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Design of Dual Space Inquiry framework for facilitating flexible learning in digital technology era

International Journal of Educational Research Open 2025年 8卷

作者： Novitra, Fuja Abdullah, Mohd Nor Syahrir Özdemir, Erdogan Riyasni, Selma Emiliannur Festiyed Metra, Pol Department of Physics Faculty of Mathematics and Natural Science Universitas Negeri Padang Indonesia Department of Mathematics and Science Education Faculty of Education University of Malaya Malaysia Vocational School of Health Services Sivas Cumhuriyet University Turkey Information Systems Study Program Faculty of Science and Technology UIN Sulthan Thaha Saifuddin Jambi Indonesia

Mixed learning that offers flexibility is a current requirement. However, the challenge lies in ensuring that these approaches effectively accommodate interactive and practical elements, especially in physics education. This research aims to design a conceptual framework of the Dual Space Inquiry for facilitating flexible learning in basic physics course. An educational design research (EDR) approach was used to develop and validate the Dual Space Inquiry framework comprising three phases: analysis and exploration;design and construction;and evaluation and reflection. This research involved 253 students and 20 experts and practitioners. The findings highlighted the urgency of implementing a mixed learning framework that combines face-to-face and online learning methods in physics education contexts to optimize learning outcomes. These results became the basis for the design of the Dual Space Inquiry Framework which emphasizes flexibility, humanism, and student-centered. Furthermore, the results of expert and practitioner judgment showed that the framework's validity is in the high category (v-values=0.770). Based on the results, it is concluded that an approach that combines online and offline learning with inquiry activities integration in a balanced manner is recommended for optimal learning outcomes for physics education. The Dual Space Inquiry Framework, with its high validity, is a valuable framework for lecturers in physics and other science fields to enhance learning quality and adapt to the digital technology era. © 2024 The Author(s)

关键词： Digital pedagogy Framework ICT Inquiry Teaching strategies

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Dijkstra and Bidirectional Dijkstra on Determining Evacuation Routes 2

Dijkstra and Bidirectional Dijkstra on Determining Evacuatio...

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2020 2nd International Conference on Enhanced Research and Industrial Application 2020

作者： Rahayuda, I.G.S. Santiari, N.P.L. Program Study of Information Systems Faculty of Informatics and Computers Institute of Technology and Business STIKOM Bali Bali Denpasar Indonesia

Determination of the best path or often called the shortest path finding is a method that has many benefits and can be applied in various cases and fields of science. In previous studies, authors have developed the shortest path finding program using various algorithms, such as held-karp, iterative deepening search, bidirectional depth first search and depth limited search. In this research author implements shortest path finding on information system for determining fire disaster evacuation route using Dijkstra and bidirectional Dijkstra. The program was developed based on web using *** framework. Both algorithms were tested on several datasets and the results will be compared to find out the strengths and weaknesses. Based on the research, the algorithm was successfully developed based on the web using the *** framework and successfully tested on several datasets, it is known that 40% of the test results show that bidirectional Dijkstra is better than Dijkstra, 10% vice versa and 50% get the same results from both algorithms. From this comparison it can be concluded that the bidirectional Dijkstra algorithm is better than Dijkstra. This research succeeded in proving that the bidirectional Dijkstra algorithm can produce a better route than the standard or classic Dijkstra algorithm. © Published under licence by IOP Publishing Ltd.

关键词： Iterative methods

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Annotated Data for Semantic Role Labeling of Crisis Events in Indonesian Tweets

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Data in Brief 2025年

作者： Amelia Devi Putri Ariyanto Diana Purwitasari Bilqis Amaliah Chastine Fatichah Muhammad Ghifari Taqiuddin Haikal Department of Informatics Faculty of Intelligent Electrical and Informatics Technology Institut Teknologi Sepuluh Nopember Surabaya 60111 Indonesia Information Technology and Systems Study Program Widya Husada University Semarang 50146 Indonesia Department of Public Health Faculty of Health Science Universitas Dian Nuswantoro Semarang 50131 Indonesia

