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Rizky Jumansyah
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International Journal of Informatics, Information System and Computer Engineering (INJIISCOM)
Published by Universitas Komputer Indonesia
ISSN : 28100670     EISSN : 27755584     DOI : https://doi.org/10.34010/injiiscom
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering
FOCUS AND SCOPE INJIISCOM cover all topics under the fields of Computer Engineering, Information system, and Informatics. Informatics and Information system IT Audit Software Engineering Big Data and Data Mining Internet Of Thing (IoT) Game Development IT Management Computer Network and Security Mobile Computing Security For Mobile Decision Support System Web and Cloud Computing Accounting Information system Electrical and Computer Engineering Sensors and Trandusers Signal, Image, Audio and Video processing Communication and Networking Robotic, Control and Automation Fuzzy and Neural System Artificial Intelligent
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 145 Documents
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Face Emotion Recognition Based on Machine Learning: A Review Abdulazeez, Adnan Mohsin; Ageed, Zainab Salih
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol. 5 No. 1 (2024): INJIISCOM: VOLUME 5, ISSUE 1, JUNE 2024
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injiiscom.v5i1.12145

Abstract

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.
Reengineering of Proxy Logging Monitoring System in XYZ Institution Dharmayanti, Dian; Mukharil Bachtiar, Adam; Ahmad, F
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol. 5 No. 1 (2024): INJIISCOM: VOLUME 5, ISSUE 1, JUNE 2024
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injiiscom.v5i1.12430

Abstract

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
Predicting Selling Product of Single Variant Using Arima, Trend Analysis, And Single Exponential Smoothing Methods (Case Study: Swalayan Xyz Store) Dwiguna Sumitra, Irfan; Sidqi, Fajar
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol. 5 No. 1 (2024): INJIISCOM: VOLUME 5, ISSUE 1, JUNE 2024
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injiiscom.v5i1.12486

Abstract

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.
Deep Learning for Sea Turtle Classification: A Bibliometric Analysis Using VOSviewer NurFarahim, Siti; Shabil, Azran; Sabrina Balqis, Nur
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol. 5 No. 1 (2024): INJIISCOM: VOLUME 5, ISSUE 1, JUNE 2024
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injiiscom.v5i1.12487

Abstract

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 Paneru, Biplov; Paneru, Bishwash; Poudyal, Ramhari; Bikram Shah, Krishna
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol. 5 No. 1 (2024): INJIISCOM: VOLUME 5, ISSUE 1, JUNE 2024
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injiiscom.v5i1.12488

Abstract

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 Abidoye Tiamiyu, Kamoru; Bolanle Abdulkareem, Habibat; Olabis Popola, Balikis
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol. 5 No. 1 (2024): INJIISCOM: VOLUME 5, ISSUE 1, JUNE 2024
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injiiscom.v5i1.12489

Abstract

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 Ahiase, Godwin; Umar, Abdurrauf; Marwan. M. Saeed, Abdulmalek; Abedin Rasuman, Mohammad; Rianti do Rego Tilman Suri, Epifania
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol. 5 No. 1 (2024): INJIISCOM: VOLUME 5, ISSUE 1, JUNE 2024
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injiiscom.v5i1.12503

Abstract

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.
Smartphone-Based Heart Disease Classification Using Machine Learning Techniques Jamtsho, Yonten; Wangmo, Sonam
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol. 5 No. 2 (2024): INJIISCOM: VOLUME 5, ISSUE 2, DECEMBER 2024
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injiiscom.v5i2.12504

Abstract

Patients having heart diseases are diagnosed with a severe delay at times and further diagnosis in the absence of medical personnel can be fatal if the prediction is inaccurate. Therefore, this paper proposes the use of heart disease datasets to predict heart disease using various machine learning methods (Logistic Regression, Naive Bayes, Random Forest, k-nearest Neighbor, Support Vector Machine, Decision Tree Classifier, XGBoost Classifier, Artificial Neural Network). Cleveland, Hungarian, Switzerland, Long Beach VA and Statlog (Heart) datasets were used in this study which has 11 features of 1190 instances. The dataset was split into train and test sets with a ratio of 80:20. The performance was evaluated based on the accuracy, precision, recall, and F1 score for each of the models. From the eight models, the XGBoost Classifier outperformed other models with an accuracy of 93.7%. The trained model was integrated with the Android Studio framework to create the mobile application for the classification of heart disease.
A Low-Cost Prototype for Edge-Computing Powered Smart Display Board: Edge Computing based notice board system Paneru, Biplov; Paneru, Bishwash; Poudyal, Ramhari; Shah, Krishna Bikram Bikram; Poudyal, Khem Narayan
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol. 5 No. 2 (2024): INJIISCOM: VOLUME 5, ISSUE 2, DECEMBER 2024
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injiiscom.v5i2.12508

Abstract

This study examines how Edge Computing technology, through the creation and use of smart notice boards, has changed the way that organizations communicate. Notice boards have historically relied on manually operated or wired electronic devices, which provide drawbacks like slowness, security flaws, and a lack of adaptability. But a new way of looking at notice board systems has developed with the advent of Edge Computing, which is driven by hardware like the ESP8266 server and communication protocols like MQTT (Message Queuing Telemetry Transport). We explore the advantages of Edge Computing in the context of smart notice boards in this study, emphasizing its capacity to support real-time data processing, improve security via local data management, login credentials, and provide users with user-friendly interfaces for content management. Smart notice boards can outperform traditional systems in terms of efficiency, security, and adaptability by utilizing the concepts of Edge Computing.
Testing and Analysis of PIM Performance in a Passive DAS Network - Experimental Approach Aniru, Muhammed Abudu; Omoavowere, Emagbetere Joy
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol. 6 No. 1 (2025): INJIISCOM: VOLUME 6, ISSUE 1, JUNE 2025
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injiiscom.v6i1.12700

Abstract

Passive intermodulation (PIM) poses a significant challenge in telecommunication networks, with potentially severe impacts on network performance and signal integrity if not addressed during the initial deployment phase. This study investigates PIM levels within a passive distributed antenna system (DAS) network for cellular mobile radio communication across multiple floors of a building. The network comprises coaxial cables, connectors, splitters, combiners, and antennas structured in a systematic plan. This work used the experimental method to test for PIM in the network used for this investigation. Designed as a multicarrier system, it handles RF signals across frequencies of 700/850MHz, 1900MHz, 2100MHz, and 2600MHz. On-site PIM testing was conducted during the network deployment phase to analyze the behavior of high-power RF signals. Utilizing Kaelus iQA-1921C and iQA 850C series PIM analyzers, tests were conducted following known industry codes and standards. High RF power was preset to 43dBm for full band, 35dBm for high bands, and 25dBm for low band. The test equipment was calibrated on high PIM load and low PIM load. Test points were selected at both vertical and horizontal subsystem cabling structures, focusing on riser cables. The standard baseline performance PIM levels was set to -150dBc. The analysis focused on examining the characteristics of PIM signals captured via time-domain PIM traces, investigating the impact of altering the frequency of the two-tone signal on the IM3 frequency component, and highlighting the importance of selecting an appropriate frequency for the two-tone signal that is not positioned near the edges. Results were based on pass or fail test, and resolution measures were taken to mitigate interference.

Page 7 of 15 | Total Record : 145

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