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JOIV : International Journal on Informatics Visualization
Published by Politeknik Negeri Padang
ISSN : 25499610     EISSN : 25499904     DOI : -
Core Subject : Science,
Computer Science & IT
JOIV : International Journal on Informatics Visualization is an international peer-reviewed journal dedicated to interchange for the results of high quality research in all aspect of Computer Science, Computer Engineering, Information Technology and Visualization. The journal publishes state-of-art papers in fundamental theory, experiments and simulation, as well as applications, with a systematic proposed method, sufficient review on previous works, expanded discussion and concise conclusion. As our commitment to the advancement of science and technology, the JOIV follows the open access policy that allows the published articles freely available online without any subscription.
Arjuna Subject : -
Articles 1,172 Documents
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EmoStory: Emotion Prediction and Mapping in Narrative Stories Too, Seng-Wei; See, John; Quek, Albert; Goh, Hui-Ngo
JOIV : International Journal on Informatics Visualization Vol 7, No 3-2 (2023): Empowering the Future: The Role of Information Technology in Building Resilien
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.3-2.2335

Abstract

A well-designed story is built upon a sequence of plots and events. Each event has its purpose in piquing the audience's interest in the plot; thus, understanding the flow of emotions within the story is vital to its success. A story is usually built up through dramatic changes in emotion and mood to create resonance with the audience. The lack of research in this understudied field warrants exploring several aspects of the emotional analysis of stories. In this paper, we propose an encoder-decoder framework to perform sentence-level emotion recognition of narrative stories on both dimensional and categorical aspects, achieving MAE=0.0846 and 54% accuracy (8-class), respectively, on the EmoTales dataset and a reasonably good level of generalization to an untrained dataset. The first use of attention and multi-head attention mechanisms for emotion representation mapping (ERM) yields state-of-the-art performance in certain settings. We further present the preliminary idea of EmoStory, a concept that seamlessly predicts both dimensional and categorical space in an efficient manner, made possible with ERM. This methodology is useful in only one of the two aspects is available. In the future, these techniques could be extended to model the personality or emotional state of characters in stories, which could benefit the affective assessment of experiences and the creation of emotive avatars and virtual worlds
CNN-LSTM for Heartbeat Sound Classification Aji, Nurseno Bayu; Kurnianingsih, Kurnianingsih; Masuyama, Naoki; Nojima, Yusuke
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.2115

Abstract

Cardiovascular disorders are among the primary causes of death. Regularly monitoring the heart is of paramount importance in preventing fatalities arising from heart diseases. Heart disease monitoring encompasses various approaches, including the analysis of heartbeat sounds. The auditory patterns of a heartbeat can serve as indicators of heart health. This study aims to build a new model for categorizing heartbeat sounds based on associated ailments. The Phonocardiogram (PCG) method digitizes and records heartbeat sounds. By converting heartbeat sounds into digital data, researchers are empowered to develop a deep learning model capable of discerning heart defects based on distinct cardiac rhythms. This study proposes the utilization of Mel-frequency cepstral coefficients for feature extraction, leveraging their application in voice data analysis. These extracted features are subsequently employed in a multi-step classification process. The classification process merges a convolutional neural network (CNN) with a long short-term memory network (LSTM), forming a comprehensive deep learning architecture. This architecture is further enhanced through optimization utilizing the Adagrad optimizer. To examine the effectiveness of the proposed method, its classification performance is evaluated using the "Heartbeat Sounds" dataset sourced from Kaggle. Experimental results underscore the effectiveness of the proposed method by comparing it with simple CNN, CNN with vanilla LSTM, and traditional machine learning methods (MLP, SVM, Random Forest, and k-NN).
Developing Compliant Audit Information System for Information Security Index: A Study on Enhancing Institutional and Organizational Audits using Web-based Technology and ISO 25010:2011 Total Quality of Use Evaluation Prabowo, Wahyu Adi
JOIV : International Journal on Informatics Visualization Vol 8, No 1 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.1.1845

Abstract

This study aimed to develop the KAMI 4.1 Index system application based on web application technology to provide a platform for controlled audit implementation and improve data management. The primary goals were to independently assess organizations' ability to obtain ISO 27001:2013 and enhance the audit process's effectiveness and efficiency. The research utilized web application technologies as materials. It employed a systematic approach, focusing on developing a web-based application using the waterfall model's stages of communication, planning, modeling, construction, and deployment. The resulting KAMI 4.1 Index system application introduced a new and efficient platform for controlled audit implementation, featuring an improved user experience and enhanced ease of use by incorporating existing audit calculations from the KAMI 4.1 index. Evaluation based on the ISO 25010:2011 quality of use model yielded a high total quality of use rate of 81.45%, indicating a "very good" categorization. However, areas requiring further research and improvement were identified, including data security, content coverage, freedom from risk, and error tracking. The study also suggested exploring integration possibilities of the audit system with other ISO audit needs, such as a quality assurance system complying with ISO 9001. Further research is necessary to gather information about user criteria and needs in different organizational contexts, ensuring the audit application system meets their requirements. Overall, this research contributes to developing the KAMI 4.1 Index system application and highlights directions for further enhancement and exploration in controlled audit implementation and data management.
Expert Analysis on the User Interface of an Academic E-Supervision Application Based on Vocational Education Character Syukhri, -; Ganefri, -; Tasrif, Elfi; Hidayat, Hendra
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.2109

