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Emerging Smart Computing and Informatics (ESCI), Conference on

作者： Nizirwan Anwar Wesley Rico Darmawan Gian Wellrich Nathaniel Pranata Sutajaya Muhamad Ali Furqon Harco Leslie Hendric Spits Warnars Faculty of Computer Science Esaunggul University Jakarta Indonesia School of Information Systems Bina Nusantara University Jakarta Indonesia Civil Service Police Unit Tangerang Indonesia KelurahanCimone Jaya Kota Tangerang Tangerang Indonesia BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728185194

ISBN: (纸本)9781728185200

These days, Indonesia has entered the era of Industry 4.0 which is marked by the development of all-digital technology and automation. With the increasing rate of technology development that changes people's lives, people are becoming fond of anything fast and instant. With the help of these technological advancements, we create an application that makes it easier for users that are willing to hold events. This application connects 2 entities, which are users and an event organizer. The event organizer can easily find their market and other hands easy as well for the user for finding the market for event organization activities. The business processes in this application were designed with a use case diagram, and the tables in the database were designed with the class diagram and the menu of the application with User Interface (UI). However, this proposed application just only an introduction and needs to be explored for those who are interested to explore entrepreneurship in these areas.

关键词： Organizations User interfaces Mobile applications Reliability Artificial intelligence Informatics Recommender systems

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Research Square

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Research Square 2020年

作者： Gaol, Ford Lumban Matsuo, Tokuro Computer Science Department BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Advanced Institute of Industry Technology Tokyo Japan

Introduction: Social Big data is generated by interactions of connected users on social network. Sharing of opinions and contents amongst users, reviews of users for products, result in Social Big data. If any user intends to select product such as movies, books etc. from e-commerce sites or view any topic or opinion on social networking sites, there are a lot of options and these options result in information overload. Case Description: Social recommendation systems assist users to make better selection as per their likings. Recent research works have improved recommendation systems by using matrix factorization, social regularization or social trust inference. Furthermore, these improved systems are able to alleviate cold start and sparsity but not efficient for scalability. Discussion and Evaluation: The main focus of this paper is to improve scalability and provide better recommendations to users with large-scale data in less response time. We have partitioned social big graph and distributed it on different nodes based on Mahout and PowerGraph like system. Conclusion: In our approach, partitioning is based on direct as well as indirect trust between users and comparison with state-of-the-art approaches proves that statistically better partitioning quality is achieved using our approach. In our proposed approach ScaleRec, hyperedge and transitive closure are used to enhance social trust amongst users. Experiment analysis on standard datasets proves that better locality and recommendation accuracy is achieved by using our proposed approach. © 2020, CC BY.

关键词： Data Analytics

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Fuzzy water flow algorithm (FWFA) based ecological decision support model (ecoDSM) for flood control operating system

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AIP Conference Proceedings 2023年第1期2896卷

作者： Ditdit Nugeraha Utama Rachmat Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Intiland Development Jakarta Indonesia 10220

Flood disaster happens periodically in Jakarta. One opportunity that can be maximized to mitigate it is control management of the Manggarai water gate (MWG). The MWG itself is placed in the Ciliwung river in one district of the capital Jakarta. It has a vital role to minimize the impact of flood disasters in Jakarta. The study is a further version of previous research indeveloping a water-flow-like algorithm (WFA) based decision support model (DSM) to mitigate the impact of flood disasters. Theconstructed DSM is practically functioned to control the operation of opening/closing the MWG. The DSM was constructed by combining the previous WFA model with the concept of fuzzy logic (FL). The constructed model is called Fuzzy-WFA (FWFA) ecological DSM (ecoDSM); as it considers several aspects of ecology, e.g. river condition, weather situation, and flood itself. By building the FWFA-ecoDSM, the value of uncertainty can be converted to become crisp logic that is easier to understand. At the end of this research, the FWFA-ecoDSM was implemented in more detail compared with the previous one by producing the decimal numbers with 3 until 6 numbers behind the point; exclusively, in predicting the water level status, where the status used todecide the opening/closing level decision for opening or closing the MWG.

