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1st IEEE International Conference on Smart Technology, ICE-SMARTec 2023

作者： Ayub, Mewati Karnalim, Oscar Toba, Hapnes Wijanto, Maresha Caroline Dulimarta, Hans Saputra, Williyandie Kotambunan, Tabitha Emanuella Master Program of Computer Science Maranatha Christian University Bandung Indonesia Ewha Womans University Dept. of Computer Science and Engineering Seoul Korea Republic of School of Computing Grand Valley State University MI United States Informatics Engineering Maranatha Christian University Bandung Indonesia

ISBN: (纸本)9798350306156

programming can help K-12 students to develop their 21st-century core skills. Despite the benefits, programming is not common to be delivered in Indonesian K-12 education. There is a need to understand potential challenges in introducing programming to K-12 students. We developed a questionnaire survey covering four identified dimensions of challenges: administrative, facilities, teachers, and students. We also asked about common programming assessments and their preferred software features for teaching programming. Forty K-12 teachers were invited to complete the survey. The responses were analyzed with thematic analysis using a bigram-based Latent Dirichlet Allocation topic modeling and descriptive statistics. Our study shows that the challenges include limited learning modules, an insufficient number of computers, limited programming skills, and limited computational thinking skills. Scratch was the most common programming language used and many programming assessments were about debugging a program or writing a small program. Visualization and animation can be helpful in teaching programming. © 2023 IEEE.

关键词： Students

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System Design for Therapist Retention Analysis in an Online Mental Healthcare Application Based on MapReduce

System Design for Therapist Retention Analysis in an Online ...

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Technology Innovation and Its Applications (ICTIIA), International Conference on

作者： Iwan Santosa Panji Yudasetya Wiwaha Hapnes Toba Andreas Widjaja Giezka Veby Agustin Katrine Katrine Master Program in Computer Science Universitas Kristen Maranatha Bandung Indonesia

ISBN: (数字)9798350351613

ISBN: (纸本)9798350351620

Retention rate is an important factor for companies providing online services. They can measure potential gains and losses based on insights about their user retention rates. Such insights cover how many active users are, to those who stopped using the application. Based on these insights, companies can analyze the factors that affect user retention, so that they can take further action to minimize users who have the potential to stop using their services. Companies, such as those in the field of mental healthcare, can also develop better business strategies by considering the insights gained from the analysis. This research aims to design an information system to extract information from application usage data, to generate insights about user retention rates based on the metrics required by the company providing the application. The information system design is based on microservices architecture using MapReduce algorithm. The use of big data approach aims to facilitate the company's future needs as user data will grow continuously, as well as other benefits provided by the big data ecosystem. The design-to-testing phase is carried out by implementing an agile project management approach. The prototype successfully passed all testing phases according to acceptance test criteria, hence the information resulting from data processing can meet the company's needs.

关键词： Technological innovation Prototypes Microservice architectures Companies Medical services Big Data Loss measurement System analysis and design Information systems Testing

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Sensor-based Data Acquisition via Ubiquitous Device to Detect Muscle Strength Training Activities

arXiv

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arXiv 2024年

作者： Wianto, Elizabeth Toba, Hapnes Malinda, Maya Chen, Chien-Hsu Bachelor Program in Visual Communication Design Universitas Kristen Maranatha Indonesia Master Program in Computer Science Universitas Kristen Maranatha Indonesia Bachelor Program in Management Universitas Kristen Maranatha Indonesia Industrial Design Department National Cheng Kung University Taiwan

Maintaining a high quality of life through physical activities (PA) to prevent health decline is crucial. However, the relationship between individuals' health status, PA preferences, and motion factors is complex. PA discussions consistently show a positive correlation with healthy aging experiences, but no explicit relation to specific types of musculoskeletal exercises. Taking advantage of the increasingly widespread existence of smartphones, especially in Indonesia, this research utilizes embedded sensors for Human Activity Recognition (HAR). Based on 25 participants' data, performing nine types of selected motion, this study has successfully identified important sensor attributes that play important roles in the right and left hands for muscle strength motions as the basis for developing machine learning models with the LSTM algorithm. © 2024, CC BY-SA.

