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Identification of Meteorological Parameters Affecting Dengue Hemorrhagic Fever Incidences 4

Identification of Meteorological Parameters Affecting Dengue...

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4th International Conference on Informatics, Multimedia, Cyber and information system, ICIMCIS 2022

作者： Asadi, Faisal Trinugroho, Joko Pebrianto Hidayat, Alam Ahmad Rahutomo, Reza Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information System Department Jakarta11480 Indonesia Binus Graduate Program Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665473279

Tropical disease is one of the infectious diseases that affect Indonesia. Many people die because of tropical diseases, such as dengue hemorrhagic fever (DHF), chikungunya, leprosy, lymphatic, and filariasis. The Indonesian government's lack of public policy is the main problem in treating and preventing tropical diseases. The paper aims to describe the analysis results of the incidence of DHF in Jakarta, Indonesia. The analysis used the DHF incidences data from the Jakarta Health service surveillance office representative and combined it with the meteorological parameters data. The meteorological parameters were collected from the Bureau of Meteorological Climatology and Geophysics (BMKG). The statistical analysis of this research used Pearson's correlation. The results show that the meteorological parameters affecting DHF incidences are temperature, humidity, and wind speed. © 2022 IEEE.

关键词： Correlation methods

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Trend Intelligent Tutoring system 2018-2022 : systematic Literature Review

Trend Intelligent Tutoring System 2018-2022 : Systematic Lit...

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Innovation in Technology (INOCON), IEEE International Conference for

作者： Jaka Suwita Harjanto Prabowo Harco Leslie Hendric Spits Warnars Meyliana Meyliana Departement of Computer Science BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Department of Information System STMIK Insan Pembangunan Tangerang 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

ITS is a method of teaching that uses technology to give lessons without the need for an instructor to be there. A systematic literature review (SLR) was conducted in this research to identify the components of an intelligent tutoring system, and the results are presented. The method used in this literature review is the prism method. The steps in the prism method are slr protocol, search for literature, select literature, summarize evidence and disseminate results. The slr protocol stage, it consists of determining a research question, searching for scientific reference sources with the keyword intelligent tutoring system, then sorting out the appropriate articles and making final conclusions. This article gives a detailed look at how the intelligent tutoring system changed over time during the pandemic epoch. Our contribution is complete information on the components of ITS in times of epidemic at universities, with the goal of improving their learning and practical use of the technology.

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The Role of Social Media on Purchase Decisions in Indonesia: Perspective of Z Generation

The Role of Social Media on Purchase Decisions in Indonesia:...

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IEEE Symposium on Industrial Electronics & Applications (ISIEA)

作者： Flourency Vellamy Dini Agnes Wijaya Anderes Gui Muhammad Shabir Shaharudin Anwar Allah Pitchay Razib Chandra Chanda Information System Study Program School of Information Systems Bina Nusantara University Jakarta Indonesia School of Management Universiti Sains Malaysia Penang Malaysia Graduate School of Business Universiti Sains Malaysia Penang Malaysia

The technological revolution had a significant impact on people's lifestyles. With the development of technology, more and more social media are being created. Social media that is now widely used, namely Instagram, Facebook, TikTok, Twitter, etc. is one indication of the increasing use of the internet and people's need for online shopping. Currently, almost all social media have implemented live streaming and even shop features, which can increase usage and consumption rates, especially for Generation Z. Generation Z has an open way of thinking and likes instant things, including shopping. Apart from the convenience provided by social media, various impacts help Generation Z in making purchasing decisions. Therefore, this research was conducted to find out whether the role of social media can help Generation Z in making purchasing decisions, with the risks that exist in social media. With a sample of 300 respondents including Generation Z, who make purchasing decisions online, this research was collected through a quantitative survey method. The results of the questionnaire data will be analyzed using IBM SPSS version 28, while the model and structural measurements are analyzed using SmartPLS 4. The results of data collection show that Generation Z, in making purchasing decisions, does not care about the risks involved. Perceived risks are considered insignificant, but the theory holds that it is significant to consumers. Therefore, future research should consider whether the role of social media use in Generation Z has a different risk perception.

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Level of awareness of Digital Banking Users on Risk and Security in Greater Jakarta

Level of awareness of Digital Banking Users on Risk and Secu...

