International Journal of Informatics, Information System and Computer Engineering (INJIISCOM)

Reengineering of Proxy Logging Monitoring System in XYZ Institution

Dian Dharmayanti, Adam Mukharil Bachtiar, F Ahmad — Thu, 29 Feb 2024 00:00:00 +0700

This research was conducted to assist the head of the IT Operational & Network Education Division of the XYZ institution to reengineering the internet usage monitoring system. This monitoring system is reengineered so that query performance becomes better and the information presented is easily understood by the user. Reengineering the old system will produce a system model that is more in line with the requirements of the current system. The steps taken in this study, analysis of the monitoring system case domain, data analysis, data visualization reengineering, internet use monitoring system reengineering, software implementation and testing. In addition, testing the performance of the query system and usability testing for users from the new visualization results as the output of this study. Reengineering the internet usage monitoring system is a solution to improve query performance and make it easier for users to understand the information presented

Distributed Systems for Artificial Intelligence in Cloud Computing: A Review of AI-Powered Applications and Services

Hewa Majeed Zangana, Subhi R. M. Zeebaree — Fri, 01 Mar 2024 00:00:00 +0700

The synergy of distributed frameworks with Artificial Intelligence (AI) is pivotal for advancing applications in cloud computing. This review focuses on AI-powered applications in distributed systems, conducting a thorough examination. Analyzing foundational studies and real-world applications, it extracts insights into the dynamic interplay between AI and distributed frameworks. Quantitative measures allow a nuanced comparison, revealing diverse contributions. The survey provides a broad overview of the state-of-the-art, spanning applications like performance optimization, security, and IoT integration. The ensuing discussion synthesizes comparative measures, significantly enhancing our understanding. Concluding with recommendations for future research and collaborations, it serves as a concise guide for professionals and researchers navigating the challenging landscape of AI-powered applications in distributed cloud computing platforms.

Bridging the ICT Gap: TOGAF ADM's Role in Modernizing Educational Institutions

Ahmad Faza, Anggita Nauli Marpaung — Mon, 04 Mar 2024 14:32:44 +0700

In the rapidly advancing world of Information and Communication Technology (ICT), various industries have recognized and started to harness technology's transformative power, especially when it comes to data management and processing. One significant component of this technological evolution is Enterprise Architecture (EA). This offers a structured framework for integrating vast amounts of data across large-scale systems. However, an area that remains somewhat untapped is the application of EA within the educational sector, which presents its own unique set of ICT challenges. This research seeks to address and bridge this knowledge gap. It takes an in-depth look at how EA, utilizing the TOGAF ADM framework, can be implemented in educational settings. Through a series of structured interviews conducted at SMA St. Bellarminus, the research aims to tailor the institution's information systems architecture to its specific and nuanced needs. While there have been previous studies that touched upon organizational systems and structures, our research distinguishes itself by modifying and adapting the TOGAF ADM approach to cater explicitly to educational environments. As the digital realm continues to expand and evolve, it's imperative for educational institutions to have the tools and methodologies in place to stay relevant and efficient in this ever-changing landscape.

Predicting Selling Product of Single Variant Using Arima, Trend Analysis, And Single Exponential Smoothing Methods (Case Study: Swalayan Xyz Store)

Irfan Dwiguna Sumitra, Fajar Sidqi — Sat, 09 Mar 2024 00:00:00 +0700

The availability of goods in a store is very important. Predicting is a tool that is used to help predict the data needed by an organization or company. The purpose of this study is to predict the sale of a product that has a high risk of damage and fast expiration time by using existing techniques in forecasting. Forecasting can also be used to make product stock safety at the XYZ Supermarket. The results of this study are in the form of forecasting the sale of a product in a store by using the existing methods of forecasting that are adjusted to the sales data of one product. The method used in forecasting is the ARIMA method, Trend Analysis, and Single Exponential Smoothing. Trend Analysis Method has the highest accuracy with MAPE 9.91%, which means that forecasting is very good, compared to ARIMA with MAPE 37.21% and Single Exponential Smoothing with MAPE 10%. So that the results of the Trend Analysis forecasting will be used for the decision-making process about forecasting stockpiles and stock safety in the future.

