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COCOMO II Analysis of Developing Multi-Account Partner Software for Crypto Exchange 15

COCOMO II Analysis of Developing Multi-Account Partner Softw...

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

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

ISBN: (纸本)9798350383829

The technique of calculating the work required for software development is known as software development estimation. The objective cost estimating technique for organizing and carrying out Multi Account Partner (MAP) software projects, COCOMO II, was employed in this study. The MAP software is a software architecture designed to support brokerage cryptocurrency exchanges using the order book and liquidity of established crypto exchanges. This research uses data sets from MAP project development at Indonesia Crypto Exchange Platform. It aims to create a software cost estimation model for MAP software using COCOMO II so that the resulting estimation model can be used as input or reference for estimates of subsequent MAP software development. The result estimated that MAP software finished in about four to five months, with a price range for software development of $7,441 to $8,780. Further research is needed with datasets from other crypto exchanges tested to increase cost estimation accuracy using COCOMO II. © 2023 IEEE.

关键词： Blockchain

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E-commerce Security Issues for SMEs: A Systematic Literature Review 7th

E-commerce Security Issues for SMEs: A Systematic Literature...

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7th International Conference on Advanced Computing and Intelligent Engineering, ICACIE 2022

作者： Gunawan, Zaldy Abdurachman, Edi Soewito, Benfano Gaol, Ford Lumban Computer Science Department BINUS Graduate Program—Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9789819950140

Significant advancements in information technology have altered existing markets, transforming them from physical to online electronic markets (e-commerce). The practice of conducting business online by smaller and medium-sized companies has received encouragement and assistance from governments all around the world, particularly those of developing nations. With the evolution of e-commerce, businesses must find a better way to implement e-commerce while maintaining its security. The purpose of this article is to carry out a Systematic Literature Review (SLR) in order to determine the types of vulnerabilities that are present in e-commerce platforms used by SMEs. As a result, in the conclusion, security issues and recommended solutions related to e-commerce systems for SMEs will be presented. These outcomes can serve as a foundation for further study on e-commerce security issues, such as solutions and recommendations for providing a secure e-commerce system for SMEs. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Electronic commerce

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Automatic essay exam scoring system: A systematic literature review 7

Automatic essay exam scoring system: A systematic literature...

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7th International Conference on computer science and Computational Intelligence, CSCI 2022

作者： Susanti, Meilia Nur Indah Ramadhan, Arief Warnars, Harco Leslie Hendric Spit Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

Currently, Indonesia and the whole world are being hit by the Covid-19 pandemic which has an impact on various fields of life. It affects all sectors, including the education sector. The government through the Ministry of Education and Culture makes a policy in education in terms of the learning process. Teaching and learning activities that were initially carried out face to face become distance learning which was carried out at home. In this study, a systematic literature review is conducted on automatic assessment of essay answers. Various previous studies discuss the essay answer scoring system that has been developed using various methods. We synthesize the results to enrich our understanding of the automated essay exam scoring system. The expected result of this research is that it can contribute to further research related to the automated essay exam scoring system, especially in terms of considering methods and dataset forms. © 2022 Elsevier B.V.. All rights reserved.

关键词： Distance education

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Shrinking Neural Style Transfer Model with Knowledge Distillation 3

Shrinking Neural Style Transfer Model with Knowledge Distill...

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

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

ISBN: (数字)9781665491648

ISBN: (纸本)9781665491648

Neural style transfer is a technique to transfer a style of an artistic image to another photorealistic image. The early development of this technique is exploiting the intermediate output of a deep learning model and utilizing it to optimize a targeted image. However, this technique needs some time to finish the process. An approach called knowledge distillation is widely used to optimize deep learning models so the speed of the model can be increased. Commonly, this technique is applied in a supervised task by providing a soft label as a target label for the student model. In this paper, a method is proposed to enable knowledge distillation happened in style transfer tasks. It is found this method is effective enough to make the style transfer process faster and give good results. In this paper also some discussion has been elaborated regarding the condition that is adequate to produce a good student model for style transfer tasks using knowledge distillation. © 2022 IEEE.

关键词： Distillation

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Street View Object Detection for Autonomous Car Steering Angle Prediction Using Convolutional Neural Network 1

Street View Object Detection for Autonomous Car Steering Ang...

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1st International Conference on computer science and Artificial Intelligence, ICCSAI 2021

作者： Sonata, Ilvico Heryadi, Yaya Budiharto, Widodo Wibowo, Antoni Bina Nusantara University BINUS Graduate Program-Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728133331

Autonomous car research is currently developing rapidly to find optimal and accurate steering angle and speed control. Various sensors such as cameras, LIDAR, and RADAR are used to recognize the surrounding environment to determine the correct steering angle prediction in avoiding obstacles. In addition to being expensive, LIDAR and RADAR have several drawbacks such as the level of accuracy that depends on the weather and the ability to detect adjacent objects. This paper will propose the prediction of steering angle and speed control in autonomous cars based on the detection of street view objects such as cars in front, traffic signs, pedestrians, and lane lines. The process of object detection and prediction of steering angle, as well as prediction of speed control using a convolutional neural network (CNN) through video captured using a single camera. In this method, other sensors such as LIDAR and RADAR are no longer needed so that the costs required are lower and the weaknesses found in LIDAR and RADAR can be eliminated. The results obtained are very good with 92% accuracy for steering angle prediction and 85% for speed control prediction. The autonomous car can run well in the simulator environment through the video taken on the real road. © 2021 IEEE.