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International Conference on Business and Industrial Research (ICBIR)

作者： Flourency Vellamy Dini Agnes Wijaya Anderes Gui Yuvaraj Ganesan Muhammad Shabir Shaharudin Anwar Allah Pitchay Information System Study Program School of Information Systems Bina Nusantara University Jakarta Indonesia Graduate School of Business Universiti Sains Malaysia Penang Malaysia School of Management Universiti Sains Malaysia Penang Malaysia

The development of technology in financial sector has change the monetary transaction system in the world. Currently, there are many banks provide services in digital banking because it is convenience to the users and, it has simplifies the movement and less time required compared to non-digital banking transaction. However, the side back of the digital banking to users are such as many frauds committed through digital banking, leaks or theft of users' data, when top-up balances are held up, interruptions when making transfers, and others. According to the OJK, with this digital transformation, cyber security attacks have increased by up to 86.70%. Therefore, it is important to seek and examine the awareness of digital banking users related to the risk and security of digital banking. 104 respondents participated in the self-administered questionnaire and we used a descriptive analysis to measure the level of awareness of risk and security of using digital banking. The descriptive results shows that more than 75% of respondents agree and are aware that digital banks have a fairly high-security risk, when doing top-ups there are frequent interruptions or pending, and the account is easy to access by anyone who knows our account. In addition, more than 15% of respondents feel that traditional banks have a higher risk, and fraud that occurs in digital banks does not occur often. The results of the study provides a preliminary information to the reader about the awareness of the digital banking in the context of Greater Jakarta.

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Recurrent Neural Network-based Models as Bahasa Indonesia-Sundanese Language Neural Machine Translator

Recurrent Neural Network-based Models as Bahasa Indonesia-Su...

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2023 International Conference on Computer Science, information Technology and Engineering, ICCoSITE 2023

作者： Wijanarko, Bambang Dwi Heryadi, Yaya Murad, Dina Fitria Tho, Cuk Hashimoto, Kiyota BINUS Online Learning Computer Science Department Bina Nusantara University Jakarta11480 Indonesia BINUS Graduate Program - Doctor of Computer Science Computer Science Department Bina Nusantara University Jakarta11480 Indonesia BINUS Online Learning Information Systems Department Bina Nusantara University Jakarta11480 Indonesia Prince of Songkla University Interdisciplinary Graduate School or Earth System Science and Andaman Natural Disaster Management Phuket83120 Thailand

ISBN: (纸本)9798350320954

Sequential data are available in many domains including weather observation data, stock price, gene sequence, and many others. Sequential data processing is very instrumental as a solution to a variety of downstream tasks in Natural Language Processing such as language translation. Translating a language to another language has become instrumental when peoples interact with other people who speak a different language. However, language translation is not an easy computation task when there is a language-resource gap. This paper presents some empirical results from the exploration of the Recurrent Neural Network (RNN), the Gated Recurrent Unit (GRU), the Long Short-term Memory (LSTM), and the Bidirectional Long Short-term Memory (Bi-LSTM) models as machine translation models from Bahasa Indonesia to the Sundanese language. These empirical results show that the Bi-LSTM achieved the highest performance (0.95 average training accuracy and 0.92 average testings BLEU score) compared to the RNN (0.93 average training accuracy and 0.91 average testings BLEU score), the GRU (0.88 average training accuracy and 0.89 average testings BLEU score), and the LSTM (0.92 average training accuracy and 0.91 average testings BLEU score) models. These results validate some previously reported studies that claim the Bi-LSTM model potentially outperforms the other recurrent neural network-based models when it is used to process sequence datasets. © 2023 IEEE.

关键词： Long short-term memory

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Neural Machine Translation Approach for Low-resource Languages using Long Short-term Memory Model

Neural Machine Translation Approach for Low-resource Languag...