Face Emotion Recognition Based on Machine Learning: A Review

Adnan Mohsin Abdulazeez, Zainab Salih Ageed — Mon, 11 Mar 2024 00:00:00 +0700

Computers can now detect, understand, and evaluate emotions thanks to recent developments in machine learning and information fusion. Researchers across various sectors are increasingly intrigued by emotion identification, utilizing facial expressions, words, body language, and posture as means of discerning an individual's emotions. Nevertheless, the effectiveness of the first three methods may be limited, as individuals can consciously or unconsciously suppress their true feelings. This article explores various feature extraction techniques, encompassing the development of machine learning classifiers like k-nearest neighbour, naive Bayesian, support vector machine, and random forest, in accordance with the established standard for emotion recognition. The paper has three primary objectives: firstly, to offer a comprehensive overview of effective computing by outlining essential theoretical concepts; secondly, to describe in detail the state-of-the-art in emotion recognition at the moment; and thirdly, to highlight important findings and conclusions from the literature, with an emphasis on important obstacles and possible future paths, especially in the creation of state-of-the-art machine learning algorithms for the identification of emotions.

Deep Learning for Sea Turtle Classification: A Bibliometric Analysis Using VOSviewer

Siti NurFarahim, Azran Shabil, Nur Sabrina Balqis — Mon, 11 Mar 2024 00:00:00 +0700

Deep learning in the context of sea turtles constitutes a significant area of exploration within marine science. Consequently, the aim of this study is to perform a bibliometric analysis focusing on the subject of sea turtle deep learning, leveraging mapping analysis through the utilization of VOSviewer software. For this research, we employed a bibliometric and descriptive quantitative approach. The data was acquired by conducting a search on Google Scholar using the keyword "Sea Turtle Deep Learning," which yielded a total of 880 articles published between 2018 and 2023. Notably, only 19 of these articles were directly relevant to the research topic. The findings underscore the diversity of research outcomes in the realm of sea turtle deep learning over this time span. In conclusion, this investigation underscores the significance of conducting bibliometric analyses, particularly within the domain of sea turtle deep learning, and serves as a valuable reference for future research endeavours in defining research themes

Exploring the Nexus of User Interface (UI) and User Experience (UX) in the Context of Emerging Trends and Customer Experience, Human Computer Interaction, Applications of Artificial Intelligence

Biplov Paneru, Bishwash Paneru, Ramhari Poudyal, Krishna Bikram Shah — Wed, 13 Mar 2024 00:00:00 +0700

The complexities of User Interface (UI) and User Experience (UX) design are explored in this research paper, along with their respective functions, areas of overlap, and the changing field of customer experience. In the digital age, where technology is developing at a rapid pace, designing innovative and user-focused digital products requires an understanding of the dynamic interplay between UI and UX. This research also examines how emerging trends in the UI/UX field will affect overall customer satisfaction. Additionally, this paper delves into applications of artificial intelligence (AI) in the domains of human-computer interaction (HCI), user experience (UX), and emerging trends in these fields

Internet Addiction among University Students: Causes, Consequences, and the Role of Cyber Counseling

Kamoru Abidoye Tiamiyu, Habibat Bolanle Abdulkareem, Balikis Olabis Popola — Thu, 14 Mar 2024 00:00:00 +0700

This study explores the prevalence of internet addiction among undergraduate students in Kwara State and examines the potential effectiveness of cyber counselling in addressing this issue. The paper commences by providing a precise definition of internet addiction, proceeds to assess its prevalence among undergraduates in Kwara State, conducts an in-depth review of existing research on the factors contributing to internet addiction, and outlines the adverse consequences associated with excessive internet use among students. Based on this thorough analysis, the research emphasizes the crucial role that cyber counsellors, professionals trained to offer therapeutic guidance and support for individuals struggling with internet addiction, can play in helping individuals manage their addiction and improve their overall well-being. Furthermore, the study advocates for a collaborative approach, bringing together cyber counsellors, educational institutions, and other relevant organizations, to raise awareness about the risks of internet addiction and to develop initiatives and policies that promote a healthier and more balanced internet usage among student populations

Research Trends in Digital Financial Inclusion: A Bibliometric Analysis using VOSviewer

Fri, 15 Mar 2024 00:00:00 +0700

Digital financial inclusion (DFI) aims to provide affordable and sustainable financial services to financially excluded and underserved populations through cost-saving digital means. The purpose of the study is to conduct a bibliometric analysis of DFI using VOSviewer software. A bibliometric and descriptive quantitative approach was employed. Data was collected based on the keyword "digital financial inclusion" from Google Scholar. From the search results, 982 articles published between 2018 and 2023 were found, with 125 relevant to the topic. The number of DFI publications increased from 7 in 2018 to 18 in 2019, indicating a growing interest. The number remained stable in 2020 and 2021, but there was a significant surge in research interest in 2022 with 37 publications. This study demonstrates the relevance of bibliometric analysis, particularly in the field of DFI. The findings are essential for policymakers, researchers, and practitioners to determine the novelty and quantity of data.