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Feasibility study of Information Technology Investment (a case study of ODOO ERP: Project Management Module Implementation in Indonesia Based Company)

Feasibility study of Information Technology Investment (a ca...

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International Conference on ICT For Smart Society (ICISS)

作者： Fredy Jingga Raymond Kosala Suhono Harso Supangkat Benny Ranti Computer Science Department BINUS Graduate Program - Doctor of Computer Science Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

IT Governance are one of the needs in managing Enterprise Level IT. This study shows part of the decision domain of IT Governance Help, which are IT Investment and Prioritization. The purpose of this study is to determine feasibility of implementation open source ERP system Odoo project management module that replaces current system based on operational, economic, and technical aspects. The method used are Fit / Gap Analysis and Cost Benefit model using economic impact worksheet. The analysis is done by comparing the requirement with features owned by current system and Odoo ERP system. This research resulted that Odoo ERP System is feasible in the 3 aspects, the operational feasibility Odoo reaching 72% Fit, the economic feasibility with ROI of 84%, and technical feasibility indicating the technical requirement can be fulfilled by leasing AWS server. The conclusion is the open source ERP system Odoo project management module is feasible to be applied in terms of 3 aspects that have been studied, those are operational, economic, and technical.

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Analysis of Gamification Models in Education Using MDA Framework 3

Analysis of Gamification Models in Education Using MDA Frame...

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

作者： Kusuma, Gede Putra Wigati, Evan Kristia Utomo, Yesun Putera Suryapranata, Louis Khrisna Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Gamification nowadays is being one of techniques that can increase motivation and encourage the involvement of users, particularly in education domain that requires teaching and learning activities to be more fun and interesting. This paper surveys some analysis of gamification models. MDA framework is used to identify surveyed papers by breaking them down into three categories: mechanics, dynamics and aesthetics. Findings from the survey show there are many gamification models in education domain. However, there are some very representative gamification models could be used as a method to increase motivation, achievement and engagement in learning activities. By knowing the latest gamification models in education domain stated in this paper, it could help gamification practitioners to make new strategies in learning activities to increase students' motivation, achievement and involvement. We also suggest some gamification strategies, which combine several mechanics in such a way to create dynamics that results in all types of aesthetics outputs. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Students

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Features Importance in Classification Models for Colorectal Cancer Cases Phenotype in Indonesia

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Procedia computer science 2019年 157卷 313-320页

作者： Tjeng Wawan Cenggoro Bharuno Mahesworo Arif Budiarto James Baurley Teddy Suparyanto Bens Pardamean Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 BioRealm LLC Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Recently there has been an interest in predicting complex disease risk using models that combine the effects of many genetic factors together. These are known as polygenic models and are useful in evaluating risk of disease in patients. These models, however, often do not include important non-genetic factors that are important to the prediction of the disease. In this paper, we explore the prediction of colorectal cancer in Indonesia from non-genetic factors using common machine learning algorithms: XGBoost and Elastic Net. The result of this study identified 8 features with strong importance from both XGBoost and Elastic Net. We recommend including these features as covariates in future genetic association studies of colorectal cancer in Indonesia. Ultimately these models may be implemented as tools to screen patients for colorectal cancer risk.

关键词： Feature Importance Feature Selection XGBoost Generalized Linear Model Elastic Net Colorectal Cancer

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Personnel System Development with Integrated Military Education Information System (MEIS) in Supporting the Personnel Position and Career

Personnel System Development with Integrated Military Educat...

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International Conference on ICT For Smart Society (ICISS)

作者： Leli Setyaningrum Suhono H. Supangkat Harco Leslie Hendric Spits Warnars Juneman Abraham Edi Abdurachman Bina Nusantara University Jakata Barat Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Humanities Bina Nusantara University BINUS Jakarta Indonesia

ISBN: (数字)9781665404228

ISBN: (纸本)9781665404235

Personnel and education data very important for organizations, including the military. All data related to military personnel will give effect positions and careers in the military field. The integration of personnel and education data can assist in processing and decision making. An analysis is needed so that the developed system can be useful for the long term. Analysis with IT balanced scorecard and COBIT ® 2019, will be able to help and fill the gaps in the existing system based on the objectives of the military organization itself. It is shown that the domains BAI05 (Managed Organizational Change) and DSS02 (Managed Service Requests and Incidents) are still not being implemented well. The system developed will have the features and capabilities to support the organization in achieving its goals, including in the field of staffing and education. Besides, it provides convenience in making decisions in terms of positions related to personnel careers.

