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International Conference on Information Management and Technology (ICIMTech)

作者： Felix Indra Kurniadi Ni Luh Putu Satyaning Pradnya Paramita Erna Fransisca Angela Sihotang Maria Susan Anggreainy Rongfang Zhan Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Statistics Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Department of Rehabilitation and Health Service School of Computer Science University of North Texas United States of America

ISBN: (数字)9798350390025

ISBN: (纸本)9798350390032

Depression affects a significant number of people, and it has a significant impact not only on their lives but also on society as a whole. In light of this, we require more advanced methods that are capable of locating individuals who are depressed in a timely and accurate manner. This research investigates the effectiveness of Long Short-Term Mem- ory (LSTM) networks used in conjunction with DistilBERT, a small transformer-based model, in identifying indications of melancholy in posts made on social networking platforms. The text was cleaned up using a dataset that was obtained from Reddit, and then we used the mixed DistilBERT+LSTM model to evaluate how well it performed in comparison to the DistilBERT model by itself. The findings that we obtained indicate that both approaches produce results that are comparable but not flawless, with only slight variations in terms of accuracy, precision, recall, and F1 scores. The fact that this is the case demonstrates that there are issues with optimizing the model and displaying the data.

关键词： Micromechanical devices Accuracy Social networking (online) Mood Mental health Depression Transformers Data models Information management Long short term memory

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Global Patent Landscape of Decision Support System in The Business: An Overview 8

Global Patent Landscape of Decision Support System in The Bu...

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8th International Conference on Information Management and Technology, ICIMTech 2023

作者： Irawan, Michelia Champaca Salsabila Purnomo, Agung Sanjaya, Angelie Natalia Meiryani Ubud, Sahnaz Maulana, Fairuz Iqbal Binus Business School Undergraduate Program Bina Nusantara University Entrepreneurship Department Jakarta11480 Indonesia School of Accounting Bina Nusantara University Accounting Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350326093

The study of decision support systems in business and entrepreneurial ecosystems continues to grow and play an essential role. However, few studies have not comprehensively reviewed decision support system studies from the patent perspective. This research attempts to review the global patent landscape and the main trends of patents on decision support systems in business. Research using patent landscapes analysis was intended to clarify data visualization, identification, and analysis. This study uses 6,713 patent documents and 3,492 simple patent families over 35 years from the *** database. The study results reveal increased trends regarding developments to patent activity related to decision support systems in the business. There were business opportunities that business parties could use to the potential for increasing patent filings. The CPC codes that dominate decision support system patents in the business were G (physics). The United States was the most prolific country regarding owners and inventors. © 2023 IEEE.

关键词： Decision support systems

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Mapping the Landscape of Social Learning: Integrating Key Success Factors, Challenges, and Digital Platforms

Mapping the Landscape of Social Learning: Integrating Key Su...

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International Conference on Information Management and Technology (ICIMTech)

作者： Marcel Meyliana Harco Leslie Hendric Spits Warnars Tirta Nugraha Mursitama Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Management Department BINUS Business School Doctor of Research in Management Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350390025

ISBN: (纸本)9798350390032

This research develops a conceptual model to understand the influence of digitalization on social learning, especially in the context of community empowerment. This model maps the relationship between factors that influence success, challenges faced, and variations in the use of digital platforms in social learning. By using a literature study approach, the research results show that effective communication, collaboration and empowerment are the main keys to the success of social learning in society. Key challenges identified include limited access to information, resource constraints, and digital literacy barriers, all of which require specific strategies to overcome. By examining the relationship between success factors, challenges, and use of digital platforms, this research provides new insights that support the development of more effective strategies for using digital technology to support social learning that leads to community empowerment. This research has great potential to increase people's access to learning opportunities and information, allowing them to be more active in the social learning process.

关键词： Information resources Collaboration Information management Digital intelligence Context modeling

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Mobile application for paid road use for the reduction of traffic congestion 5

Mobile application for paid road use for the reduction of tr...

