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3rd International Conference on Computing and Applied Informatics 2018, ICCAI 2018

作者： Betty Yel, Mesra Sfenrianto, Sfenrianto Wang, Gunawan Faculty of Computer Science STIKOM CKI Jakarta Indonesia Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia

Understanding learning culture based on learning activities is important for learning success in an e-Learning. As an effort that can be done for this purpose, it is necessary to build a student learning culture based on students activities. The study proposes a Cultural Framework for Learning in an E-Learning. It is called E-LEEP Culture because used in an e-Learning the Equality Education program (E-LEEP). This framework has five key components, namely: Students, E-LEEP, Learning Activities, Learning Culture, and Digital Contents. Learning culture component in E-LEEP Culture Framework consists of sharing activities, getting information, discussingIndividualistic Learning, Collaborative Learning, Learning Time (learn a little), and Learning Time (learn a lot). Each of the components is expected as a basis for providing learning material that suits the needs of students. © 2019 Published under licence by IOP Publishing Ltd.

关键词： E-learning

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Resource-Constrained Project Scheduling Problem using Firefly Algorithm 3

Resource-Constrained Project Scheduling Problem using Firefl...

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3rd International Conference on computer science and Computational Intelligence, ICCSCI 2018

作者： Kassandra, Tiffany Rojali Suhartono, Derwin Mathematics Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

This research discusses house construction project scheduling which is classified as resource-constrained project scheduling problem with fuzzy trapezoidal number expressing optimistic and pessimistic view of activity duration. Parallel schedule generation scheme is used to generate feasible scheduling solutions, while firefly algorithm is used to find optimal solution by updating priority value of each activity. A web-based application is developed to run the scheduling simulation. Scheduling simulation is conducted to determine the optimal parameter values for firefly algorithm and minimum project makespan. The optimal firefly algorithm parameter values are 10 for light absorption coefficient value, 10 for firefly population, 100 for maximal iteration, and 0.8 for random parameter. With 6 structure resources and 12 finishing resources available for construction project, the minimum project makespan value is [110, 142, 167, 224] with fuzzy magnitude value of 213.583. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Scheduling

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Face recognition system Using Deep Neural Network with Convolutional Neural Networks 3

Face recognition system Using Deep Neural Network with Convo...

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3rd International Conference on Computing and Applied Informatics 2018, ICCAI 2018

作者： Fernando, Erick Andwiyan, Denny Fitria Murad, Dina Touriano, Derist Irsan, Muhamad Information System Department School of Information Systems Bina Nusantara University Indonesia School of Information Technology Indonesia Information System Department Binus Online Learning Bina Nusantara University Indonesia Information Technology Department Faculty of Computer Science and Engineering University of Adi Wangsa Indonesia

Face recognition has long been a hot topic and challenging research point in areas such as image processing, pattern recognition, and machine vision. The face is a biometric feature with the intrinsic nature of a human. So that the face has self-stability, deep individual differences and can be an ideal basis for verification of an identity. In this research use, Deep Learning Network method uses to perform detection or face recognition. In this study, we present a framework that can be used to detect faces. This research is also able to present a DNN model that is used to study data sources from the data stream in sequence. The most important part of this study is able to adjust the capacity of the model from the simple one. This research uses experimental design method. The first step is a collection of face image data. Then the architecture design starts from the determination of the depth of the network, layout layers, and the selection of layer types that will be used to get the model based on input dataset and label name index. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Face recognition

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A Fuzzy Goal programming Model for Production Planning in Furniture Company 3

A Fuzzy Goal Programming Model for Production Planning in Fu...

