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International Conference on Information Management and Technology (ICIMTech)

作者： Hendro Nindito Meyliana Harjanto Prabowo Achmad Nizar Hidayanto BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Computer Science University of Indonesia Jakarta Indonesia

ISBN: (数字)9781728170718

ISBN: (纸本)9781728170725

Indonesia is a country that consists of islands and has various ethnic groups and customs in it. This condition causes Indonesia to have cultural heritage that must be maintained. On the one hand, the rapid advancement of computing technology has affected all aspects of life including the cultural field. This Systematic Literatur Review aims to determine the use of adoption technological or computing that are widely applied by cultural observers in Indonesia in order to maintain the heritage of the nation's ancestors. Published articles used in this research came from the process of filtering in five online databases based on a keyword search pattern then carried out with a content analysis process, the results filtered out as many as 25 relevant articles. The next process is to analyze the content of articles in the role of ICTs that are relevant to preserve cultural heritage. The findings contribute to a better understanding on recent research in cultural heritage and adoption of technologies to maintain cultural heritage in Indonesia.

关键词： Cultural differences computer science Information systems Databases Buildings Global communication Education

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The Design of Smart Cashless Transaction 2020

The Design of Smart Cashless Transaction

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5th International Conference on Intelligent Information Technology, ICIIT 2020

作者： Fernando, Anthony Bryan Shreevasta Desprianto, Ferry Gaol, Ford Lumban Oktavia, Tanty Mobile Application and Technology-School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Program-Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Department-School of Information Systems Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781450376594

Cashless Transaction describes as a state where financial transactions are not bound by physical form such as banknotes or coins, but rather trough transfer of digital information (electronic representation of money). Cashless Transaction exists because of fast majorities of human transaction evolved towards digital environment, this creates an opportunity where legal money exists, recorded, and exchanged in digital form. Thus cashless transaction will make less effort in currency operation cost, keep on track with expenses, connected anytime everywhere as long as connected with internet, and eliminates the needs of banknotes or receipt. Cashless Transaction have done over the past few years making life easier by reducing a number of objects to merge into 1 functional object that could make payments faster and simpler starting with check the first mark of cashless transaction that's still being used nowadays, but cashless transaction doesn't stop evolving in this modern era where money is demonetized, cashless transaction is moving into the digital grid resulting a breakthrough mobile wallets and online transfer that offers people flexibility because its technology advancement makes it possible to make payments anytime and anywhere since it's only depend on a secure network(internet) and a platform, therefore cashless transaction could be done as fast as possible saving precious time. Cashless transaction has some of key components such as security, UX, Functionality, Performance and Data Integrity. Five key components could make cashless transaction become reality but also poses a different threat to cashless transaction. Hacking is one of them. Hacking could be done by anyone that have the ability to compromise the transmission, the transmission needs to have more data protection thus the cashless transaction could be done safely and free of risk. © 2020 ACM.

关键词： Personal computing

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Weight-dropped long short term memory network for stock prediction with integrated historical and textual data

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2020年第3期47卷 367-377页

作者： Thayogo Wibowo, Antoni Computer Science Department Binus Graduate Program-Master of Computer Science Bina Nusantara University Indonesia

Investors and traders need an accurate stock prediction model to help them make decisions. They can use deep learning models such as Long Short-Term Memory Network (LSTM). However, a weakness of LSTM is that it tends to overfit to the training data and have unstable results. To overcome this weakness, this paper proposes using Averaged Stochastic Gradient Descent and Weight-Dropping on an LSTM network (AWD-LSTM). The proposed model regularizes the network by weight-dropping with DropConnect and optimizes the training process using a Non-Monotically Triggered Averaged Stochastic Gradient Descent (NT-ASGD). Additionally, this paper tested with integrating historical data with textual data which was shown to be valuable by other studies. This paper evaluated six variants of the model with different regulizers, optimizers, and data. The results show that (1) DropConnect regulizer performed better than DropOut or No Drop;(2) Adam optimizer is better for stock prediction than NT-ASGD;(3) Adding textual data slightly increases performance;(4) The models were able to gain consistent profits in a market simulation;(5) A variant of the model outperformed a previous study in 4 out of 5 indexes. © International Association of Engineers.

关键词： Optimization

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The Role of Financial Technology for Development of Micro, Small and Medium Enterprises (Msmes) in Indonesia 11

The Role of Financial Technology for Development of Micro, S...