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Data annotation system for intelligent energy conservator in smart building 3

Data annotation system for intelligent energy conservator in...

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3rd International Conference on Eco Engineering Development, ICEED 2019

作者： Pardamean, Bens Cenggoro, Tjeng Wawan Chandra, Bloomest Jansen Rahutomo, Reza Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department College of Letters and Science University of Wisconsin MadisonWI53706 United States Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia

The concept of smart building includes the optimization of energy usage in a building. One of the possible solutions for this is to adaptively adjust appliances utilization according to activity level in the building. Thus, an intelligent activity estimation system needs to be developed. However, massive annotated dataset is necessary to train the system. Therefore, we propose a system that enables rapid data annotation to collect the massive dataset. With the proposed system, an image can be annotated within 4.8 seconds in average. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Historic preservation

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Deep Learning with Greedy Layer-Wise Compound Scaling for Temperature and Humidity Prediction in Solar Dryer Dome

SSRN

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SSRN 2022年

作者： Cenggoro, Tjeng Wawan Elwirehardja, Gregorius Natanael Dominic, Nicholas Setiawan, Karli Eka Rahutomo, Reza Djuana, Endang Gunawan, Fergyanto E. Budiman, Arief S. Romeli, Sugiarto Pardamean, Bens Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta11440 Indonesia Industrial Engineering Department BINUS Graduate Program Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Department of Manufacturing and Mechanical Engineering and Technology Oregon Institute of Technology Klamath FallsOR97601 United States PT. Impack Pratama Industri Jakarta Indonesia

Drying has been an eco-friendly and cost-efficient method to reduce post-harvest losses of agricultural crops. In various countries, the technique has been widely utilized in the form of Solar Dryer Dome (SDD) buildings. Accurate indoor microclimate forecasting is very important to implement smart control systems in SDDs that can maintain the ideal conditions, as the availability of solar energy is limited only at daytimes and the temperature may drop significantly during nighttimes in remote areas. The microclimate variables that play an important role in maintaining ideal environmental conditions include temperature and relative humidity. © 2022, The Authors. All rights reserved.

关键词： Forecasting

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K-Means Clustering Model to Discriminate Copper-Resistant Bacteria as Bioremediation Agents

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Procedia computer science 2021年 179卷 804-812页

作者： Ika Nurlaila Wahyu Irawati Kartika Purwandari Bens Pardamean Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480 Department of Biology Education Faculty of Education Pelita Harapan University Tangerang Indonesia 15811 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Copper (Cu) has been excessively used for some valuable commodities and this creates environmental problems. The inorganic element becomes toxic when presents beyond the recommended tolerated concentration. Bacterial-based remediation is seen to be an excellent tool to overcome it as it reduces the copper contamination without yielding any other forms of contamination. There are some pivotal properties in the bacteria render them being considered as bioremediation agents against coppers contamination, namely bioaccumulation and biosorption. In the present study, we question if these bacteria could be clustered into a strong and representative proximity according to their functional properties. Mostly, bacteria are grouped based on their genetic profiles derived from the 16S rRNA sequencing. We propose that our K-Means clustering model can be employed to identify genetically-unlabelled bacteria. But first, a prominent reference should be developed and we are in this phase. We figured out the K-Means clustering model do not pull the same-genus bacteria into the same cluster. Instead, the model gathers into a proximity those isolates with similarity on a functional characteristic termed minimum inhibitory concentration (MIC), regardless their origins and their hierarchy in taxonomy.

关键词： Copper-Resistant Bacteria K-Means Minimum Inhibitory Concentration

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A Literature Review: Drug Supply Chain and Neural Networks

A Literature Review: Drug Supply Chain and Neural Networks

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International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)

作者： Gunadi Emmanuel Meyliana Achmad Nizar Hidayanto Harjanto Prabowo Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Fakultas Sains dan Teknologi Unika Katolik Musi Charitas Palembang Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Faculty of Computer Science Universitas Indonesia Depok Indonesia Management Departement BINUS Business School Undergraduate Program Bina Nusantara University Jakarta Indonesia