Social media platforms like Twitter provide essential real-time information about crisis events. Although the text data generated is rich, its vast volume and unstructured format make manual analysis challenging. information extraction technologies such as Semantic Role Labeling (SRL) are needed to identify a sentence's semantic roles, such as who is the victim, what happened, when and where the event occurred, and what objects are affected in the crisis text to speed up and facilitate the emergency response process. However, the availability of public SRL datasets, especially for Indonesian, still considered a low-resource language, is very limited. We aim to develop an Indonesian-language SRL dataset based on Twitter text focusing on crisis events. This dataset includes entity labels for Named Entity Recognition (NER), another information extraction technique besides SRL. Text data was obtained through a crawling process on Twitter using specific keywords from 2018–2023, then preprocessed to obtain clean and relevant data for crisis events in Indonesia. The cleaned text data was then manually annotated by two experts based on guidelines designed to maintain consistency, resulting in 99,206 tokens labeled with SRL and NER. The high inter-annotator agreement value (Cohen's Kappa >0.90) indicates reliable data quality. This dataset is designed to support the development of automated models for information extraction, such as SRL and NER. The results of this extraction will be used for disaster impact analysis, mapping affected areas, and planning for crisis mitigation. By providing this dataset, the research opens up new opportunities for developing Natural Language Processing (NLP) in Indonesian, especially in crisis event analysis.

关键词： Semantic Role Labeling Named Entity Recognition Crisis Event Twitter Data Low-resource Languages Indonesian Tweets

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Evaluation of E-government services based on social media using structural equation modeling 4

Evaluation of E-government services based on social media us...

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4th International Conference on information Management and technology, ICIMTech 2019

作者： Nindito, Hendro Madyatmadja, Evaristus Didik Dian Sano, Albert Verasius Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Study Program Bina Nusantara Institute of Creative Technology Malang65126 Indonesia

ISBN: (纸本)9781728133331

Today many local governments have provided aspiration services or social media based complaints about the community to participate in giving aspirations and report problems that occur around the area. To improve the usefulness of this service, we conduct research with the aim of evaluating and identifying the factors that affect the service's application. The impact of this study is that the government can provide services according to the wishes of the community, because the model found can be a reference for the government to increase public trust and satisfaction for users of government services. The influence on the adoption of Aspiration Services is explained by using perceptions of trust, attitudes, and intentions of use that refer to technology acceptance models (TAM). Data processing and analysis in our research using the SEM-PLS method (Structural Equation Model-Partial Least Square). The results in this research will present that services applying technology that gain a positive effect on the awareness of usability and benefit for service users. © 2019 IEEE.

关键词： Least squares approximations

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The Application of AGNES Algorithm to Optimize Knowledge Base for Tourism Chatbot 3

The Application of AGNES Algorithm to Optimize Knowledge Bas...

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3rd International Conference on information Management and technology, ICIMTech 2018

作者： Sano, Albert Verasius Dian Imanuel, Tanto Daud Intanadias Calista, Mega Nindito, Hendro Condrobimo, Andreas Raharto Bina Nusantara Institute of Creative Technology Computer Science Study Program Malang65126 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

Most tourists have limited time and schedule when they are visiting a particular tourism area. One of the main issues faced by those tourists is that they can not make simple queries to search engines about, for example, which sites or places to visit optimally if we only have one day or two-day visit? Search engines are better and better in replying users' queries with relevant answers. However, search engines are not always able to respond queries suited to users' characteristics such as their styles, personalities, knowledge backgrounds, etc. Also, search engines are not as flexible as chatbots in enabling dialogical-communication-queries. This case study aims to respond aformentioned issue by applying hierarchical cluster analysis on a set of tourism sites around Malang city, Malang regency, and Batu city based on AGNES (Agglomerative Nesting) algorithm. The result, then, is fed into chatbot's knowledge base. This chatbot will assist tourists to get information on which possible sites they have to visit optimally if they are under limited vacancy-Time constraints. © 2018 IEEE.