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2023 International Conference on Computer Science, information Technology and Engineering, ICCoSITE 2023

作者： Heryadi, Yaya Wijanarko, Bambang Dwi Murad, Dina Fitria Tho, Cuk Hashimoto, Kiyota Bina Nusantara University BINUS Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia BINUS Online Learning Computer Science Department Bina Nusantara University Jakarta11480 Indonesia BINUS Online Learning Information Systems Department Bina Nusantara University Jakarta11480 Indonesia Prince of Songkla University Interdisciplinary Graduate School or Earth System Science and Andaman Natural Disaster Management Phuket83120 Thailand

ISBN: (纸本)9798350320954

Communication is a form of translation that human learns naturally since early childhood. Translating a language to another language has become instrumental when peoples interact with other people who speak a different language. One example of high-impact language translation is translating health protocols from the World Health Organization to many national languages to prevent the spread of the Covid-19 virus. However, the language translation is not an easy computation task when there is a language-resource gap. This paper presents empirical results on the performance of the Long Short-term Memory model as a machine translation involving Bahasa Indonesia and the Sundanese languages. Performance of the Sundanese language to Indonesian language translation is 0.93 average training and validation accuracy and 0.91 average testings BLEU score. Whilst, Indonesian language to Sundanese language translation is 0.92 average training and validation accuracy and 0.88 average testings BLEU score. Both models achieve 0.39 average training loss and 0.38 average validation loss. © 2023 IEEE.

关键词： Viruses

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Revalidating the Encoder-Decoder Depths and Activation Function to Find Optimum Vanilla Transformer Model

Revalidating the Encoder-Decoder Depths and Activation Funct...

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2023 International Conference on Computer Science, information Technology and Engineering, ICCoSITE 2023

作者： Heryadi, Yaya Wijanarko, Bambang Dwi Fitria Murad, Dina Tho, Cuk Hashimoto, Kiyota Bina Nusantara University Graduate Program- Computer Science Computer Science Department BINUS Jakarta11480 Indonesia Bina Nusantara University Online Learning Computer Science Department BINUS Jakarta11480 Indonesia Bina Nusantara University BINUS Online Learning Information Systems Department Jakarta11480 Indonesia Prince of Songkla University Interdisciplinary Graduate School or Earth System Science and Andaman Natural Disaster Management Phuket83120 Thailand

ISBN: (纸本)9798350320954

The transformer model has become a state-of-the-art model in Natural Language Processing. The initial transformer model, known as the vanilla transformer model, is designed to improve some prominent models in sequence modeling and transduction problems such as language modeling and machine translation. The initial transformer model has 6 stacks of identical encoder-decoder layers with an attention mechanism whose aim is to push limitations of common recurrent language models and encoder-decoder architectures. Its outstanding performance has inspired many researchers to extend the architecture to improve its performance and computation efficiency. Despite many extensions to the vanilla transformer, there is no clear explanation of the encoder-decoder set out depth in the vanilla transformer model. This paper presents exploration results on the effect of combination encoder-decoder layer depth and activation function in the feed-forward layer of the vanilla transformer model on its performance. The model is tested to address a downstream task: text translation from Bahasa Indonesia to the Sundanese language. Although the value difference is not significantly large, the empirical results show that the combination of depth = 2 with Sigmoid, Tanh, and ReLU activation function;and d = 6 with ReLU activation shows the highest average training accuracy. Interestingly, d = 6 and ReLU show the lowest average training and validation loss. However, statistically, there is no significant difference between depth and activation functions. © 2023 IEEE.

关键词： Neural machine translation

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Learner Action Patterns in the Problem-Solving Process Related to program Code Composition Based on Tracking system Activities 7

Learner Action Patterns in the Problem-Solving Process Relat...

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7th International Conference on Informatics and Computing, ICIC 2022

作者： Syahidi, Aulia Akhrian Supianto, Ahmad Afif Hirashima, Tsukasa Watanobe, Yutaka Politeknik Negeri Banjarmasin Smart City Information System Applied Undergraduate Program Banjarmasin City Indonesia Research Center for Data and Information Sciences Bandung City Indonesia Graduate School of Advanced Science and Engineering Hiroshima University Kagamiyama Learning Engineering Laboratory Higashihiroshima Japan University of Aizu Division of Information Systems Department of Computer Science and Engineering Fukushima AizuWakamatsu Japan

ISBN: (纸本)9798350345711

Learning activities are an indicator of the learner's desire to learn during the learning process. The pattern of learner action is related to learning activities. In this case, in extracting the learning process, it is necessary to collect a lot of data through analysis of the learning process. The purpose of this study is to recommend and report the performance of an activity tracking system equipped with visual artifacts as an educational data mining approach to analyze action patterns when learners complete the arrangement of program code lines in each programming problem. In this study, data were taken from activity recordings when learners used interactive learning media for a basic programming subject called TOLSYASUPI-EduMed which had problem-solving learning models embedded in their interactions. Learning Analytics is used as a method of this research and data relationships from learner actions during the learning process using the 'if-then' rule. Log data is used for recording and detecting activities carried out by learners. We confirm that the results of the study are based on the findings of the data relationship that if the lines of program code are too long (more than five lines) then almost all learners experience a bottleneck condition. The completion time of each question and the number of iterations in completing the program code lines for each question have also been recorded and have a pattern of connection between the data. The information that has been obtained is then forwarded to teachers or stakeholders as key information to make appropriate feedback to learners based on the results as a means of analyzing and evaluating the programming learning process. © 2022 IEEE.

