JOIV : International Journal on Informatics Visualization
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.
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<![CDATA[Characteristics of Multi-Class Suicide Risks Tweets Through Feature Extraction and Machine Learning Techniques ]]>
<![CDATA[Lim, Yan Qian]]>;
<![CDATA[Loo, Yim Ling]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023) ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
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DOI: 10.62527/joiv.7.4.2284
<![CDATA[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.]]>
<![CDATA[A Systematic Literature Review of Design Thinking Approach for User Interface Design ]]>
<![CDATA[Zamakhsyari, Fardan]]>;
<![CDATA[Fatwanto, Agung]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023) ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
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DOI: 10.62527/joiv.7.4.1615
<![CDATA[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.]]>
<![CDATA[LoRaWAN for Smart Street Lighting Solution in Pangandaran Regency ]]>
<![CDATA[Enriko, I Ketut Agung]]>;
<![CDATA[Gustiyana, Fikri Nizar]]>;
<![CDATA[Kurnianingsih, Kurnianingsih]]>;
<![CDATA[Puspita Sari, Erika Lety Istikhomah]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023) ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
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DOI: 10.62527/joiv.7.4.1198
<![CDATA[Smart street lighting is a key application in smart cities, enabling the monitoring and control of street lamps through internet connectivity. LoRa/LoRaWAN, an IoT technology, offers advantages such as low power consumption, cost-effectiveness, and a wide area network. With its extensive coverage of up to 15 kilometers and easy deployment, LoRa has become a favored connectivity option for IoT use cases. This study explores the utilization of LoRaWAN in Pangandaran, a regency in the West Java province of Indonesia. Implementing LoRaWAN in this context has resulted in several benefits, including the ability to monitor and control street lighting in specific areas of Pangandaran and real-time recording of energy consumption. The primary objective of this research is to estimate the number of LoRaWAN gateways required to support smart street lighting in Pangandaran. Two methods are employed: coverage calculation using the free space loss approach and capacity calculation. The coverage calculation suggests a requirement of 34 gateways, whereas the capacity calculation indicates that only two gateways are needed. Based on these findings, it can be inferred that, theoretically, a maximum of 34 gateways would be necessary for smart street lighting in the Pangandaran area. However, further research, including driving tests, is recommended to validate these results for future implementation. This study provides insights into the practical application of LoRaWAN technology in smart street lighting, specifically in Pangandaran. The findings contribute to optimizing infrastructure and resource allocation, ultimately enhancing the efficiency and effectiveness of urban lighting systems. ]]>
<![CDATA[History Students’ Readiness in Using QR Code Based E-Job Sheet ]]>
<![CDATA[Aisiah, Aisiah]]>;
<![CDATA[Purwati, Sherly]]>;
<![CDATA[Pernantah, Piki Setri]]>;
<![CDATA[Afriani, Rini]]>;
<![CDATA[Maharani Putri, Bintang]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023) ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
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DOI: 10.62527/joiv.7.4.2228
<![CDATA[The research objective is to identify primary history students' readiness to use QR code-based e-job sheets in terms of knowledge, experience, and supporting facilities. The research material consists of digital technology devices, smartphones, internet networks, electronic worksheets, QR Code applications, and an assessment of historical learning. This research applied a quantitative approach. Research respondents included significant history students at the Faculty of Social Sciences Universitas Negeri Padang from 2018 to 2022, including 140 students. Data were collected through a Google Form application questionnaire and shared with the students via WhatsApp. The data were analyzed quantitatively by using percentages and averages. General findings showed that many students were ready to use QR code-based e-job sheets, but others still needed them. The particular findings included: 1) more than half of respondents knew what the e-job sheet was, but two-thirds of them had no experience using the e-job sheet, 2) related to QR codes, it was found that half of the respondents knew what QR code was, but a part of them had no experience using QR codes, and 3) two-thirds of the respondents stated that supporting facilities such campus internet and their smartphone were unable to support the use of QR codes-based e-job sheets. QR code-based e-job sheets have become essential in optimizing digital technology in learning activities. Further research is needed to measure the effectiveness of using QR code-based e-job sheets as an alternative strategy and instrument for assessing learning outcomes in the digital era.]]>
<![CDATA[Storychart: A Character Interaction Chart for Visualizing the Activities Flow ]]>
<![CDATA[Abidin, Zainal]]>;
<![CDATA[Munir, Rinaldi]]>;
<![CDATA[Akbar, Saiful]]>;
<![CDATA[Mandala, Rila]]>;
<![CDATA[Widyantoro, Dwi H.]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023) ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
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DOI: 10.62527/joiv.7.4.1608