关键词： Search engines

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Urgency Detection of Events Through Twitter Post: A Research Overview 4

Urgency Detection of Events Through Twitter Post: A Research...

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4th International Conference on Electrical Engineering and Computer Science, ICECOS 2024

作者： Edlim, Frederick William Edo, Gregorius Wiratama, Rangga Kurnia Putra Mahmudin, Riyan Solihin, Andi Ariyanto, Amelia Devi Putri Purwitasari, Diana Institut Teknologi Sepuluh Nopember Department of Informatics Surabaya Indonesia Widya Husada University Information Technology and Systems Study Program Semarang Indonesia

ISBN: (纸本)9798350368253

Indonesia is located in volatile Pacific fire ring and stands as one of the most global disaster-prone areas. The government and public are in constant vigilance of the potential threats. Social media generates large amounts of data from its users and is one of the prime candidates to be used as a disaster monitoring and response system. Several studies have demonstrated the effectiveness of using such an approach for developing disaster monitoring systems. but due to the number of messages generated, filtering is needed to extract useful information from the message. Hence, it's needed to detect an urgency from a message. This review, which was carried out following the PRISMA model, focused on the detection of the urgency of Indonesian Twitter during crisis events. From studies selected, several recommendations are suggested for future endeavor in this topic. Future systems are advised to employ three or four class schemes rather than binary class to gain more nuanced insights into tweet urgency. On-Event training and testing approaches are suitable for frequently occurring events, whereas out-of-event approaches offer broader applicability for real-world scenarios. Both machine learning and deep learning methods, including multimodal approaches, have demonstrated efficacy in urgency detection. Addressing pre-processing challenges, such as abbreviations and slang, is critical, and ensuring consistency in manually annotated data is essential. Additionally, the selection of appropriate word embeddings, such as fastText, IndoBERT, or crisis-specific embeddings, is crucial for achieving optimal model performance. © 2024 IEEE.

关键词： Tweets

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Biomedical Image Quality Improvement with Spatial Domains 2

Biomedical Image Quality Improvement with Spatial Domains

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2nd International Conference on Innovative and Creative information technology, ICITech 2021

作者： Fernando, Erick Siagian, Pandapotan School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Computer Engineering Study Program Del Institute of Technology Faculty of Informatics and Electrical Engineering North Sumatera22381 Indonesia

ISBN: (纸本)9781728197463

Digital image processing aims to improve the quality of an original image so that it can display an image that is relatively better than the original image, so as to obtain the detailed information needed for an analysis need. Quality degradation Biomedical images in computerization usually experience changes in brightness, blur, and contrast stretching. Because of the deterioration in the image quality, doctors and patients cannot obtain the information needed for analysis, therefore the need for biomedical image processing techniques with spatial domain methods to improve the quality and details of information in the image so that it helps doctors in diagnosing. Data analysis is biomedical images like X-ray images, CT-Scan (Computer Tomographic Scan) images, and USG (Ultrasound Graphic) images. A focused study on improving image quality can be done with digital spatial domain image processing techniques. Digital domain image processing is digital image processing based on the manipulation of pixel values in the image directly, in the form of point processing and mask processing. Process testing for each image for Blur level is CT-scan images with a value of 0.98436, ultrasound images with a value of 0.9875, X-ray images with a value of 0.9836. This value is blur level value get near to 1 which means the image becomes clearer. The analysis results prove that the spatial domain method can clarify the object image in this study. The biomedical image quality processing model is proven to be able to improve the quality of the image that is declining due to the digitization process and assist the user in analyzing the biomedical image. © 2021 IEEE.

关键词： Image quality

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Smartphone Application As An Air Quality Monitor Using Raspberry Pi for Reducing Air Pollution 2

Smartphone Application As An Air Quality Monitor Using Raspb...