关键词： Pattern recognition

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Bloom-epistemic and sentiment analysis hierarchical classification in course discussion forums

arXiv

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arXiv 2024年

作者： Toba, Hapnes Hernita, Yolanda Trixie Ayub, Mewati Wijanto, Maresha Caroline Master of Computer Science Study Program Faculty of Information Technology Maranatha Christian University Bandung Indonesia Bachelor of Informatics Study Program Faculty of Information Technology Maranatha Christian University Bandung Indonesia

Online discussion forums are widely used for active textual interaction between lecturers and students, and to see how the students have progressed in a learning process. The objective of this study is to compare appropriate machine-learning models to assess sentiments and Bloom's epistemic taxonomy based on textual comments in educational discussion forums. The proposed method is called the hierarchical approach of Bloom-Epistemic and Sentiment Analysis (BE-Sent). The research methodology consists of three main steps. The first step is the data collection from the internal discussion forum and YouTube comments of a Web programming channel. The next step is text preprocessing to annotate the text and clear unimportant words. Furthermore, with the text dataset that has been successfully cleaned, sentiment analysis and epistemic categorization will be done in each sentence of the text. Sentiment analysis is divided into three categories: positive, negative, and neutral. Bloom's epistemic is divided into six categories: remembering, understanding, applying, analyzing, evaluating, and creating. This research has succeeded in producing a course learning subsystem that assesses opinions based on text reviews of discussion forums according to the category of sentiment and epistemic analysis. © 2024, CC BY-SA.

关键词： Sentiment analysis

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Cluster Dominance Analysis of Strength Training Motion Characteristics

Cluster Dominance Analysis of Strength Training Motion Chara...

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IEEE Global Conference on Consumer Electronics (GCCE)

作者： Hapnes Toba Elizabeth Wianto Maya Malinda Agung Wijaya Al Halim Chien-Hsu Chen Master Program in Computer Science Universitas Kristen Maranatha Bandung Indonesia Bachelor Program in Visual Communication Design Universitas Kristen Maranatha Bandung Indonesia Bachelor Program in Management Universitas Kristen Maranatha Bandung Indonesia Bachelor Program in Informatics Universitas Kristen Maranatha Bandung Indonesia Industrial Design Department National Cheng Kung University Tainan Taiwan

This paper presents an approach to analyze clusters as a means to determine the characteristics of strength training motion patterns. The proposed method emphasizes the observation of dominance sequences within clusters and is reinforced by the formation of specific characteristics within each cluster. Data collection is performed using video-guided strength training exercises equipped with 1 kg dumbbells and recorded by a sensor embedded in smartwatches. The analysis method involves applying the concept of density affinity, which calculates the density ratio of clusters to the recognized motions. Subsequently, the dominance sequence is observed to identify which clusters exhibit distinct characteristics, ultimately determining the intended motions. The research findings demonstrate the potential for further investigation into a more comprehensive understanding of motion patterns, leading to the development of models that can be integrated into mobile devices or smartwatches.

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Topic Relation Graph Construction to Identify Challenges in Introducing programming in Indonesian K-12 Education

Topic Relation Graph Construction to Identify Challenges in ...

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Smart Technology (ICE-SMARTec), IEEE International Conference on

作者： Mewati Ayub Oscar Karnalim Hapnes Toba Maresha Caroline Wijanto Hans Dulimarta Williyandie Saputra Tabitha Emanuella Kotambunan Master Program of Computer Science Maranatha Christian University Bandung Indonesia Dept. of Computer Science and Engineering Ewha Womans University Seoul South Korea School of Computing Grand Valley State University Michigan USA Informatics Engineering Maranatha Christian University Bandung Indonesia

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Inappropriate Benefits and Identification of ChatGPT Misuse in programming Tests: A Controlled Experiment

arXiv

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arXiv 2023年

作者： Toba, Hapnes Karnalim, Oscar Johan, Meliana Christianti Tada, Terutoshi Djajalaksana, Yenni Merlin Vivaldy, Tristan Master of Computer Science Study Program Faculty of Information Technology Maranatha Christian University Bandung Indonesia Bachelor of Informatics Study Program Faculty of Information Technology Maranatha Christian University Bandung Indonesia Media Culture Department Faculty of Information Sciences and Arts Toyo University Kawagoe Japan EC-Council TampaFL United States

While ChatGPT may help students to learn to program, it can be misused to do plagiarism, a breach of academic integrity. Students can ask ChatGPT to complete a programming task, generating a solution from other people’s work without proper acknowledgment of the source(s). To help address this new kind of plagiarism, we performed a controlled experiment measuring the inappropriate benefits of using ChatGPT in terms of completion time and programming performance. We also reported how to manually identify programs aided with ChatGPT (via student behavior while using ChatGPT) and student perspective of ChatGPT (via a survey). Seventeen students participated in the experiment. They were asked to complete two programming tests. They were divided into two groups per the test: one group should complete the test without help while the other group should complete it with ChatGPT. Our study shows that students with ChatGPT complete programming tests two times faster than those without ChatGPT, though their programming performance is comparable. The generated code is highly efficient and uses complex data structures like lists and dictionaries. Based on the survey results, ChatGPT is recommended to be used as an assistant to complete programming tasks and other general assignments. ChatGPT will be beneficial as a reference as other search engines do. Logical and critical thinking are needed to validate the result presented by ChatGPT. © 2023, CC BY.

关键词： Students

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