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Improving the Community Services through Electronic Management of East Pringsewu Subdistrict Administration
No full textEvery Government Institution cannot be separated from carrying out daily administrative activities. Manuscripts or recordings of documents or information, including text, images, and sound recordings, are called archives because archives are records of every activity carried out. Currently, the East Pringsewu sub-district office for filing letters and other activities still uses manual methods. The implementation of E-Government is expected to enable all service activities to the community to be carried out electronically, thereby simplifying policy and service functions. The data collection methods used in this writing are observation, documentation, interviews, and literature study. The SDLC (System Development Life Cycle) method is used in this research, namely a systematic approach to planning, designing, developing, testing, and maintaining software systems. Based on needs analysis, the system developed focuses on managing population data, archiving, and correspondence related to village authority. Before implementing the system, it is necessary to design the system. When designing a system, use the Unified Modeling Language (UML) approach using Use Case Diagrams, Activity Diagrams, and Class Diagrams. Use case diagrams to describe the interaction between users and the system being developed. This research uses the PHP programming language and Visual Studio Code as a text editor and MySQL DBMS. Applications can be used as a medium for implementing subdistrict or village development with information technology and supporting the progress of subdistricts or villages by Government recommendations in developing E-Government
A Study on Non-Fungible Tokens Marketplace for Secure Management
No full textThe secure management and sale of digital assets has become a critical problem in an increasingly digitized environment. This project intends to address this issue by creating decentralized applications (dApps) that use blockchain technology to provide secure and efficient digital asset management, with a focus on NFTs. The NFT marketplace includes secure wallet connections, NFT image creation, minting, the marketplace, and profile management. Solidity-based smart contracts are utilized to create the NFT Marketplace back end, and IPFS is used for storage. The NFT Marketplace's front-end development uses React JSX and the web3js framework, allowing developers to connect to the Ethereum network. NFT Marketplace may assist creators in selling their art through a smart contract system, in which the artwork's ownership transfers to the new owner upon submission of a digital certificate
Implementing Smart College Chatbot using Ml And Python
No full textThe era of just captivating with a console has passed. Voice collaborators and chatbots are employed by clients to engage with frameworks. A chatbot is a piece of computer software that can speak with people using Artificial Intelligence in the Stages that are instructive. When the chatbot receives client input, it remembers both the information and the response, enabling for future use virtual assistant with limited beginning information to grow using built responses. As the quantity of replies increases, so does Chabot’s accuracy. This study will investigate how advancements in AI and ML technology are being used in various organizations. Naturally, it will investigate the evolution of Chat bots as a data dissemination channel. Using WordNet, the computer finds the nearest matching reaction from the nearest matching proclamation that suits the input, and then chooses the reaction from a predetermined set of articulations for that reaction. This mission aimed to develop an online chatbot structure to help students who visit the school's web page, employing equipment that discover Student interaction with the school is made possible by artificial intelligence techniques like natural language processing
Machine Learning Applications in Offense Type and Incidence Prediction
No full textIn today's rapidly evolving world, detrimental behaviourhas undeniably emerged as a significant factor leading to the downfall of individuals and communities. The rising prevalence of such behaviourcreates substantial disruptions within a country's population, affecting social stability and economic progress. To mitigate the impact of these harmful actions, it is crucial to identify and address them promptly and effectively. This study evaluates specific patterns of detrimental behaviour using data from Kaggleto predict and analyzeprevalent negative behaviours. Recent incidents of theft, for example, have underscored the importance of understanding the most common types of misconduct, as well as their timing and locations. We can develop targeted strategies to prevent and respond to such incidents by analyzing these patterns. Artificial Intelligence (AI) techniques encompass variouscomputational methods and algorithms designed to enable machines to perform tasks that typically require human intelligence. These techniques are used in various applications, fromnatural language processing to image recognition, and offer powerful tools for behavioral analysis. This project employs advanced AI techniques, such as Naive Bayes, to model and identify patterns in detrimental behavior. Naive Bayes, a probabilistic classifier based on Bayes' theorem, is particularly effective in handling large datasets and making accurate predictions. By applying this algorithm, the study achieves a high level of precision in predicting various types of detrimental behavior, enabling a better understanding of their underlying patterns. This knowledge can inform the development of more effective prevention and intervention strategies, ultimately contributing to the reduction of harmful behaviors and the enhancement of community well-bein
Analysis of Sentiment Based on Opinions from the 2019 Presidential Election
No full textTwitter is a popular social media platform where the public is free to comment and write about anything. It is common for people to post comments containing harsh words and even hate speech. The 2019 presidential election in Indonesia generated a significant amount of comments, with some users praising the candidates, others criticizing them, and some even resorting to insults. To extract meaningful information from these comments and classify the text, sentiment analysis is essential. In this research, sentiment analysis involves the process of categorizing textual documents into two classes: negative and positive sentiment. The opinion data was collected from the Twitter social network in the form of tweets related to the 2019 presidential election. The dataset used in the study consisted of 3,337 tweets, which were divided into 70% training data and 30% test data. The training data comprised tweets whose sentiment was already known, serving as a foundation for the model to learn and make predictions. The primary objective of this research is to determine whether the tweets, written in Indonesian, express positive or negative sentiments. The Naive Bayes Classifier algorithm was employed to classify the tweet data. This algorithm is well-suited for text classification tasks due to its simplicity and efficiency in handling large datasets. The classification results on the test data demonstrated that the Naive Bayes Classifier algorithm achieved an overall accuracy of 71%. Specifically, the accuracy for negative sentiment classification was 71%, while the accuracy for positive sentiment classification was 70%. These results indicate that the Naive Bayes Classifier is effective in distinguishing between positive and negative sentiments in tweets related to the presidential election
