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Development of smart building for better building management in the era of industrial revolution 4.0

AIP Conference Proceedings 2024年第1期3026卷

作者： Wahyu Sardjono Widhilaga Gia Perdana Information Systems Management Department BINUS Graduate Program – Master of Information Systems Management Bina Nusantara University Jl. K. H. Syahdan No. 9 Kemanggisan Palmerah Jakarta 11480 Indonesia Post Graduate Program of Management Science State University of Jakarta Jl. R.Mangun Muka Raya No.11 Jakarta Timur Jakarta 13220 Indonesia

A scaled-down form of smart cities is smart buildings since they have overlapping needs for managing lighting and energy as well as for ensuring the safety and security of their residents. Installing and utilizing cutting-edge, integrated building technology systems constitutes a smart building. These systems include facility management, telecommunications, user systems, and building automation. The benefits of smart buildings include lower expenses for upkeep and energy use, a decrease in emissions, better productivity, more habitable structures, and higher resale value. On the other side, there are also drawbacks, including usability, initial installation expenses, ongoing internet fees, and cyber security issues. The purpose of smart buildings was the main topic of this study, which searched online for literature reviews and other information sources.

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A study on the implementation of green information technology to support the competitive advantage of an environmentally friendly and sustainable company

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AIP Conference Proceedings 2024年第1期2987卷

The Data Center is the center of the company’s data management operations as well as the largest energy consumer to support the operations of information technology infrastructure. Therefore, the company must have a strategy for implementing information systems and information technology related to the data center. The purpose of developing this article is to increase the efficiency of the company’s data center electricity load and help companies move towards green computing that is environmentally friendly. The direct survey method was conducted through interviews with related information technology staff, and field data collection. While the green grid method is used to analyze green Information Technology (IT) and for project appraisal, discounting models are used, namely Net Present Value (NPV) and internal rate of return (IRR). The results of the study prove that the company’s PUE (Power Utilization Effectiveness) and DCiE (Data Center Infrastructure Efficiency) are not efficient. In addition, the company’s data center information technology equipment has inefficient usage, causing waste of electricity costs. The conclusion that can be drawn from this research is that green data centers are able to solve various problems of managing data centers that are environmentally friendly and support sustainable competitive advantages for companies.

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Reshaping marketing in industry 4.0 by artificial intelligence

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AIP Conference Proceedings 2024年第1期3026卷

Industry 4.0 has been revolutionizing the way companies do business from production, development, selling, and distribution of their product. Digital marketing is one of the marks of Industry 4.0; a fusion of technology and marketing as well as proof of how technology has changed the pattern of human life. Artificial intelligence as part of technology products has been implemented in marketing activities from awareness to retention, such as chatbots, programmatic ads, email marketing, and search engines. Users need to understand the patterns and prerequisites needed of each artificially intelligent product to optimize the marketing.

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Implementation of learning management system towards quality education according to sustainable development goals

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AIP Conference Proceedings 2024年第1期3026卷

In the Sustainable Development Goals (SDGs), one of the goals to be achieved in 2030 is quality education. However, the occurrence of the Covid-19 pandemic is a challenge because learning must be carried out remotely so that it has the potential to interfere in achieving these goals. The use of the Learning Management System (LMS) as a distance learning media has increased during the Covid-19 pandemic. LMS is expected to be able to restore the quality of learning during the new normal and after the pandemic. However, there are still many difficulties and dissatisfaction in its implementation. Several dimensions must be considered in the implementation of LMS, such as technology, organizational, Human Resources, organizational environment, and learning content dimension. The implementation of LMS must be planned carefully and according to needs, supported by job holders, adequate understanding and cost planning.

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A tabu search approach with embedded nurse preferences for solving nurse rostering problem

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International Journal for Simulation and Multidisciplinary Design Optimization 2020年第1期11卷

作者： Ramli, Razamin Ahmad, Siti Nurin Ima Abdul-Rahman, Syariza Wibowo, Antoni Department of Decision Science School of Quantitative Sciences Universiti Utara Malaysia Sintok Kedah06010 Malaysia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

This paper presents an intelligent tabu search (TS) approach for solving a complex real-world nurse rostering problem (NRP). Previous study has suggested that improvement on neighborhoods and smart intensification of a TS could produce faster and fitted solution. In order to enhance the TS, this paper introduces an improvement to the neighborhoods and explores on the neighborhoods exploitations of TS to solve the NRP. The methodology consists of two phases: Initialization and neighborhood. The semi-random initialization is employed for finding a good initial solution during the initialization phase which avoids the violation of hard constraints, while the neighborhood phase is established for further improving the solution quality with a special representation and innovative neighborhood generations within TS algorithm. The aim is to move sample points towards a high-quality solution while avoiding local optima by utilising a calculated force value. It is observed that the enhancement strategy could improve the solution quality of the constructed roster. It is concluded that the TS with enhancements approach is able to assign effective and efficient shift duties for the NRP especially when related with real-world working regulations and nurses preferences. © 2020 R. Ramli et al., published by EDP sciences.