<![CDATA[Event-predicate-based storyline extraction results in a chronologically ordered activity journal. The extraction results contain complex human activities, so the activity journal requires a visualization model to describe actor interactions. This paper proposes a chart to visualize the activities' flow to describe the characters' interactions in an activity journal. This chart is called a storychart. Storycharts have an actor channel that can accept single entities or teams. The actor channel allows changing the type from single to a team or vice versa and moving members to other teams. The activity channel serves as a connector to accommodate interactions between actors. The activity channel provides a visual space for the elements of what, where, and when. Event predicates are the core of what. Therefore, the storychart visualizes the event predicate using glyphs to attract the reader’s attention. The main contribution of this paper is to introduce a team channel that can visualize the identity of team members and an activity channel that can visualize the details of events. We invited participants to discover the reader’s perception of the ease of team recognition and the integrity of the meaning of the narrative visualized by the storychart. Participants involved in the evaluation were filtered by literacy score. Evaluation of storychart reading showed that readers could easily distinguish teams from single actors, and storycharts could convey the story in the activity journal with little reduction in meaning.]]>
<![CDATA[Curriculum Management Systems for Blended Learning Support ]]>
<![CDATA[Asrini, Hari Windu]]>;
<![CDATA[Wicaksono, Galih Wasis]]>;
<![CDATA[Budiono, Budiono]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023) ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
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DOI: 10.62527/joiv.7.4.1306
<![CDATA[The ongoing COVID-19 has left some serious impacts on education, bringing academic activities to a halt, and restrictions have been in place to hamper the proliferation of the virus. The utilization of technology these days plays a vital role in assisting students in attending education online or blended learning and keeping academic activities running. However, limited learning management systems present a new problem in online learning, especially in higher education. Thus, a new information system is required to resolve this issue. This study aims to develop the Bauran information system to assist lecturers in higher education with curriculum design and semester lesson plans and to evaluate the effectiveness of Bauran's implementation using the ISO 25010 model. The material used during the research process included the Bauran application, Guidelines for Developing Higher Education Curriculum, and some data from relevant users to test the application. Meanwhile, during the development stage of the research, the prototype method was used to adjust the development to the feedback given by stakeholders. This application received positive feedback from relevant users regarding the curriculum development flow in line with the Guidelines of Curriculum Drafting for Higher Education. Using the ISO 25010 model during the testing process, the results of user evaluations demonstrated its effectiveness with an average score of 4.84 out of 5. Future research is expected to evaluate the long-term effectiveness of Bauran using a larger sample size and a different software evaluation model.]]>
<![CDATA[Drowsiness Detection System Through Eye and Mouth Analysis ]]>
<![CDATA[Belle Lim, Bey-Ee]]>;
<![CDATA[Ng, Kok Why]]>;
<![CDATA[Ng, Sew Lai]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023) ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
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DOI: 10.62527/joiv.7.4.2288
<![CDATA[Traffic jams are one of the serious issues in many developed countries. After the pandemic, many employees were allowed to travel interstate to work. This contributes to more severe jams, especially in the capital and nearby states. Long-distance driving and congestion can easily make the drivers sleepy and thus lead to traffic accidents. This paper aims to study and analyze facial cues to detect early symptoms of drowsy driving. The proposed method employs a deep learning approach, utilizing ensemble CNNs and Dlib's 68 landmark face detectors to analyze the facial cues. The analyzed symptoms include the frequency of eyes opened or closed and yawning or no yawning. Three individual CNN models and an ensemble CNN structure are built for the classification of the eyes and mouth yawn. The model training and validation accuracy graph and training loss and validation loss graph are plotted to verify that the models have not been overfitted. The ensemble CNN models achieved an approximate accuracy of 97.4% from the eyes and 96.5% from the mouth. It outperforms the other pre-trained models. The proposed system can immediately alert the driver and send text drowsy messages and emails to the third party, ensuring timely intervention to prevent accidents. The proposed method can be integrated into vehicles and transportation systems to ensure driver's safety. It can also be applied to monitor the driving behavior of those who drive long distances]]>
<![CDATA[A New Feature Extraction Approach in Classification for Improving the Accuracy in Iris Recognition ]]>
<![CDATA[Qadir, Tara Othman]]>;
<![CDATA[Taujuddin, Nik Shahidah]]>;
<![CDATA[Fuad, Norfaiza]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023) ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
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DOI: 10.62527/joiv.7.4.1373