Cybersecurity in Big Data Era: From Securing Big Data to Data-Driven Security
No full textIn the age of information, the proverb "knowledge is power" has been shown to be true. admission to, which ultimately leads to knowledge acquisition. The relevance of the ability to glean knowledge from vast amounts of facts has increased. To describe the process of distributing, storing, and gathering enormous amounts of data for future analysis, researchers coined the term "big data analytics" (BDA). Data is generated at an alarming rate. The Internet of Things (IoT), the net's explosive expansion, and other technological advancements are the main forces behind this long-term growth. Since the information generated reflects the environment in which it is formed, the use of information gleaned from systems to understand the inner workings of those systems. The goal of protecting assets has been developed into a crucial component of cybersecurity. Additionally, big data now has the status of a high-value target due to the growing value of data. Current cybersecurity research in relation to big data has been reported here to explore big data security and its potential use as a cybersecurity tool. This gives trends, open research projects, and challenges along with a summary of current studies in the form of tables. In addition to current advancements and unanswered questions in this area of active research, this research work also provides readers a more thorough understanding of safety in the big data era
Literature Review on the Teaching Engineering Mathematics: Issues and Solutions for Student Engagement
No full textEngineering mathematics is essential for fostering analytical and problem-solving abilities in
engineering education, especially in Malaysia, where it plays a crucial role in the nation's technical
and industrial ambitions. Nevertheless, students encounter substantial obstacles such as the need
to strike a balance between grasping abstract concepts and acquiring practical skills, surmounting
feelings of apprehension about mathematics, actively participating in crowded classrooms, and
adapting to the demands of online education and self-directed study. This paper examines the
difficulties and suggests remedies, with a focus on incorporating active learning methods, creating
supportive learning environments, and using digital resources to improve student involvement and
understanding. The study emphasizes the significance of visualizing abstract mathematical ideas
and establishing connections with practical engineering applications. These strategies are
important to maintain the sustainable development of engineering education. By using these
strategies, instructors may enhance pupils' readiness for prosperous engineering jobs, guaranteeing
that they grasp mathematical ideas, and possess the ability to apply them proficiently in real-world
situations
Corporate Governance and Business Resilience in the Banking Industry
No full textThe unstable banking business environment and ethical questions that bedeviled the industry
have opened new windows for researchers and policymakers on how best to tackle the menace.
But as researchers keep pace on how best banking institutions can remain unperturbed with
preparation for future adversities and bearing in mind the shareholders' wealth, the concept of
resilience becomes the beacon of hope for managers and directors alike. 139 participants drawn
from ten interest-deposit money banks in south-eastern Nigeria were selected for this inquiry.
The result of this study demonstrated that corporate governance predicted business resilience positively. It was concluded that corporate governance that is predicated on board independence, board size, board effectiveness, leadership quality, and accountability would strengthen the resilience of interest deposit money banks. This study recommends that
managing directors of interest deposit money can leverage corporate governance measures utilized in this study to strengthen the resilience capability of their organisations
Potential of Small and Medium Enterprises Growth: Role of Internal and External Factors of Commercial Banks’ Credit Accessibility
No full textThe common factors determining Commercial banks’ lending to SMEs are internal and external
factors. This study assessed the combined effect of these two factors that determine the commercial
banks’ credit accessibility and SMEs’ growth in Nigeria. Data from 1990 to 2023 were used to
evaluate the hypothesis. The outcome demonstrates that internal factors of commercial bank
factors on credit accessibility to SMEs was 0.039110 and statistically significant at the 5% level
(p-value = 0.0254). The outcome suggests that internal factors of commercial bank determinants
on the availability of credit to SMEs play a significant impact in the expansion of SMEs in Nigeria.
At the 5 percent level, the external influence of commercial banks on SMEs' access to credit was
-0.014003 and statistically insignificant (p-value = 0.2757). The results will substantially aid in
designing and implementing monetary policy with regard to the cash reserve requirement. It also
conveys to SMEs the significance of cash reserve requirement in improving loan accessibility in
Nigeria. As a result, the paper recommends that monetary policy be continually improved to favour
SMEs because doing so will facilitate their expansion
The Impact of Gamification on Motivation and Retention in Language Learning: An Experimental Study Using a Gamified Language Learning Application
No full textThis study investigates the effects of gamification elements such as points, levels, and
badges on motivation and retention in language learning. An experimental design was
employed, observing two groups of learners over a 10-week period. One group engaged with
a gamified version of a language learning app, while the control group used the app without
these features. Key variables, including time spent on the app, lesson progression, and
motivation levels, were analysed through surveys and usage data. Results indicated a
significant increase in both motivation and retention within the gamified group, providing
empirical support for integrating game mechanics into language learning