihoods. By examining the current state of technology adoption in Ugandan agriculture, analyzing successful case studies, and identifying challenges and opportunities, this research will provide valuable insights into the potential of technology and digitization to drive sustainable agricultural development in Uganda.\" Keywords: Agricultural digitization, High-quality agricultural development, skilled labor, a two way fixed effects model, and the threshold effect","PeriodicalId":167914,"journal":{"name":"Journal of Applied Science, Information and Computing","volume":"48 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139360770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Predicting personnel appointment in the Nigerian army using performance records and machine learning techniques 利用业绩记录和机器学习技术预测尼日利亚军队的人员任命情况
Journal of Applied Science, Information and Computing Pub Date : 2023-07-10 DOI: 10.59568/jasic-2023-4-1-04
Joseph Amakurugbonwo, Hashim Ibrahim Bisallah, Israel Musa
{"title":"Predicting personnel appointment in the Nigerian army using performance records and machine learning techniques","authors":"Joseph Amakurugbonwo, Hashim Ibrahim Bisallah, Israel Musa","doi":"10.59568/jasic-2023-4-1-04","DOIUrl":"https://doi.org/10.59568/jasic-2023-4-1-04","url":null,"abstract":"Professionalism and discipline in the Nigerian armed forces have been negatively impacted due to a lack of structured methods of promotion, appointment, and succession in the rank and file of military officers. This lacuna is an attribution of the socio-cultural diversities in Nigeria dispensed through nepotism, favouritism, and ethnicity. Thus, validates the need for pellucid techniques for personnel appointment at the higher echelon based on merit. This paper aims to promote professionalism in the armed forces through a model of seamless human resource processing of enthroning a seamless and transparent culture of succession based on personnel performance records. Supervised learning techniques are adopted for this research given labelled data of 10, 000 records of officers from the rank of major general eligible for appointment as the chief of army staff from the year 1990 to 2002. Relevant features were extracted from the dataset during pre-processing to filter noise, and resampled using sci-kit random over sampler to generate augmented data to balance the target class in order to eliminate algorithmic bias toward the underrepresented class. Three classification algorithms were used comparatively for modelling. The result obtained in terms of accuracy is Logistic regression 84%, decision tree 92%, and random forest 92%. The findings in this research show that our best model random forest will be 92% correct every time prediction is made with a 95 AUC score signifying 95% correctness in distinguishing between the two target classes. This research is the first of its kind and gives room for further improvement with a larger dataset","PeriodicalId":167914,"journal":{"name":"Journal of Applied Science, Information and Computing","volume":"81 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139360654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Revolutionizing legal and business processes of the digital age using blockchain technology 利用区块链技术革新数字时代的法律和业务流程
Journal of Applied Science, Information and Computing Pub Date : 2023-07-10 DOI: 10.59568/jasic-2023-4-1-05
Geoffrey Getare Nyauma, Manjula V. S
{"title":"Revolutionizing legal and business processes of the digital age using blockchain technology","authors":"Geoffrey Getare Nyauma, Manjula V. S","doi":"10.59568/jasic-2023-4-1-05","DOIUrl":"https://doi.org/10.59568/jasic-2023-4-1-05","url":null,"abstract":"Blockchain technology has transcended its origins in cryptocurrency and is now poised to transform various aspects of the legal and business landscape by implementing smart contracts. Smart contracts, which operate on blockchain networks and are self-executing, programmable contracts, have the potential to completely change how agreements are made, carried out, and enforced. In order to shed light on their benefits, drawbacks, and potential future ramifications, this article examines the development of blockchain-based intelligent contracts and their influence on legal and corporate procedures. Traditional methods of managing and carrying out contracts are frequently time consuming, expensive, and prone to disagreements. Blockchain technology's smart contracts provide a decentralized, automated, and impenetrable means of drafting, carrying out, and upholding contracts. This article explains how smart contracts can streamline processes across multiple industries, including finance, real estate, supply chain management, and intellectual property by carefully exploring the technological foundations and real-world use cases of smart contracts. Smart contracts' potential societal and economic effects, such as decreased transaction costs, increased effectiveness, and improved. This article promotes interdisciplinary study and collaboration among legal scholars, technologists, and business professionals to fully realize the promise of blockchain-based intelligent contracts. It ends by imagining a time when smart time when smart contracts are fully incorporated into daily life, revolutionizing the way contracts are established and carried out in the digital age.","PeriodicalId":167914,"journal":{"name":"Journal of Applied Science, Information and Computing","volume":"54 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139361075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Development of a machine learning regression model for accurate sugarcane crop yield prediction, Jinja – Uganda 为准确预测甘蔗作物产量开发机器学习回归模型,乌干达金贾