关键词： Personnel Education Organizations Task analysis Information technology Engineering profession computer science

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Mining Association rule with Attribute Oriented Induction High level Emerging Pattern (AOI-HEP) data mining technique 2

Mining Association rule with Attribute Oriented Induction Hi...

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2nd International Conference on Inventive Communication and Computational Technologies, ICICCT 2018

作者： Warnars, Harco Leslie Hendric Spits Gaol, Ford Lumban Heryadi, Yaya Trisetyarso, Agung Sanchez, Horacio Emilio Perez Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta11480 Indonesia Guadalupe30107 Spain

ISBN: (纸本)9781538619742

Attribute Oriented Induction High level Emerging Pattern (AOI-HEP) as proposed new data mining technique has been success to mine frequent and similar patterns. Moreover, the AOI-HEP data mining technique has been improved with confidence mining pattern into two terms, where firstly give confidence mining pattern for each AOI-HEP pattern either frequent or similar pattern. Secondly, give confidence for each dataset as confidence AOI-HEP pattern between frequent and similar patterns. Confidence for each AOI-HEP pattern will show how interested each of AOI-HEP pattern between frequent and similar pattern, whilst confidence per dataset will show how interested each dataset between frequent and similar pattern. In this paper the mining of AOI-HEP has been extended to mine AOI-HEP association rules using the current AOI-HEP frequent pattern, since association rule deal with frequent pattern. Based from previous experiments upon 4 UCI machine learning datasets such as adult, breast cancer, census and IPUMS, there are 9 finding AOI-HEP frequent patterns where 8 from adult and breast cancer datasets respectively. Finally, there are 2 and 1 AOI-HEP association rules from adult and breast cancer datasets respectively. © 2018 IEEE.

关键词： Association rules

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COVID-19 Testing Pipeline: Lesson Learned

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

作者： Dian Amirulloh Digdo Sudigyo Arif Budiarto Ika Nurlaila Erlin Listiyaningsih Andrew Simon Bens Pardamean Genetics Indonesia Jakarta Indonesia 12940 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Information System Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

The transmission of severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) in Indonesia is seen to be uncontrollably increasing that urges the government to leverage the capacity for the disease detections. Real-time polymerase chain reaction (RT-PCR), rapid test and computed tomography (CT) scan are the most common methods to determine if one has been infected regardless of whether or not the common symptoms of such Corona Virus Disease 2019 (COVID-19) surface. Among these three, RT-PCR is considered the gold standard for qualitative and quantitative assessment of SARS CoV-2 detection. The present paper aims at elaborating the framework of Roche's RT-PCR machine employed specifically for SARS CoV-2 detection performed by Genetics Indonesia which is deemed to be efficient and relatively quicker than other detection kits. RT-PCR machine detected SARS Cov-2 with RNA amplification curve equals to 10 copies RNA below the cut off value of Crossing point (Cp) positive control. Also elucidated in the paper is the implementations of EAV RNA and LightCycler® 96 RT-PCR System through which analysis time, amounts of individual required sample, as well as the reagents, can be accordingly reduced.

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A Design of Deep Learning Experimentation for Fruit Freshness Detection

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

作者： Febrian Valentino Tjeng Wawan Cenggoro Bens Pardamean 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 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480

Indonesia is a country with a tropical climate so that fruit and vegetable plants can grow easily in *** have many good nutrients such as vitamins, proteins and others. But the fruit also has a period where the fruit is said to be fresh *** this time there are still many fruit supplier companies that send fruit unfit for consumption due to lack of accuracy in the process of sorting the fruit when the fruit is taken from the plantation and the entry of other fruit into an improper packaging. Thus, it makes detecting food spoilage from the production stage to consumption is very important. We propose a design of computer vision-based technique usingdeep learning with the Convolutional Neural Network (CNN) model to detect fruit freshness. The specially designed CNN model is then evaluated with public datasets of fruits fresh and rotten for classification derived from Kaggle.