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11th International Conference on Communication and Network Security, ICCNS 2021

作者： Meiryani, Meiryani Hanna Uli Pakpahan, Noviyanti Wahyuningtias, Dianka Mad Daud, Zaidi Liawatimena, Suryadiputra Accounting Department Faculty of Economics and Communication Bina Nusantara University Jakarta11480 Indonesia Hotel Management Department Faculty of Economics and Communication Bina Nusantara University Jakarta11480 Indonesia Accounting Department Faculty of Economics and Business Universiti Putra Malaysia Malaysia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781450386425

The rapid development has made financial technology/financial technology's innovations more diverse according to the needs and financial problems that arise. With the existence of financial technology (financial technology) it can also make the financial service process faster, more effective and easier. Because of the development in the field of financial technology with the various solutions offered, this study aims to examine the role of financial technology for the development of MSMEs (Micro and Medium Enterprises), this research also includes aspects of the role of financial inclusion for the development of MSMEs to be able to see how much public knowledge is about financial service products and risk knowledge. The case study in this research is MSMEs in the Tangerang area using quantitative methods. The results of research using multiple linear regression analysis found that the role of financial financial technology for the development of MSMEs has a significant positive effect. Meanwhile, financial inclusion for the development of MSMEs has a positive and insignificant effect on the dependent variable. This study concludes that the use of financial technology for MSME businesses, as well as the high reference to financial products, are important factors in encouraging the development of MSMEs. © 2021 ACM.

关键词： Linear regression

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Application internet of things in healthcare Covid-19: A systematic review

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AIP Conference Proceedings 2023年第1期2594卷

作者： H. Citrawati G. P. L. Barnabas T. A. Santoso Suharjito Computer Science Department BINUS Graduate Program -Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480

Coronavirus, or Covid-19, is a new virus first discovered in Wuhan, China, at the end of 2019. This virus attacks the human respiratory area, which can cause respiratory problems and even loss of life. Covid-19 virus transmission is also high-speed and very easy; it is transmitted through airborne and human droplets. Therefore, to reduce the transmission rate of this virus, several researchers revealed that social distancing is one way to suppress the transmission of the Covid-19 virus. In the era of technology, The Internet of Things (IoT) is one of the systems that can help to solve this problem. The Internet of Things (IoT) cancan use one or more devices connected to the network, and it can exchange data and information effectively and efficiently. In this study, the researchers review several IoT technologies that can be used to detect COVID-19 symptoms and implement social distancing rules based on the latest literature. The review results show that IoT technology has been used to monitor the progress of COVID-19 patients in real-time with various sensors connected to geographic positioning systems, mobile devices, and cloud computing. Several research proposals for the development of IoT technology have been identified, such as the detection of COVID-19 patients in crowds, prediction of the spread of the virus in an area, and implementation of health protocols in various crowded locations.

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Proposed Autonomous Vehicle Framework for Safe Driving 7

Proposed Autonomous Vehicle Framework for Safe Driving

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7th International Conference on Cyber and IT Service Management, CITSM 2019

作者： Winoto, Amadeus Suryo Kristianus, Michael Linardi, Brandon Warnars, Harco Leslie Hendric Spits School of Computer Science Computer Science Department Indonesia BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728129099

The proposed idea to improve the usage of an autonomous vehicle to increase safe driving based on the DARPA project, which already has shown the bright future of the autonomous vehicle. This paper proposes a new idea regarding the sensors and the autonomous vehicle framework, such as the usage of some algorithms and new UI along with the data logger. Moreover, the use of a LIDAR sensor is extended, along with a stereo camera and also ultrasonic sensor to make it more precise. Then, a calibration system is made for the stereo camera, which will take help from the ultrasonic sensor. Not the only ultrasonic, camera, and LIDAR, and IMU and GPS sensor are used to know the angle of x, y, and z of our vehicle. Both IMU and GPS are helping in the perception and mostly in the RNDF Localization that will be used in the pathfinding, planning, and control. The global Dynamic-Window approach is applied for the path selection algorithm and combining it with the Autonomous System Approach. The speed selection algorithm will decide on the speed limit and the camera. Not only that but the implement the Inter-Vehicle Algorithm is implemented, which makes the vehicles can exchange information with the other vehicles in the radius of the vehicle. Which all of this together can make a safer driving environment, not only for cars but another vehicle as well. Hope this framework can be used for any other vehicle project and becoming the base of all autonomous vehicle. © 2019 IEEE.