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3rd International Conference on computer science and Computational Intelligence, ICCSCI 2018

作者： Komsiyah, Siti Meiliana Centika, Hasegaf Ekaputera Mathematics Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

In the industrial world, there is always a problem of supply chain and always be for a long time. Production planning is one of its stages. Almost all of companies want to make production process efficient and optimized with minimum expenses while still meet with the market demand. This paper present production planning problem in furniture company with different operational constraint, including production time, warehouse capacity, and quantity of raw materials. The fuzzy goal programming applied to maximize the profit, minimize the production cost and minimize raw materials cost. In this paper was conducted at the furniture company CV. Arte Jaya which aims to help company for decision making regarding to production planning model by using fuzzy goal programming. This Method is suitable for CV. Arte Jaya because the objective function can be adapted to preferences of the company. The result obtained application program for solving decision making problem about the amount of production that is exact and still meet with the market demand. The application program that has been created is able to simplify the user's performance of CV. Arte Jaya. © 2018 The Author(s).

关键词： Decision making

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Improving Rice Productivity in Indonesia with Artificial Intelligence

Improving Rice Productivity in Indonesia with Artificial Int...

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International Conference on Cyber and IT Service Management (CITSM)

作者： Nicholas Liundi Aditya Wirya Darma Rivaldi Gunarso Harco Leslie Hendric Spits Warnars School of Information Systems Bina Nusantara University Jakarta Indonesia School of Computer Science Bina Nusantara University Jakarta Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

Indonesia is one of the biggest agriculture countries in the world with one of its major commodities, rice. Despite its vast paddy field and tropical resources, Indonesia still has not achieved food security. This paper explores ideas about how to present artificial intelligence that may increase rice productivity in Indonesia. Current situations of rice cultivation are mentioned start from existing technologies and systems used in Indonesia. Some artificial intelligence concepts are also introduced. Artificial Intelligence use in rice farming is then analyzed which ideas may be applicable to increase efficiency further. Those that are already implemented in rice farming include diseases and pest detection, prediction and estimation, and automated intelligent systems. In the proposed idea section, ideas to increase production are explored. Using advanced technologies may not be suitable for Indonesia's rice farmers. One argument is to minimize the differences in rice yield in different areas or so what we called yield gap. Factors such as weather, water, and harvest date are those with most impacts on the yield gap. It is beneficial to have a model that can predict the optimal planting date of rice since that will maximize the factors before. Among those implemented, a planting calendar prediction on rice-based on rainfall is already developed. However, rainfall is not the only factor. El-Nino occurrences and temperature changes also have a role in deciding when best to plant rice. The author suggests adding those two new variables, making three in total to the earlier neural network model may improve the overall result.

关键词： Artificial intelligence Diseases Meteorology Agriculture Productivity Artificial neural networks

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A Strategy using Social Media to Increase Students Engagement in E-Learning for the Equivalency Education program (E-LEEP) 3

A Strategy using Social Media to Increase Students Engagemen...

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3rd International Conference on Computing and Applied Informatics 2018, ICCAI 2018

作者： Betty Yel, Mesra Sfenrianto, Sfenrianto Wang, Gunawan Fajar, Ahmad Nurul Faculty of Computer Science STIKOM CKI Jakarta Indonesia Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia

Social media can be used to support learning activities in non-formal education. The utilization of social media by students can be seen as a strategy to improve the students' engagement in e-Learning. It is an important goal for the e-Learning of non-formal education. This study aims to propose a strategy using social media to increase students engagement in E-Learning for the Equivalency Education program (SosMed E-LEEP strategy). This strategy has several key components. These components are students, social media, E-LEEP, and Students Engagement. SosMed E-LEEP Strategy consists of sharing activities, getting information, discussing, and interacting with students and Tutor, and for learning purpose. Each of these strategic activities is expected to improve students engagement, namely: access to learning materials, forum discussion activities, and assignment uploading. © 2019 Published under licence by IOP Publishing Ltd.

关键词： E-learning

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Text Encryption in Android Chat Applications using Elliptical Curve Cryptography (ECC) 3

Text Encryption in Android Chat Applications using Elliptica...