关键词： Tabu search

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Optimum Nutrition Intake from Daily Dietary Recommendation for Indonesian Children using Binary Particle Swarm Optimization Algorithm

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Procedia computer science 2019年 157卷 16-24页

作者： Fanny Lili Ayu Wulandhari Sani Muhamad Isa Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department Binus Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Optimum nutrition intake in daily dietary habit has a significant role for children growth. Nevertheless, the mistakenness in the fulfillment of nutrition still concerned. It happens because an individual does not have much knowledge about the energy content of food and food combination to meet the nutrition requirement. The objectives of this research are to facilitate an individual to obtain the optimum nutrition intake from their daily dietary habit. This paper proposes a Binary Particle Swarm Optimization (BPSO) algorithm to find the optimum combination of food portion and food option for an individual daily dietary habit. The food data is obtained from ’Tabel Komposisi Pangan Indonesia ’ book which contains more than 1600 kind of Indonesian food. The results show that BPSO provides an optimum nutrition intake accuracy of 99.14%. Moreover, the nutritionist is already validated that this experiment is succeed in recommending a variation of daily dietary habit that meet an optimum nutrition intake for an individual. Based on this result it can be conducted that BPSO can provide the better accuracy of optimum nutrition intake than Genetic Algorithm (GA), while GA can only provide an optimum nutrition intake accuracy of 97.87%.

关键词： Optimum nutrition Energy requirement Energy intake Dietary habit recommendation Binary Particle Swarm Optimization

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A Blockchain Technology-Based for University Student Enrollment Process

A Blockchain Technology-Based for University Student Enrollm...

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International Conference on Computing, Engineering, and Design (ICCED)

作者： Meyliana Surjandy Erick Fernando Cadelina Cassandra Henry Antonius Eka Widjaja Yakob Utama Chandra Harjanto Prabowo School of Information Systems Bina Nusantara University Jakarta Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

University in Indonesia contemporary is looking for a solution to improve the university documentation such as certificate and transcript. But fake diploma certificate and transcript is an issue reported in several articles recently. The new technology called Blockchain has been elaborate and predicted can be used to solve the issue because of blockchain characteristics which are immutable, secure, tamperproof and unchangeable. The enrollment process is one of the vital process for university before the document can be made. Therefore, the research tries to elaborate deeply to create a model of the university student enrollment process. The research question of this research is how Blockchain Technology can be merge in the enrollment process? The model has been validated by several universities in Indonesia. Forum Group Discussion had been performed to discuss for enrollment process. In the end, many benefits come up from blockchain technology utilization to produce a reliable document such as diploma certificate and transcripts.

关键词： Government Blockchain Documentation Companies Forgery Reliability

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Detection Traffic Congestion Based on Twitter Data using Machine Learning

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Procedia computer science 2019年 157卷 118-124页

作者： Muhammad Taufiq Zulfikar Suharjito Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department Binus Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Twitter is one of the social media with text and image information that can be used as a source of information to detect traffic congestion in real-time. This study developed a system to detect traffic congestion in Indonesia, especially DKI Jakarta. The system displays the direction of the street according to the name of the street being passed and from each of the names of the streets, resulting in a tweet from the classification. The proposed method uses the Support Vector Machine (SVM) classification with the sigmoid kernel. This study shows that the SVM classification with the sigmoid kernel (libSVM) has an accuracy rate of 96.24% and that was increased by 2.68% when compared to SVM dot (mySVM). Based on the evaluation result of the proposed system compare to google maps application on detecting traffic congestion, the system could find a similar condition as many as 17 times from 25 of testing.

关键词： Traffic Congestion Text Classification Support Vector Machine

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A Comparison of Prediction Methods for Credit Default on Peer to Peer Lending using Machine Learning

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Procedia computer science 2019年 157卷 38-45页

作者： Netty Setiawan Suharjito Diana Computer Science Department Binus Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Social lending or peer to peer lending (p2p lending) has emerged as a viable digital platform where lenders and borrowers can do business without the involvement of financial institutions. P2p lending has gained significant momentum recently, with some platform has reached billion-dollar loan circulation. However, p2p lending platforms are not free from any form of risks. A higher return on investment for investor comes with a risk of the loan and interest not being repaid. For this purpose, this research proposes a tree-based classification method for predicting whether a loan will go bad or default before the loan is approved. The high dimensionality of the dataset needs to be processed and chosen carefully. This paper proposes a Binary PSO with SVM to perform feature selection for the dataset and Extremely Randomized Tree (ERT) and Random Forest (RF) as the classifiers. In this research, BPSOSVM-ERT and BPSOSVM-RF are compared with several performance metrics. The experimental results show BPSOSVM can produce subset of features without decreasing the performance from the original features and ERT can outperform RF in several performance metrics.

关键词： P2P lending Random forest Extremely randomized tree PSO BPSO

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Blockchain Technology Open Problems and Impact to Supply Chain Management in Automotive Component Industry

Blockchain Technology Open Problems and Impact to Supply Cha...

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International Conference on Computing, Engineering, and Design (ICCED)

作者： Surjandy Meyliana Hareco Leslie Hendric Spits Warnars Edi Abdurachman School of Information Systems Bina Nusantara University Jakarta Indonesia BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

The study of the adoption of Blockchain Technology (BT) of the Supply Chain Management System (SCMS) automotive components industry still in infancy. BT's previous research topic mostly in virtual currency, security, and IoT. However, the automotive market's significant development causes several issues in the SCMS automotive components industry, such as fake components. Blockchain Technology (BT), as identified, might be possible as a way out for the development of SCMS automotive components. There are several research questions in this research, such as how BT can facilitate SCMS open issues? What is the BT impact in the SCM area? The study method used the systematic literature review (SLR) method to gather all information from 12 publishers and an international index journal. Seven open issues identified in this study and SCM's core operational aspect, such as supplier, logistics, manufacturer, distribution, and customer, have been identified impact with BT.

关键词： Industries Supply chain management Manufacturing processes Systematics Blockchain Tools Security

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