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Detection of Vehicle Position and Speed using Camera Calibration and Image Projection Methods

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Procedia computer science 2019年 157卷 255-265页

作者： Alexander A S Gunawan Deasy Aprilia Tanjung Fergyanto E. Gunawan Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480

Traffic congestion is the main problem faced by big cities, such as Jakarta. One approach to reduce congestion levels is to improve traffic management that regulates and controls the number of vehicles. To evaluate the impact of traffic management before direct implementation on the highway, traffic modeling can be carried out. Parameters in modeling traffic must be determined from a calibration process where the vehicle is accurately measured for its position and speed. This study aims to propose an efficient calibration procedure with accurate results, based on recorded vehicle movement in perspective view. First, the road image is projected using the Direct Linear Transformation (DLT) method, then the vehicle position is detected using the Background Subtraction and tracked using Mixture of Gaussian (MoG) to determine the vehicle speed. Finally, we develop a prototype of Automated Traffic Flow Monitoring based on Python programming. In the experiment results, the accuracy of vehicle position detection is evaluated based on the Euclidean distance. The average difference between the results of position detection with ground-truth is 12.07 pixels with a camera angle 40 °. The percentage of speed measurement accuracy using the DLT projection method is 96.14%.

关键词： Music recommender system Convolutional recurrent neural network Similarity distance

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Analysis of Acoustic Features in Gender Identification Model for English and Bahasa Indonesia Telephone Speeches

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Procedia computer science 2019年 157卷 199-204页

作者： Muhamad Fitra Kacamarga Tjeng Wawan Cenggoro Arif Budiarto Reza Rahutomo Bens Pardamean Eureka.ai Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics and 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

One of the most interesting topics in auditory problem is determining gender of the speaker. In recent years, machine learning has gained significant attentions as a way to build a classifier from labeled data which also can be implemented to build a gender classifier. In this study we develop gender classifier using two different datasets with different languages, English and Bahasa Indonesia. Each data from both datasets is represented by 20 acoustic features. Multi Layer Perceptron (MLP) is used to build the classification model using all these features and trained only on English dataset. This model is evaluated in both dataset to get the performance matrices consist of accuracy, AUROC, precision and recall. Ultimately, using this model we also identify and compare important features from both dataset to see the different characteristics of English and Bahasa Indonesia speeches.

关键词： Gender Identification Acoustic Feature Speech Recognition

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Impact of Intention to Use to a Document Management System (Case Study Approach) 3

Impact of Intention to Use to a Document Management System (...

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3rd International Conference on Information Management and Technology, ICIMTech 2018

作者： Hartono, Sugiarto Kosala, Raymondus Raymond Supangkat, Suhono Harso Ranti, Benny Information Systems Department Computer Science Department BINUS Graduate Program-Doctor of Computer Science Jakarta11480 Indonesia Computer Science Department Bina Nusantara University BINUS Graduate Program-Doctor of Computer Science Jakarta11480 Indonesia Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia

ISBN: (纸本)9781538658215

Document management system makes user to access information anytime and anywhere. The purpose of this research is to analyze what variables have impact on the intention to use of document management system. To achieve the objectives conducted by identification problem on the research model developed from the model of Technology Acceptance Model and Unified Theory of Acceptance and Use of Technology to the use of document management system. Furthermore, the data obtained from the respondents tested outer model, inner model test, hypothesis test and to produce a comprehensive analysis will be conducted Importance Performance Analysis. This research will result in a comprehensive analysis and able to provide recommendations and solutions for improvement from the implementation DMS has been done earlier. © 2018 IEEE.

关键词： Information services

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