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3rd International Conference on computer science and Computational Intelligence, ICCSCI 2018

作者： Natanael, Dimas Faisal Suryani, Dewi Mathematics Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Information technology is an important aspect of human life that has provided comfort and ease in communicating. The most used communication technologies today is the smartphone, which is a mobile phone with the ability of a portable computer. Currently, to communicate each other, people feel more convenience using chat application in a smartphone than calling or short message services (SMS) features. Some of the advantages of chat application are there is no message size limitations, highest number of consumers use it;especially younger demographics,and it also works on mobile web without application download. Due to the convenience of communication using chat apps increases, the security demands are also higher, i.e., a proper cryptography scheme is needed to protect the messages. In this paper, we implement ECC algorithm to secure text message in messaging application of a smartphone. We will adopt the method proposed by Singh1 to create a chat application in Android program that equipped end-to-end encryption. We also give the experimental result of our chat apps performance such as the accuracy of the received text message, average encryption and decryption time. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Smartphones

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A Model of Visual Intelligent System for Genus Identification of Fish in the Siluriformes Order

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IOP Conference Series: Earth and Environmental science 2021年第1期794卷

作者： Taufik Budhi Pramono R Ardharyan Islamy Saprudin Joni Johanda Putra Teddy Suparyanto Kartika Purwandari Tjeng Wawan Cenggoro Bens Pardamean Aquaculture Study Program Faculty of Fisheries and Marine Science Jenderal Soedirman University Purwokerto Central Java Indonesia 53123 Aquatic Resources Management Brawijaya University Malang East Java Indonesia Graduate Program Aquatic Resources Faculty of Fisheries and Marine Science Jenderal Soedirman University Purwokerto Central Java Indonesia 53123 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Ambiguity in the fish naming is present in several fish species database, especially for fish in Siluformes order. To fix the ambiguity, a visual intelligent system is needed to automate the fish naming correction in the database. In this study, we developed a deep-learning-based model as the core of the intelligent system. The proposed model achieved 89% accuracy for the classification of three genera in Siluformes order: Mystus, Hemibagrus, and Glyptothorax.

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Mobile Application for Tire Sensor as Implementation Internet of Things in Transportation

Mobile Application for Tire Sensor as Implementation Interne...

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International Conference on Cyber and IT Service Management (CITSM)

作者： Bravio Pranatta Jonathan Carstensz Michael Jihanda Nicholas Liundi Diana Teresia Spits Warnars Harco Leslie Hendric Spits Warnars School of Computer Science Bina Nusantara University Jakarta Indonesia School of Information System Bina Nusantara University Jakarta Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

This paper headed to the role of the Internet of Things in transportation life and as one of an important thing, the Internet of Things (IoT) is getting grow and grow every day. Slowly but sure, IoT enters our experience in all things. Different visions of this IoT are reported and enabling technologies reviewed. What appears is that still significant issues must be faced by the research community. The technology that relates to IoT is still in development until now, and soon it will be used in human life. IoT embraced people to bring welfare and efficiency for every activity, played the role of technology development; IoT also shows people to think and invent more technology for every application such as vehicle and smart cities. Once it was implemented, the IoT will bring efficiency and make the activity more comfortable than before. The development of IoT also creates a vision for everybody, because it opens people's minds to technology development. Smart transportation will also be implemented in every city, and soon it will become a smart city. The efficiency and human development will pay the resources, technologies, contributions, and all works from scientists and researchers with transportation.

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Named-Entity Recognition for Indonesian Language using Bidirectional LSTM-CNNs 3

Named-Entity Recognition for Indonesian Language using Bidir...

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3rd International Conference on computer science and Computational Intelligence, ICCSCI 2018

作者： Gunawan, William Suhartono, Derwin Purnomo, Fredy Ongko, Andrew Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

In this paper, we describe the implementation of Named-Entity Recognition (NER) for Indonesian Language by using various deep learning approaches, yet mainly focused on hybrid bidirectional LSTM (BLSTM) and convolutional neural network (CNN) architecture. There are already several developed NERs dedicated to specific languages such as English, Vietnamese, German, Hindi and many others. However, our research focuses on Indonesian language. Our Indonesian NER is managed to extract the information from articles into 4 different classes;they are Person, Organization, Location, and Event. We provide comprehensive comparison among all experiments by using deep learning approaches. Some discussions related to the results are presented at the end of this paper. Through several conducted experiments, Indonesian NER has successfully achieved a good performance. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Long short-term memory

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