Journal of Applied Science, Information and Computing Pub Date : 2023-07-10 DOI: 10.59568/jasic-2023-4-1-03
Erick Yuma, C. Umezuruike, Jossy Nasasira, Gusite Balyejusa
{"title":"Development of a machine learning regression model for accurate sugarcane crop yield prediction, Jinja – Uganda","authors":"Erick Yuma, C. Umezuruike, Jossy Nasasira, Gusite Balyejusa","doi":"10.59568/jasic-2023-4-1-03","DOIUrl":"https://doi.org/10.59568/jasic-2023-4-1-03","url":null,"abstract":"Sugarcane is one of the key crops grown worldwide and used for sugar processing, food, alcohol, biogas, fertilizer, and other products. There is a problem with Sugarcane yield prediction, yields aren’t accurately predicted, and this creates an impact on yields. This research looks at identifying methods used for the prediction, design, development, and evaluation of the three machine learning regression models used for predicting sugarcane yields in Uganda. This research was implemented using Data Science methodology, several machine learning algorithms for prediction of yields on dataset have been analyzed. The collected and analyzed dataset in this research had one output/ dependent variable and eight independent variables. The algorithms used to develop the prediction models are the Multiple Linear Regression algorithm, Decision Tree Regression algorithm, and Random Forest Regression algorithm to predict the output. The dataset of 3 years, 2019, 2020, and 2022 was considered and merged to train and test the model at a ratio of 80% to 20%. The accuracies of the individual models were compared after training, testing the dataset, and evaluation. The multiple Linear regression model results indicate that out of 100%, the model accuracy was 76.5%, the Decision Tree Regression Model scored 89.2%, Random Forest Regression Model was 94.6%. The random forest model came out as the best model. The Random Forest model has a percentage improvement of 60.4%. In future research, researchers can work on, A web-based machine learning model, Deep learning methods used to improve the model and more data can be used to improve the accuracy","PeriodicalId":167914,"journal":{"name":"Journal of Applied Science, Information and Computing","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139361093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Identification and mitigation of the vulnerability of web applications in institutions of higher education 识别和减轻高等院校网络应用程序的脆弱性
Journal of Applied Science, Information and Computing Pub Date : 2023-07-10 DOI: 10.59568/jasic-2023-4-1-06
Muhammed Sabo, Zake Muwanga, Manjula V.S., Saleh Auwal
{"title":"Identification and mitigation of the vulnerability of web applications in institutions of higher education","authors":"Muhammed Sabo, Zake Muwanga, Manjula V.S., Saleh Auwal","doi":"10.59568/jasic-2023-4-1-06","DOIUrl":"https://doi.org/10.59568/jasic-2023-4-1-06","url":null,"abstract":"The security of information technology, specifically web applications, has become an area of concern today. Computer cybercrime is now a significant problem that affects more than just businesses and organizations. Higher education institutions also began to experience computer threats that revealed their information assets. Universities, polytechnics, colleges of education, research centers, and other postsecondary institutions are probably the most vulnerable because they house sensitive data on their faculty, staff, and students, as well as academic records of scientific and technological advancements and research. The first step in an information system security strategy is risk analysis management It helps in assessing the risk of information assets to know their security level or status, and assist in define a security control measures and implementation of technical plan to avoid threats that exploit some vulnerability that could cause severe damage to an asset or infrastructure of institutions higher education (IHEs). This article presents some recommendations to perform a risk analysis management in IHEs to accessed threats and vulnerability that helps to lower the risk of their information assets. This article presents existing educational threat and vulnerability on their web applications. Ensuring security is a goal of every organization regardless of its size or purpose and also proposed a risk management model. With the information technology, an organization may be considered secure when it ensures the confidentiality, integrity, and availability of information and IT assets. Confidentiality may be broken due to theft of sensitive information such as trade secrets, clients’ personal information.","PeriodicalId":167914,"journal":{"name":"Journal of Applied Science, Information and Computing","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139361108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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