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GIS-Based MCDM for Central Business Suitability in a Small City 5

GIS-Based MCDM for Central Business Suitability in a Small C...

引用

5th International Conference on Informatics and Computing, ICIC 2020

作者： Herlawati, Herlawati Abdurachman, Edi Heryadi, Yaya Soeparno, Haryono Binus Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728180472

Extended urbanization phenomenon in smaller-sized cities in Java should be considered by the government. However, the local governments can only use the plans from the central government. The negative effects of this, among others, are improper land use allocation, lack of facilities, and crimes that are difficult to handle. This study proposes a geographic information system (GIS)-based method to analyze the proper central business district in Karawang, a small district in Java, Indonesia. Multi-criteria analysis of factors affecting the candidate locations was used through a weighted sum method in a model. The spatial data were retrieved and analyzed using a GIS tool to classify region into urban, peri-urban, and rural. Some central business locations have been found after reclassification which is located near the toll gates. Two locations in the north of Karawang were classified have the potential to become the new central business locations. © 2020 IEEE.

关键词： Geographic information systems

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Deep learning and Threshold Probability for Out of Scope Intent Detection in Task Oriented Chatbot 3

Deep learning and Threshold Probability for Out of Scope Int...

引用

3rd International Conference on Artificial Intelligence and Data sciences, AiDAS 2022

作者： Hasani, Muhammad Fikri Gaol, Ford Lumban Soewito, Benfano Warnars, Harco Leslie Hendric Spits Binus Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (数字)9781665491648

ISBN: (纸本)9781665491648

A lot of research on task-oriented chatbots has been carried out to improve research on intent recognition. However, there are not many studies that discuss out-of-scope. This study introduces the use of threshold for classification results. The use of threshold improves recall performance of OOS detection above baseline for BiLSTM but reduces recall inside scope for all models. Directly applying multiclass classification with combined class of inside scope and out of scope also showed higher recall than baseline. © 2022 IEEE.

关键词： Deep learning

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Prediction Diabetes Mellitus Using Decision Tree Models

Prediction Diabetes Mellitus Using Decision Tree Models

引用

2019 International Congress on Applied Information Technology, AIT 2019

作者： Sunge, Aswan Supriyadi Warnar, Harco Leslie Hendric S. Heryadi, Yaya Abdurachman, Edi Soewito, Benfano Gaol, Ford Lumban BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728158624

Health is an essential thing in human life, but Indonesian people are still far from the word healthy lifestyle. One disease that can be caused by an unhealthy lifestyle is diabetes mellitus that can cause many deaths. So far, there are many data in the hospital, but the data can not be maximized well even if it can be used to predict diabetes. The need for accuracy to produce better results. In conducting this test, the results obtained using C 4.5 only algorithm is 72.08%. © 2019 IEEE.

关键词： Data mining

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Neural Network and Resampling to Handle Imbalance Class on Estimate Software Defect 15

Neural Network and Resampling to Handle Imbalance Class on E...

引用

15th International Congress on Advanced Applied Informatics Winter, IIAI-AAI-Winter 2023

作者： Setiawan, Tri Agus Soeparno, Haryono Gaol, Ford Lumban Arifin, Yulyani Bina Nusantara University Binus Graduate Program - Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350383829

Rapid progress in the field of artificial intelligence has created opportunities for extensive applications in software development. One area that receives attention is the evaluation of code quality using machine learning techniques. In this investigation, we examined the possible application of machine learning to predict the likelihood of defects in computer code. We employ NASA archival data as case studies. Machine learning models employ neural network algorithms. Our exploration involves partitioning the dataset into training data and test data for performance evaluation. The findings indicate that the Neural Organize technique with resampling yields a high level of accuracy in predicting software defects. Our simulated neural network is capable of identifying intricate patterns in the data and providing precise measurements of the size and intensity of defects. These results have significant implications in the software business, enabling developers to promptly identify possible vulnerabilities and take preventive measures before product release. © 2023 IEEE.