关键词： Object recognition

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The Impact of Shift-Left Testing to Software Quality in Agile Methodology: A Case Study 8

The Impact of Shift-Left Testing to Software Quality in Agil...

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8th International Conference on Information Management and Technology, ICIMTech 2023

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

ISBN: (纸本)9798350326093

The point of Agile Methodology is continuous improvement, delivering a small feature quickly without sacrificing the feature quality;every sprint must be better than the previous sprint, and better can be fewer bugs, faster development, and testing. We will present how we reduce production bugs by customizing our sprint iteration. As we know, bugs are unavoidable, there is no software engineer that can make software without a bug;however, we can reduce bugs in production if we can find bugs in lower environments as early as possible. The case study in this paper was taken from one of technology company in Indonesia, the activity was done by the Quality Engineer (QA) Team. We will show that shift-left testing can help us reduce bugs in production. Testing is part of agile methodology, and the main idea of shift-left testing is to move testing early and could be done by any team member, not only QA. We include shift-left testing in our agile methodology for one year in 2022 and compare the result in the previous year. © 2023 IEEE.

关键词： Software testing

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A Survey of Refactoring Techniques to Maximize Code Coverage Metric 15

A Survey of Refactoring Techniques to Maximize Code Coverage...

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

作者： Simatupang, Johannes 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

Refasctoring is a technique used in software development to improve the quality of code without changing its functionality. One metric that is often used to measure code quality is Code Coverage. This study aims to examine refactoring techniques that can maximize Code Coverage Metric. Through the study, identification, evaluation, and summary of empirical evidence from various literature sources are carried out. The results of this study provide guidance on effective refactoring techniques to improve Code Coverage as well as other positive impacts for software development. There are ten refactoring techniques that can be used to improve Code Coverage Metrics in software testing. © 2023 IEEE.

关键词： Software testing

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Linear Regression Model to Predict the Spread of COVID-19 in Tangerang City 9

Linear Regression Model to Predict the Spread of COVID-19 in...

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9th International Conference on Information and Communication Technology, ICoICT 2021

作者： Sudiyono, Yusuf Trisetyarso, Agung Prabowo, Harjanto Meyliana, Meyliana Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781665404471

The outbreak of acute respiratory syndrome virus disease in China at the end of 2019 has caused a global epidemic as well as high mortality rates in affected countries. This research aimed at examining the extent of the spread of confirmed Covid-19 cases in Tangerang City. The data used included the data of confirmed Covid-19 patients. Such data was integrated with geospatial data found in 13 sub-districts in Tangerang City. The prediction of the spread of confirmed Covid-19 cases was made by using Linear Regression model. The results of the MAPE calculation with a value below 10% in 13 districts resulted in a very good predictive value. This prediction resulted in a graph and was connected to each other in a thematic map coordinate point system. The results of the Covid-19 spread prediction were divided into several districts and indicated with different color variations. Therefore, the darker the resulting color on the thematic map visualization, indicates an increase in Covid-19 cases that have occurred. © 2021 IEEE.

关键词： COVID-19

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Recommendation System Model for Personalized Learning in Higher Education using Content-Based Filtering Method 7

Recommendation System Model for Personalized Learning in Hig...

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7th International Conference on Information Management and Technology, ICIMTech 2022

作者： Julianti, M. Ramaddan Heryadi, Yaya Yulianto, Budi Budiharto, Widodo BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

- An online learning system is a learning approach that typically uses a one fit for all approach in which all student abilities are considered the same so that the provision of learning materials provided is the same for all students. In contrast, a personalization learning system is a teaching and learning approach in which students are positioned as the learning centers and the students are motivated and facilitated to overcome their learning needs based on their learning speed and understanding of the learning process carried out to achieve. In the context of learning, learning materials and learning objectives are the main components that are interrelated in achieving the expected learning outcomes. However, the relationship between learning materials, especially in prerequisite courses, must have similarities so that the learning process can continue in accordance with the learning outcomes to be achieved. This paper presents an experiment results of the proposed the recommendation system modeling for personalization learning model implemented using Content-Based Collaborative Filtering model. In the proposed recommender system model, similarities between the learning materials and the description of the course being are computed as basis for developing recommended learning materials to students. The recommendation system modeling for personalized learning is applied as a solution to achieve learning goals and minimize dropouts due to the inability of students to understand the learning process in online learning systems. The results given in the research are modeling of an adaptive learning personalization recommendation system to provide recommendations for students who do not reach the minimum competency standards. © 2022 IEEE.

关键词： Recommender systems

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Implementation of Light Gradient Boosting Machine (LGBM) for Customer Services Feedback Classification 5

Implementation of Light Gradient Boosting Machine (LGBM) for...

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5th International Conference on Artificial Intelligence and Data sciences, AiDAS 2024

作者： Anggreainy, Maria Susan Binus Graduate Program Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11530 Indonesia

ISBN: (纸本)9798331528553

Customer complaints are an important aspect in the business world. Every company must face complaints from its customers, whether related to unsatisfactory products, services or experiences. Customer complaints are a sign of unmet needs or expectations. A customer service person is tasked with serving questions asked by customers or consumers. The purpose of this research is to classify types of complaints to help customer service. The classification carried out is in binary form, namely disputed or not. This research compares several machine learning algorithms for classification of customer questions into appropriate categories for more efficient responses. Based on evaluation metrics, the F1 Score light gradient boosting machine (LGBM) is the best model compared to Multinomial Naive Bayes (MNB), Logistic Regression (LR), SVM (Support Vector Machine), and EXTC (Extra Tree Classifier). © 2024 IEEE.

关键词： Sales

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