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5th International Conference on Intelligent Computing and Control Systems, ICICCS 2021

作者： Harliano, Muhammad Rizqiko Afif, Mohammad Ramadhani, Hafiz Iwan, Tanto Harsono Koswara, Rian Warnars, Hareo Leslie Hendrie Spits School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665412728

Technology has evolved a lot in the last few years. E-toll becomes the only payment method available for highway roads, especially in Indonesia. This system of payment is expected to enhance the efficiency of payment from using the previous payment method. However, there are still some weaknesses addressed by the implementation of e-toll. It still takes time because the car's owner should tap the card first, and the sequence time between each person to tap is different. Thus, the queue results still long, and the traffic congestion on the highway road is not fully solved. This paper aims to address a better solution by adding a more efficient option of payment. So, traffic congestion is reduced and leads to better operation in toll gates. This research work has proposed a mobile application and route prediction model based on the Dijkstra Algorithm, where the price will be decided on which type of car will be passed by the gate, and the algorithm predicts the best possible routes based on the number of cars on the highway. Payment is conducted on the application using the balance from the application. This application eliminates time consumed during toll payment at any toll gate. © 2021 IEEE.

关键词： Smart city

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A Hybrid Inference Engine to Predict Uncertain Sugar Content for Sugar Industry

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Procedia computer science 2024年 245卷 480-489页

作者： Muhammad Asrol Napthaleni Ditdit Nugeraha Utama Suharjito Christian Harito Muhammad Syafrudin Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Department of Artificial Intelligence and Data Science Sejong University Seoul 05006 South Korea

The sugar industry is facing challenges in increasing productivity to meet consumer demand. One opportunity for productivity improvement lies in ensuring sugar content. This study proposes a hybrid model to predict sugar content by considering uncertainty factors. A hybrid model combining fuzzy subtractive clustering, and a fuzzy inference system is proposed to predict sugar content. The clustering results using silhouette and fuzzy subtractive clustering successfully identified 6 cluster centres from 2225 datasets collected in a sugar industry in East Java Province. The hybrid inference engine model is designed with fuzzy rules derived from the clustered data. Two inference models are developed: triangular and Gaussian fuzzy numbers. The testing results indicate that the hybrid model with triangular fuzzy numbers shows the smallest error with an R2 value of 0.95. This model is possible to applied in the sugar industry for decision makers in improving productivity with taking attention into uncertain factors influencing sugar content.

关键词： Clustering Fuzzy Hybrid model Inference System Prediction Sugarcane

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Comparison of Spelling Error Correction Algorithms for the Indonesian Language

Comparison of Spelling Error Correction Algorithms for the I...

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Information and Education Technology (ICIET), International Conference on

作者： Yanfi Yanfi Reina Setiawan Haryono Soeparno Widodo Budiharto BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Computer Science School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

Edit distance as a string measurement metric is often used to help detect misspellings in languages. This paper aims to compare two string spelling error correction algorithms for the Indonesian language. The N-gram, Jaro-Winkler distance, and Levenshtein distance algorithms are used to determine whether they can accurately correct typological errors in the Indonesian language. Moreover, this study utilized KNIME tools to process the data from beginning to end. The data was retrieved from news in Indonesia. After the experiment on N from 1 to 12, the results obtained for the comparative analysis proved that Jaro-Winkler distance performed better than Levenshtein distance for comparing smaller strings like words and names. However, Levenshtein distance performs as well as Jaro-Winkler distance started from four strings. Finally, both Jaro-Winkler distance and Levenshtein distance algorithm got the best performance accuracy for eight strings with an accuracy of 99.52 percent. The result of this study is also presented that both algorithms can support word error correction for the Indonesian language.

关键词： Measurement Education Error correction

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Snake and digital ladder applications involving the behavior of children applying the health protocols 2

Snake and digital ladder applications involving the behavior...

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2nd Annual Conference of science and Technology, ANCOSET 2020

作者： Ariessanti, H.D. Gaol, F.L. Supangkat, S.H. Ranti, B. Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department Esa Unggul University Jakarta11510 Indonesia

This study defines the problem of how understanding health protocols during a pandemic is correctly conveyed according to age levels. This problem for the Government to implement gamification by modifying game media through snake and ladder game that can socialize health protocols for pre-school. Measuring the acceptance of a snake and ladder game media can be considered as a learning medium from the Government which will refer to four components (game content, ease of play, appearance, and active player involvement). The purpose of this study was to modify online-based games as a learning media and to measure children's active interaction with parents in practicing health protocols during game play. This study will use a quantitative approach with data techniques through playing together experiments and filling in online research questionnaires from 115 samples as participants (7 Kindergartens). The results show that the snake and ladder digital game can have a significant effect on changes behavior in implementing health protocols. This research can provide a contribution that can be used as a reference for the Government to design a strategy for socialization through gamification. © Published under licence by IOP Publishing Ltd.