Abstract

Designing information systems to accommodate the unique needs of various users receives a lot of attention in contemporary software engineering. One such distinctive requirement in the educational context is academic supervision. Academic supervision encompasses activities to assist educators in enhancing their skills for managing the learning process and achieving educational objectives. In vocational high schools, the primary educational goals are to prepare students for the job market and empower them to initiate their businesses. These goals can only be realized if teachers incorporate technical and entrepreneurial skills into learning. The main goal of this study is to assist school supervisors and principals in assessing and directing teachers as they incorporate ideas of vocational education into the teaching and learning process. The research methodology used in this study is research and development, which includes several stages: initial needs analysis and assessment of the current state of academic supervision; development, which involves the creation of a conceptual system model; system interface design; model validation and revision; and evaluation, which requires system testing, implementation, and deployment. Based on the initial investigation and analysis of academic supervision, particularly in the context of vocational education, this research presents a conceptual model and system interface design. The outcomes of this research encompass the interface, system architecture, and user guide for the academic e-supervision system. An expert analysis of the user interface design indicates that the interface received positive evaluations from experts, with an overall average rating of 88%.
The Implementation of the K-Medoid Clustering for Grouping Hearing Loss Function on Excessive Smartphone Use Wahyudi, Eri; Meidelfi, Dwiny; -, Nofrizal; Saam, Zulfan; -, Juandi
JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.7.4.1873

Abstract

During the current pandemic, smartphones have become a means of learning for all students in Indonesia, including high school students. Students use smartphones to send assignments, learn via video calls, and conduct online exams. The prolonged use of smartphones, from the beginning of learning hours in the morning to study hours in the evening, has a terrible impact on the ear health of high school students in Padang. Excessive smartphone use caused a decrease in the student's hearing function. Therefore, this study aims to group the audiometry results of high school students in Padang who have a hearing loss function. The audiogram result is only performed as the result of a frequency test of the subject's hearing in both the left and right ear. Conventionally, an otolaryngologist concluded the final decision of hearing loss ability. This research proposed an automatic classification of audiometry results using machine learning methods. The K-Medoids clustering was selected to classify the audiometry data in this research. Of 210 audiometry data, 91 data is confirmed by an otolaryngologist as valid data. By using the K-Medoids clustering, 93 data is classified into Normal hearing, Mild Hearing loss, and Moderate Hearing loss. The proposed model successfully grouped the audiometry data into three categories. The confusion matrix is applied to measure the model performance, which has 28,3% accuracy, 64,3% precision, and 21,4% recall. 
Artificial intelligence applications in solar energy Le, Thanh Tuan; Le, Thi Thai; Le, Huu Cuong; Dong, Van Huong; Paramasivam, Prabhu; Chung, Nghia
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.2686

Abstract

Renewable energy research has become significant in the modern period owing to escalating prices of fossil fuels and the pressing need to reduce greenhouse gas emissions. Solar energy stands out among these sources due to its abundance and global accessibility. However, its weather-dependent and cyclical nature add inherent risks, making effective planning and management difficult. Soft computing technologies provide attractive solutions for modeling such systems, while machine learning and optimization techniques are gaining popularity in the solar energy industry. The current literature highlights the growing use of soft computing technologies, emphasizing their potential to address difficult challenges in solar energy systems. To effectively reap the benefits, these strategies must be seamlessly connected with emerging technologies like the Internet of Things (IoT), big data analytics, and cloud computing. This integration provides a unique opportunity to improve the scalability, flexibility, and efficiency of solar energy systems. Researchers can use these synergies to create intelligent, linked solar energy ecosystems capable of real-time optimization of energy production, delivery, and consumption. These technologies have the potential to transform the renewable energy environment, allowing for more resilient and sustainable energy infrastructures. Furthermore, as these technologies improve, there is a growing demand for trained experts to address associated cybersecurity problems, assuring the integrity and security of these sophisticated systems. Researchers may pave the road for a more sustainable and energy-efficient future by working collaboratively and using interdisciplinary methodologies.
NasiQu: Designing Mobile Applications with the Concept of Social Entrepreneurship for Hunger People Using Agile Methods Hidayat, Hendra; Yulastri, Asmar; Susanto, Perengki; Ardi, Zadrian; Yustisia, Henny
JOIV : International Journal on Informatics Visualization Vol 8, No 1 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.1.1896