关键词： Optical radar

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Genome data mining approach to identify potential protein in crop plants

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AIP Conference Proceedings 2024年第1期3026卷

作者： Joko Pebrianto Trinugroho Faisal Asadi Bens Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

There is a need to produce more crop plants to meet the future global demand. However, the climate change has affected the global crop yield. Consequently, finding an alternative approach to improve crop yield becomes essential. The development of sequencing techniques, as well as information technologies, have enabled us to perform genome data mining. Using genome data mining approach, it is possible to identify or discover a protein which has a particular characteristic. This study aims to identify a protein, which could potentially improve crop yield, using genome data mining approach. D1 protein was used as the target, as this protein is highly involved in photosynthesis. Then, protein sequences of various crop plants were collected from biological database. After conducting data trimming and filtering, sequence analysis was performed. The analysis was used to construct phylogenetic tree and create a 3D protein model. Sequence analysis displayed variation in amino acid sequence in D1 protein. Protein modelling located the variations, which scattered within D1 protein. Furthermore, we highlighted the amino acid residues that are the targets for genetic engineering. The research findings may provide a reference to improve crop production through genome mining approach.

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Web Scraping Methods on Odoo Framework to Collect Rupiah Exchange Rate From Bank Indonesia Website

Web Scraping Methods on Odoo Framework to Collect Rupiah Exc...

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IIAI International Conference on Advanced Applied Informatics (IIAIAAI)

作者： Masmur Tarigan Ford Lumban Gaol Tukoro Matsuo Doctor of Computer Science Graduate Program Faculty of Computer Science Universitas Bina Nusantara Universitas Esa Unggul Jakarta Indonesia Doctor of Computer Science Universitas Bina Nusantara Jakarta Indonesia Graduate School of Industrial Technology Advanced Institute of Industrial Technology Japan Asia University Taiwan

ISBN: (纸本)9781665424219

The foreign currency exchange rate against the rupiah in the Odoo ERP framework system accommodates multi-currencies. However, Odoo has not updated the rupiah exchange rate based on the value from Bank Indonesia regularly. The exchange rate is the price at which one country's currency can be exchanged for another country's currency. The rupiah exchange rate in business has an influence on the cost revenue as well as the profit of the Indonesian company. The problem is updating the rupiah exchange rate must be done manually by looking at the exchange rate on the Bank Indonesia website and entering it into the ERP system according to the current date. The Rupiah exchange rate in foreign currencies needs to be updated regularly by Bank Indonesia exchange rates. To collect rupiah exchange rate uses the Odoo Framework ERP system using the web scraping methods to extract data from Bank Indonesia exchange rates, the library used in scraping is Beautiful Soup. Beautiful Soup is a Python package for parsing HTML and XML. Is used to extract data from HTML, which is useful for web scraping. Rupiah exchange rate updates will be scheduled by the system every day at 12.30 p.m. GMT+07.

关键词： Manufacturing industries Exchange rates Schedules Supply chain management XML Libraries Data mining

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Corrigendum to “Oil palm fresh fruit bunch ripeness classification on mobile devices using deep learning approaches” [Comput. Electron. Agric. 188 (2021) 106359]

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computers and Electronics in Agriculture 2023年 207卷

作者： Gregorius Natanael Elwirehardja Jonathan Sebastian Prayoga Suharjito Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Online Learning Bina Nusantara University Jakarta 11480 Indonesia

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Classification of Hotel Customer Based on Support Vector Machine

Classification of Hotel Customer Based on Support Vector Mac...

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International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA)

作者： Choirul Huda Yaya Heryadi Lukas Wayan Suparta Antoni Wibowo Computer Science Department Doctor of Computer Science Graduate Program Bina Nusantara University Jakarta Indonesia Computer Science Department Bina Nusantara University Jakarta Indonesia Computer Engineering Research Group (CERG) Atma Jaya University Jakarta Indonesia Computer Science Department Graduate Program Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665499705

The tourism industry has contributed positively for regional and global economic income in recent years. Although this sector faces a hard challenge in COVΓD-19 pandemic, it has been predicted that it will rebound and will continue in growing as in previous periods. Tourist experience should become important to be improved regarding the service level for visitors such as the improvement of hotel customer accommodation. The aim of this study is classifying the hotel customer based on Support Vector Machine (SVM). This classification conducted through classification of satisfaction level and the related factors. The result of the study presented a good accuracy and precision of SVM in conducting customer hotel classification at 93% accuracy level with error level of prediction result for about 0.27 based on Root Mean Squared Error (RSME) function. The features of customer satisfaction at this study are proposed to be important preferences for improvement of customer services in hospitality.

关键词： Support vector machines Economics Mechatronics Pandemics Tourism industry Europe Machine learning

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