关键词： Machine learning

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Analyzing the Impact of Service Design on Maintainability Factor in Microservices Architecture 15

Analyzing the Impact of Service Design on Maintainability Fa...

引用

15th International Congress on Advanced Applied Informatics Winter, IIAI-AAI-Winter 2023

作者： Gintoro Gaol, Ford Lumban Soeparno, Haryono Arifin, Yulyani Binus Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350383829

Applications designed utilizing Microservices Architecture (MSA) provide the desirable trait of good maintainability. To ensure optimal maintainability, it is important to provide services that are suitable and adhere to prescribed rules. Multiple aspects must be taken into account while designing services to ensure optimal maintainability. The objective of this study is to examine the elements that impact the capacity to sustain and improve maintainability in service design, ultimately resulting in an application that possesses strong maintainability. The Systematic Literature Review (SLR) will be utilized to identify variables and strategies for their enhancement, by examining pertinent publications on the subject. After examining 45 publications, the study discovered 8 elements and 14 solutions that can enhance the highlighted parameters throughout the services design process. The outcomes of this systematic literature review (SLR) are anticipated to give valuable insights to application developers, empowering them to generate service designs that exhibit commendable maintainability for the developed applications. © 2023 IEEE.

关键词： Maintainability

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Identification of Clustering BRISK Keypoint Feature in Grocery Product Using the Elbow Method

Identification of Clustering BRISK Keypoint Feature in Groce...

引用

2024 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2024

作者： Rahmania, Rissa Anggreainy, Maria Susan Kartowisastro, Iman Herwidiana Budiharto, Widodo Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9798350353464

In smart retail, the problem in grocery product image classification is fine-grained image representation. Product variants are characterized by differences in color, text, and size. However, while the process of image classification involves quite complex stages, there is still a misclassification of grocery products. This is because there are many areas of the image being calculated, which makes the models not optimally calculate the most important area. This paper aims to identify a number of patch image formations as an important area of the product by involving Binary Robust Invariant Scalable Keypoints (BRISK) as a feature descriptor, K-Means Clustering, and the elbow method. First, we experiment with the BRISK keypoint feature for grocery products with different categories of brands. Second, the keypoint features are clustered using K-Means clustering. Lastly, the number of clusters is analyzed using the elbow method to find the optimal number. The result shows that the number of clusters from 8 products has variations of 5, 5, and 6 clusters. Finally, each cluster represents an important area in forming patches to support fine-grained grocery product image classification. ©2024 IEEE.

关键词： K-means clustering

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Scoring Urban Sustainability as a Guidance and Self-Learning for City Planners

Scoring Urban Sustainability as a Guidance and Self-Learning...

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2019 International Congress on Applied Information Technology, AIT 2019

作者： Herlawati, H. Heryadi, Yaya Trisetyarso, Agung Suparta, Wayan Kang, Chul Ho Abbas, Bahtiar Saleh BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728158624

City planners worldwide have tried to develop their cities following the concept of sustainable development. To allocate land use properly, the zoning method has been widely used, especially in densely populated cities, namely a kind of sustainable urban form with considers the mix of use/diversity of land use to minimize travel distance. This study proposes a method for calculating how much a city meets the sustainable urban forms based on compact city criteria, i.e. compatibility, dependency, and compactness. After the survey filling in compatibility and dependency scores for each land use, and compactness was calculated for each sub-district. Fuzzy C-Means clustering was used to cluster the result to classify other areas. In addition, this method can be used by planners to check whether their plans meet the concept of sustainable development or not. © 2019 IEEE.

关键词： Land use

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Promoting Timor Leste's Tais Cloth Using Mobile Augmented Reality Application 3

Promoting Timor Leste's Tais Cloth Using Mobile Augmented Re...