Abstract

Entrepreneurship is becoming an essential part of everyday life today. But the social problems of society, especially cases of hunger, have also become an essential issue to date. Digital entrepreneurship has become a trend recently, with many digital business platforms and emerging applications. However, combining digital entrepreneurship with social activities becomes more attractive, which we know as Digital Social Entrepreneurship. This study describes and explains the stages in designing NasiQu, a mobile social entrepreneurship application, to see how agile can make digital social entrepreneurship interesting by involving people's sense of concern for people in need, in this case, hungry people. The Agile method, one of many used in software development, is the one that is being used. The Agile method is a short-term system development approach that calls for quick adaptation and developers who can work with any change. The results of this product from NasiQu can facilitate donations in the form of packaged rice to those who need food; in the case of this implementation, it is still specifically for orphans. In this application, there are three users, namely donors, admins, and partners. All these users have different roles and application usage flows. In addition, this application makes food donation activities more effective and can be done anywhere and anytime. It is hoped that the ongoing implementation of this activity will help many people who need food and impact opening new job opportunities.
Cluster Analysis of Japanese Whiskey Product Review Using K-Means Clustering Witarsyah, Deden; Akbar, Moh Adli; Praditha, Villy Satria; Sugiat, Maria
JOIV : International Journal on Informatics Visualization Vol 8, No 1 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.1.2601

Abstract

Since 2008, the Japanese whiskey business has grown steadily. Overall, the whiskey market (at factory price) is expected to reach $2.95 billion in 2019, accounting for 8.6 percent of the entire alcoholic beverage industry. The rise in popularity of Japanese whiskey is associated with the country's growing international reputation. Founded 1985 as an independent bottler, Master of Malt was the first company to service clients who ordered single malt whiskey through the mail-order system. Master of Malt's omnichannel approach encompasses all channels available to the company. Known as their 'omnichannel,' this refers to the organization's capability to provide speed and precision from any place at any time. As their brand has grown over the years, they have used various marketing strategies, including a website redesign and rebuild that involved the creation of all relevant content and designing and constructing landing pages for their website. Following a clustering technique, we discovered that the data is being divided into four distinct groups and that these clusters may serve as a recommender system based on the occurrence of terms in each of the categories. Our summarizing component combined phrases related to the exact subtopics and provided users with a concise summary and sentimental information about the group of phrases.
Characteristics of Multi-Class Suicide Risks Tweets Through Feature Extraction and Machine Learning Techniques Lim, Yan Qian; Loo, Yim Ling
JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.7.4.2284

Abstract

This paper presents a detailed analysis of the linguistic characteristics connected to specific levels of suicide risks, providing insight into the impact of the feature extraction techniques on the effectiveness of the predictive models of suicide ideation. Prevalent initiatives of research works had been observed in the detection of suicide ideation from social media posts through feature extraction and machine learning techniques but scarcely on the multiclass classification of suicide risks and analysis of linguistic characteristics' impact on predictability. To address this issue, this paper proposes the implementation of a machine learning framework that is capable of analyzing multiclass classification of suicide risks from social media posts with extended analysis of linguistic characteristics that contribute to suicide risk detection. A total of 552 samples of a supervised dataset of Twitter posts were manually annotated for suicide risk modeling. Feature extraction was done through a combination of feature extraction techniques of term frequency-inverse document frequency (TF-IDF), Part-of-Speech (PoS) tagging, and valence-aware dictionary for sentiment reasoning (VADER). Data training and modeling were conducted through the Random Forest technique. Testing of 138 samples with scenarios of detections in real-time data for the performance evaluation yielded 86.23% accuracy, 86.71% precision, and 86.23% recall, an improved result with a combination of feature extraction techniques rather than data modeling techniques. An extended analysis of linguistic characteristics showed that a sentence's context is the main contributor to suicide risk classification accuracy, while grammatical tags and strong conclusive terms were not.
A Systematic Literature Review of Design Thinking Approach for User Interface Design Zamakhsyari, Fardan; Fatwanto, Agung
JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.7.4.1615

Abstract

The user interface is an influential element in software applications. A well-designed user interface will potentially increase the usability of software applications. Therefore, user interface designers should deliberate when considering which approach and method to implement for designing user interfaces. Design thinking is currently a widely followed approach in user interface design practices. Hence, this study aimed to explore research trends and current practices of design thinking approach for user interface design. This study employed a systematic literature review following the Kitchenham method. This study found 39 articles deemed relevant to the design thinking approach. In general, our study found five common stages broadly mentioned in the articles, i.e., empathize, define, ideate, prototype, and test. The most widely practiced method during those five stages is interview, user persona, brainstorming, user interface, and usability testing. However, there is no consensus on what kind of stage(s) and which method(s) should be employed when following the design thinking approach for user interface design. Therefore, it will depend on the designer's decision in choosing which stage(s) and their related method(s) will be employed.

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