关键词： Data mining

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Selection of the Most Beneficial Flight Training Venue in the Airline Industry Using the Analytic Hierarchy Process (AHP) 23

Selection of the Most Beneficial Flight Training Venue in th...

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5th International Conference on Management Science and Industrial Engineering, MSIE 2023

作者： Payumo, Redentor R. Redi, Anak Agung Ngurah Perwira German, Josephine D. Persada, Satria Fadil Nadlifatin, Reny School of Graduate Studies Mapua University Manila Philippines Department of Industrial Engineering Sampoerna University Jakarta Indonesia School of Industrial Engineering and Engineering Management Mapua University Manila Philippines Entrepreneurship Department Bina Nusantara University Binus Business School Undergraduate Program Jakarta Indonesia Department of Information System Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (纸本)9798400708381

The airline industry is a highly regulated industry where every aspect of operation requires adherence to regulations and policies mandated by the government. Safety is the core value-offering of fast and reliable air services, and this is achieved in part by the robust training requirement for pilots. Pilot training and qualifications are achieved with the use of full flight simulators. The significant costs involved in the use of the simulator, other additional costs involved, and the need to minimize pilots' time away from flight duties while undergoing training, require an effective selection process to decide on the most beneficial training venue. Not much research has been done on this topic area and the research gap necessitates a study of this nature. The goal is to provide a criteria analysis to support the simulator training venue decision process with the use of analytic hierarchy process (AHP). The analysis resulted to a selection among the alternatives that provide the best training venue for pilot training based on the evaluated criteria. It proved the applicability of the AHP when deciding on available alternatives based on set criteria. This study will contribute to the management of training requirements conducted by airlinetraining organizations and help their heads/managers/decision-makers in utilizing decision-making tools and processes when choosing the best alternative among available training resources. © 2023 ACM.

关键词： Accident prevention

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Indonesian-Sundanese Language Machine Translation using Bidirectional Long Short-term Memory Model

Indonesian-Sundanese Language Machine Translation using Bidi...

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2023 International Conference on Computer Science, information Technology and Engineering, ICCoSITE 2023

作者： Heryadi, Yaya Wijanarko, Bambang Dwi Fitria Murad, Dina Tho, Cuk Hashimoto, Kiyota BINUS Graduate Program - Doctor of Computer Science Computer Science Department Bina Nusantara University Jakarta11480 Indonesia BINUS Online Learning Bina Nusantara University Computer Science Department Jakarta11480 Indonesia BINUS Online Learning Information Systems Department Bina Nusantara University Jakarta11480 Indonesia Prince of Songkla University Interdisciplinary Graduate School or Earth System Science and Andaman Natural Disaster Management Phuket83120 Thailand

ISBN: (纸本)9798350320954

Translating a language to another language has become instrumental when peoples interact with other people who speak a different language. However, the language translation is not an easy computation task when there is a language-resource gap. This paper presents empirical results on the performance of two models: the Long Short-term Memory and the Bidirectional Long Short-term Memory models as machine language translation models involving Bahasa Indonesia and the Sundanese language. The empiric results showed that the Bidirectional Long Short-term Memory model achieves higher performance as a language translator from the Sundanese language to Bahasa Indonesia and vice versa (0.95 and 0.95 average training accuracy respectively;and 0.90 and 0.89 average testing BLEU scores respectively) than the Long Short-term Memory model as a language translator from the Sundanese language to Bahasa Indonesia and vice versa (0.93 and 0.92 average training accuracy respectively;and 0.91 and 0.88 average testing BLEU scores). These results validate some previously reported studies that claim the Bidirectional Long Short-term Memory model potentially outperform the Long Short-term Memory model when it is used to process a sequence dataset. © 2023 IEEE.

关键词： Computational linguistics

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