<![CDATA[Personal identity is becoming increasingly vital to meet the increasing security standards of today's business society. Iris recognition is one of the most accurate biometric technologies currently in use. Iris recognition is employed in high-security sectors due to its dependability and flawless identification rates. The steps of iris identification, comprising image preparation, extraction of features, and classifier creation, are described thoroughly in the primary portion of this research. The feature extraction stage is the most important in an iris identification system since it extracts the iris's distinctive feature. Several methods have been devised to extract the various characteristics that are unique to everyone. Modern iris identification systems frequently use Gabor filters to identify iris textural characteristics. However, in the application, it is necessary to identify the appropriate Gabor modules and to generate a pattern of iris Gabor characteristics. This research aims to provide a novel multi-channel Gabor filter and Wavelet filter for breaking down and extracting iris data from two different iris datasets. Because wavelet is the most scalable method of image processing, the research investigates using it to create a unique pattern for the iris recognition system. The MATLAB program is used to implement these ideas. CASIA and MMU are the datasets used for this purpose, and their comparative analysis is addressed in the research. To show how well the method performs, experimental results are given. We demonstrate through experiments that the suggested approach results in excellent iris identification performance.]]>
<![CDATA[A Review of Neural Network Approach on Engineering Drawing Recognition and Future Directions ]]>
<![CDATA[Mohd Yazed, Muhammad Syukri]]>;
<![CDATA[Ahmad Shaubari, Ezak Fadzrin]]>;
<![CDATA[Yap, Moi Hoon]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023) ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
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DOI: 10.62527/joiv.7.4.1716
<![CDATA[Engineering Drawing (ED) digitization is a crucial aspect of modern industrial processes, enabling efficient data management and facilitating automation. However, the accurate detection and recognition of ED elements pose significant challenges. This paper presents a comprehensive review of existing research on ED element detection and recognition, focusing on the role of neural networks in improving the analysis process. The study evaluates the performance of the YOLOv7 model in detecting ED elements through rigorous experimentation. The results indicate promising precision and recall rates of up to 87.6% and 74.4%, respectively, with a mean average precision (mAP) of 61.1% at IoU threshold 0.5. Despite these advancements, achieving 100% accuracy remains elusive due to factors such as symbol and text overlapping, limited dataset sizes, and variations in ED formats. Overcoming these challenges is vital to ensuring the reliability and practical applicability of ED digitization solutions. By comparing the YOLOv7 results with previous research, the study underscores the efficacy of neural network-based approaches in handling ED element detection tasks. However, further investigation is necessary to address the challenges above effectively. Future research directions include exploring ensemble methods to improve detection accuracy, fine-tuning model parameters to enhance performance, and incorporating domain adaptation techniques to adapt models to specific ED formats and domains. To enhance the real-world viability of ED digitization solutions, this work highlights the importance of conducting testing on diverse datasets representing different industries and applications. Additionally, fostering collaborations between academia and industry will enable the development of tailored solutions that meet specific industrial needs. Overall, this research contributes to understanding the challenges in ED digitization and paves the way for future advancements in this critical field.]]>
<![CDATA[Project-Based Learning Model Development Using Flipped Classroom for Drawing Learning in College ]]>
<![CDATA[Mayar, Farida]]>;
<![CDATA[Putra, Febri Wandha]]>;
<![CDATA[Monia, Fenny Ayu]]>;
<![CDATA[Kosassy, Siti Osa]]>;
<![CDATA[Fadli, Rima Pratiwi]]>;
<![CDATA[Arinalhaq, Ririen]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023) ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
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DOI: 10.62527/joiv.7.4.2227
<![CDATA[The learning process was initially carried out online during the pandemic then after the post-pandemic, learning activities began to be carried out face-to-face. This raises a new problem, because lecturers who teach are starting to be required to use various media in the learning process in the new normal era. But in reality, the lecturers still use old methods such as lectures or task-based learning. Therefore, the research objective is to develop a new model that can be used in the learning process in higher education. This type of research is development research using the ADDIE approach. The instrument used was a student learning motivation questionnaire and a student learning satisfaction questionnaire following the lesson. Another instrument used is a Likert model scale with three alternative answers. The operational procedure taken in this research and development goes through three stages, namely: (1) preliminary study, (2) preparation of conceptual models (3) validity test and (4) practicality test. The results of the validity test show that the model book and manual are in the very valid category from the aspects of design, language and content. Furthermore, the practicality test results show that model books and guidebooks for project-based learning models using flipped classrooms for drawing lectures in tertiary institutions are practically used by lecturers. The implications of this research can help lecturers in designing practical learning.]]>