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2nd International Conference on Innovative and Creative information technology, ICITech 2021

作者： Siagian, Pandapotan Fernando, Erick Computer Engineering Study Program Del Institute of Technology Faculty of Informatics and Electrical Engineering North Sumatera22381 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9781728197463

Good air quality is very important in human health. However, air pollution has been polluted everywhere, whether in the house, in cities. This is caused by a growing industry that produces air pollution. Room air pollution and various cities will contribute to air pollution, which will cause problems for human health. This work measures the carbon monoxide level using the MQ-7 sensor and measures the air's carbon dioxide level with the CCS811 sensor and MH-Z19 sensor. All three sensors are connected to the NodeMCU ESPS266, and we call it a NodeMCU module. Tests are carried out in three rooms in the house, and then three NodeMCU modules are used so that the three modules will send data alternately. Raspberry Pi3 (RPi3) functions as a server that collects data and acquires information data from sensors. Data from the CCS811 (TCOV) sensor, MH-Z19 (co2), will be processed first with fuzzy logic rules to make decisions about CO2, which are right, moderate, nasty conditions. The process is carried out on the Raspberry Pi 3 server with MQTT using publication, customer, fuzzy logic, and broker services. The value of the sensor's measurement results can be accessed via a smartphone and provides good air control values. © 2021 IEEE.

关键词： Air quality

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Long Short Term Memory Networks for Stroke Activity Recognition base on Smartphone 5

Long Short Term Memory Networks for Stroke Activity Recognit...

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5th IEEE International Conference on information technology, information systems and Electrical Engineering, ICITISEE 2021

作者： Siagian, Pandapotan Fernando, Erick Del Institute Of Technology Faculty Of Informatics And Electrical Engineering Computer Engineering Study Program North Sumatera 22381 Indonesia Bina Nusantara University School Of Information Systems Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9781665401968

Aims this study to analyze rehabilitation exercises using sensor data embedded in smartphones is widely used to recognize human activities regularly to gain a better understanding of human behavior. However, it is rarely used to measure accelerators of patient movement in hospital wards. This paper proposes an optimized neural network-based feature extraction approach based on the Long Short Term Memory technique to recognize human activity using data from a tri-axial accelerometer. The activity to be measured is the Range of Motion for patient rehabilitation, and rehabilitation exercises are one of the most important steps for recovery. The results of the softmax regression trained on the dataset set have 1, 076, 105 records and 12 class attributes (class distribution). The experimental results on the SAR dataset show that our Long Short Term Memory-based approach is practical and successful, with an accuracy of 89.74%. © 2021 IEEE.

关键词： Smartphones

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Citrus Limon L. Ripeness Identification Using Feature Extraction of Mean RGB, HSV, LBP and K-Nearest Neighbor

Citrus Limon L. Ripeness Identification Using Feature Extrac...

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2023 International Seminar on Application for technology of information and Communication, iSemantic 2023

作者： Priyo Utomo, Ade Cahyo Sari, Christy Atika Rachmawanto, Eko Hari Hadi, Heru Pramono Mostafa, Salama A. Al-Dayyeni, Wisam Subhi Talib University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Information Systems Semarang Indonesia Universiti Tun Hussein Onn Malaysia Faculty of Computer Science and Information Technology Johor Malaysia Ada University School of Information Technologies and Engineering Baku Azerbaijan

ISBN: (纸本)9798350339215

Citrus Limon L. (Lemon) is a type of fruit that is currently widely consumed, because it contains abundant vitamin C, fiber, and antioxidants. This fruit have high potential in the agribusiness sector and is widely cultivated by traditional farmers. However, during harvest time, traditional farmers generally still use manual methods using the human eye in distinguishing the maturity level of lemons which is less efficient because it has a low accuracy. Digital image processing is one solution to this problem. In the research on the classification of lemon maturity levels using digital image processing with the feature extraction method of the Mean RGB, HSV, and LBP methods and the K-Nearest Neighbor classification algorithm in this study, a total of 120 lemon images were used which were divided into 80 training image data and 40 image data. testing. The results of model performance measurements in the form of the highest accuracy level in the Mean RGB method of 100%, the highest accuracy in the HSV method of 98%, and the highest accuracy in the LBP method of 82.5%. © 2023 IEEE.

关键词： Citrus fruits

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