关键词： Health

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Literature Review: Analysis of Essential Metadata Attributes of Digital Goods for Transaction in The Virtual World

Literature Review: Analysis of Essential Metadata Attributes...

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International Conference on Information Management and Technology (ICIMTech)

作者： Gede Indra Raditya Martha Harjanto Prabowo Ford Lumban Gaol Richard Wiputra Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Management Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350390025

ISBN: (纸本)9798350390032

In online-based virtual worlds such as Metaverse, Online Games, and other online digital spaces, the virtual/digital goods (digital items / digital assets) are fundamental things that must be available to be able to do business & create an economy in the virtual world through monetization & transactions from these digital goods. This research focuses on summarizing and exploring the attributes used in digital goods in the virtual world by extracting attributes in digital goods from other related studies using the Systematic Literature Review methodology & PRISMA Framework comprehensively so that it can be a reference for developers in designing the properties and functions of digital goods in the virtual world that are being developed, which in this case will be in the form of an NFT in the future. Based on research that has been carried out, 3 essential metadata attributes have the most influence on transactions, number 1 Visual Design / Aesthetic (Representative), number 2 Effect (Utilities), and number 3 Statistics / Performance (Utilities) which must be considered in developing/making digital goods in the form of NFTs in the virtual world so that the value of digital goods can attract users to buy or transact them in the virtual world.

关键词： Visualization Metaverse Buildings Games Metadata Information management Business

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A literature review of crowd-counting system on convolutional neural network 2

A literature review of crowd-counting system on convolutiona...

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2nd International Conference on Biospheric Harmony Advanced Research, ICOBAR 2020

作者： Chrysler, A. Gunarso, R. Puteri, T. Warnars, H.L.H.S. Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia

With the proliferation usage of video surveillance for safety, traffic control, and privacy purposes and with the constant growth of population, it is important to keep monitoring using Closed-Circuit Television (CCTV). With new upcoming developed technologies, new systems and algorithms are introduced and implemented to the crowd counting system today retrieving live video surveillance from the CCTV. However, recent studies show that there are some challenges still faced regarding the crowd counting system which uses the density estimation. The problems that occurred have resulted from the inaccuracy of the system that is caused by several factors. Factors such as the perspective distortion which is caused by the lack of data training and the method such as face detection is an ineffective method to determine the population density. Studies proposed have projected the idea of developing a more robust crowd counting methodology by implementing crowd counting by detection, clustering, and regression. Implementing these methods using the Convolutional Neural Network (CNN) will better the result of the detection since in CNN the image can be inputted and it will undergo several layers which will result in the system being able to differentiate one image from the other. With CNN the process of crowd counting will be able to be more advanced. © Published under licence by IOP Publishing Ltd.

关键词： Face recognition

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BERT-based Topic Modeling Approach for Malaria Research Publication 4

BERT-based Topic Modeling Approach for Malaria Research Publ...

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4th International Conference on Informatics, Multimedia, Cyber and Information System, ICIMCIS 2022

作者： Hidayat, Alam Ahmad Nirwantono, Rudi Budiarto, Arif Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665473279

Malaria is a communicable disease with half of the global population at risk due to its high morbidity and mortality rates. A massive number of studies are dedicated to malaria research, so it plays a key role in formulating the proper prevention strategy and effective malaria treatment. With the overwhelming number of updated publications in the field, an unsupervised text mining approach such as topic modeling may provide an alternative method for the malaria researcher to keep pace with new insights. In this work, we collect metadata of malaria publications from the PubMed database to perform BERT-based topic modeling to find well-defined topics regarding malaria research. The method is largely based on the popular BERTopic pipeline. We compare the performance of three different language models to generate document embeddings from the data. The dimension reduction and the density-based clustering algorithm are used to cluster the embeddings. The topic representation is computed based on the semantic similarity of the class TF-IDF representation. The substance of the resulting topics is then manually annotated based on the top words of each topic. We demonstrate that by merging initial topics into larger topics using hierarchical clustering and manual content-based examination, the evaluated coherence measure can be further improved, thus enhancing the topic's interpretability. Our modeling result is able to extract ten major topics recurring in the malaria research publication published from 2017-2022. The result provides preliminary insight to understand the dynamics and patterns of malaria research over the years © 2022 IEEE.

关键词： Diseases

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