The drug supply chain is an important variable that will be asked when there is a shortage of drugs. The distribution and storage of drugs require accurate predictions to support the drug supply chain. Many methods have been studied to obtain a high level of prediction accuracy. One of the methods used is an artificial neural network to recognize the pattern of drug demand. It is important to find breakthroughs in artificial neural network technology to anticipate drug shortages. This study seeks to identify and find challenges from previous research in drug supply management and drug demand prediction by utilizing neural networks over the past five years. From the seven sources used, 34 articles were selected based on inclusion criteria and keyword searches according to Kitchenham's systematic review methodology. The discussion areas of the selected articles are 29% in the Logistics and Inventory area, 20% Risk - Resilience, and 18% for Drug supply chain planning which is a description of the research development area. Integrated development provides room for the use of neural networks in these three correlated areas. The model for implementing neural networks in maintaining the continuity of drug shortages is always associated with policies adopted by all drug supply chain stakeholders to anticipate drug shortages.

关键词： Drugs Training Systematics Supply chains Artificial neural networks Prediction algorithms Planning

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Next Generation Firewall for Improving Security in Company and IoT Network

Next Generation Firewall for Improving Security in Company a...

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2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019

作者： Soewito, Benfano Andhika, Charlie Erwin Bina Nusantara University Computer Science Department BINUS Graduate Program Computer Science Jakarta Indonesia

ISBN: (纸本)9781728137490

The goal of this research is to analyze of effectiveness the Next Generation Firewall that implemented to secure IoT in smart house and company network. The method used in this research is the method of comparison with a test of DDoS attacks, phishing and SQL Injection on both network, smart house network and company network. From the results of experiment, it can be concluded that the Next Generation Firewall has significantly better performance for protecting smart house and company network, it can increase security of data communication networks against threats from the Internet. © 2019 IEEE.

关键词： Network security

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A Review of Implementation and Obstacles in Predictive Machine Learning Model at Educational Institutions 2

A Review of Implementation and Obstacles in Predictive Machi...

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2nd International Conference on computer, science, Engineering, and Technology, ICComSET 2019

作者： Ranggadara, Indra Sari, Yunita Sartika Dwiasnati, Saruni Prihandi, Ifan Sfenrianto Computer Science Department Mercu Buana University Indonesia Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia

Machine learning is a system that can learn by itself by using training data and testing data testing. In a variety of machine learning research has various obstacles in implementation especially in education institution, in its application, many things need to considered for more information to enrich research in the area of machine learning by way of comparing various obstacles in implementation in similar research. So that in this study is to find similarities and anticipations made in the initial stages of pre-processing to visualisation, as well as the contribution that can give in this study explains the best alternative for researching following the experience of several researchers in conducting machine learning research. © 2020 IOP Publishing Ltd. All rights reserved.

关键词： Machine learning

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A prototype of Baby Monitoring Use Raspberry Pi

A prototype of Baby Monitoring Use Raspberry Pi

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International Conference on ICT For Smart Society (ICISS)

作者： Aldy Rudyansyah Harco Leslie Hendric Spits Warnars Ford Lumban Gaol Tokuro Matsuo BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Graduate School of Industrial Technology Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (数字)9781665404228

ISBN: (纸本)9781665404235

The security system in monitoring the room or something suspicious activity that can cause crimes in the field of information and technology as in private homes is indispensable. Aims to keep valuables from theft and loved ones like babies from kidnapping or reducing the risk of an accident in an unguarded infant activity. The use of CCTV still has constraints because some functions are still done manually such as should always move the record of the CCTV data every day to different memory so that there is waste in using memory. Moreover, the position of the camera can not be adjusted freely in the placement so that it can easily be destroyed by irresponsible people, and also ordinary CCTV needs electricity that is considerable in its use. This research is done to improve and facilitate the process of monitoring of baby activity and the room where the baby is called sleep or rest, all monitoring activities can be done using only a Web browser that can be accessed by a smartphone or desktop. The monitoring system is created using a program called RPi Cam that is installed on the Raspberry Pi with a Raspberry Camera module as a monitoring camera and a DHT22 sensor module as a room temperature monitor.

关键词： Cameras Monitoring Temperature sensors Pediatrics Temperature measurement Security Tools

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