引用

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

作者： Seran Bria, Marianus Magno Kusuma, Gede Putra Putera Suryapranata, Louis Khrisna Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia

The results of observations showed that the book about Tais produced by Secretariat de Estado da Arte e Cultura (SEAC) has not been able to meet the needs of users because the information is less interesting and interactive. This paper's aim is to introduce the more interesting and interactive way to introduce Tais. Utilization of Augmented Reality (AR) technology in an application built with the Unity3D program is done to provide different way in presenting interesting and interactive information to its users. Based on the results in this paper, the developed application can handle the presentation in more interesting and interactive way. The ideal distance in the tracking process for target objects with size 7 x 6 cm is ranged from 6 cm to 30 cm, with the image ratio that can be detected at the farthest distance is 4% of the camera image. For the detection angle, the target object can be detected properly from approximately ±640. From the data acquired, it can be said that AR can be used to introduce Tais in more interesting and interactive way. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Augmented reality

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Drug Demand Prediction Based on Epidemiology Factors Using Random Forest 15

Drug Demand Prediction Based on Epidemiology Factors Using R...

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15th International Congress on Advanced Applied Informatics Winter, IIAI-AAI-Winter 2023

作者： Emmanuel, Gunadi Arifin, Yulyani Sonata, Ilvico Zarlis, Muhammad Bina Nusantara University Doctor of Computer Science Program Jakarta Indonesia Bina Nusantara University Binus Graduate Program-Doctor of Computer Science Computer Science Department Jakarta Indonesia Binus Graduate Program Bina Nusantara University Information System Management Department Jakarta Indonesia

ISBN: (纸本)9798350383829

The characteristics of the disease that spreads quickly, the number of sufferers, and the severity of sufferers of Coronavirus Disease 2019 are components of uncertainty during the pandemic. In an uncertain situation, prediction models for the need for drugs and medical devices are of great concern to policymakers in government, drug manufacturers, distributors, and pharmaceutical installation managers to maintain drug availability. Drug need prediction models that rely on historical data components on drug use are no longer reliable. Learning from the COVID-19 case, epidemiological variables correlate with predicting drug demand. This research includes data on ten major diseases in private hospital units for 2017-2022 to complete historical data on drug use. This study implements the Random Forest algorithm. The research method uses literature studies and processing field data from pharmaceutical installations. The analysis process uses KNIME software. The level of accuracy in predicting drug demand from historical drug use data was 77.272%, increasing to 81.818% with a model for predicting drug demand based on consumption cycles and classification of drug therapy groups. Furthermore, predictions of drug demand can consider variables recorded in medical records related to the seasonal frequency of diseases. © 2023 IEEE.

关键词： Forecasting

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Perkedel: Spreadsheet-inspired domain-specific programming language for data entry

Perkedel: Spreadsheet-inspired domain-specific programming l...

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2017 IEEE International Conference on Cybernetics and Computational Intelligence, CyberneticsCOM 2017

作者： Noprianto Soewito, Benfano Gaol, Ford Lumban Abbas, Bahtiar Saleh Warnars, Harco Leslie Hendric Spits Trisetyarso, Agung Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781538607831

To develop a data entry application, one may use a general-purpose programming language, a domain-specific programming language for data entry, or end-user tools that offer no programming at all. The first two offer more flexibilities but greatly differ in complexities. General-purpose language is probably overkill for a simple data entry application. In order to be useful, domain-specific language should be as close as possible to the problem domain and still open to research. This paper presents Perkedel, a domain-specific programming language designed for data entry. It is inspired by spreadsheet concept and offers user interface definitions that resemble a paper-based data entry form. Spreadsheet is one of the most popular programming systems that has been around us for almost four decades and we argue that easy user interface definition is important. This results in writing source code for a data entry application that looks nothing like ordinary source code. This speeds up the development time, too. One of our respondents spent only five minutes to a develop a simple data entry application, compared to the fastest development time of 32 minutes using a generalpurpose language, for similar application. That way, we hope that Perkedel may add a little perk to data entry developer's life using this data entry language. © 2017 IEEE.

关键词： Spreadsheets

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