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2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Andres, Arfandi Tanjaya, Edwin Setiawan Ghaniyardi Sandhi, Joshua Christian Warnars, Harco Leslie Hendric Spits Bina Nusantara University Information Systems Department School of Information Systems Jakarta11480 Indonesia Bina Nusantara University Computer Science Department Binus Graduate Program - Computer Science Jakarta11480 Indonesia

ISBN: (纸本)9781665400527

In this era, people often overeat, make parties or events, where there are excessive availability of food. As well as shops or restaurants that sell food, has ready-to-eat foods that only lasts one day and then treated as expired food. Often this precious food is thrown in the trash, and meanwhile, many destitute people cannot eat enough per day. Therefore, this research paper aims to mobilize people who overeat and donate their excess food that can still be consumed to those in need. This smartphone application is equipped with activities such as registering for new donors who want to join the mobile application and logging in for donors who are already registered in the mobile application. Donors can monitor couriers taking photos of recipients with food donated from donors. In addition, donors can select the food category for donation and input amount, track the donated food that the courier has picked up, and send it to the recipient. This mobile application is also equipped with donors to share experiences, ideas, and views based on topics created by staff and available threads. © 2022 IEEE.

关键词： Mobile computing

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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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Six Sigma for Evaluating Electronic Signature in eProcurement System: A Case Study 4

Six Sigma for Evaluating Electronic Signature in eProcuremen...

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4th Asia Pacific Conference on Research in Industrial and Systems Engineering: Building Business Resilience to Face the Challenge in Pandemic Era, APCORISE 2021

作者： Nugroho, Eko Cahyo Saputra, Herry Gunarso, Davy Yeria Wibowo, Antoni Utama, Ditdit Nugeraha Computer Science Department Binus Graduate Program Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781450390385

Six-sigma is an approach to appraise a company's prospect in generating a number of piece with homogenized processes without any production defects or zero faults. It is operated not only for declining defect numbers, but also for reducing the company's imperfection itself. It means, company is able to decrease the cost (in term of money or time), also to increase the efficiency by evaluating current process and planning to improve company management process. In this study, six-sigma benefited to determine the success level of implementation of e-signature application in e-procurement system based on user experience rate. Conclusively, the implementation of "change management"has enhanced the business process in detail, while it was still in the equivalent sigma level 2. © 2021 Owner/Author.

关键词： Six sigma

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Random Forest Based QSAR Model Analysis for Predicting Drug Effectiveness Against Mycobacterium Tuberculosis Bacteria

Random Forest Based QSAR Model Analysis for Predicting Drug ...

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International Conference on ICT For Smart Society (ICISS)

作者： Alicia Josephine Ekosputri Amanda Ardianti Maria Susan Anggreainy Brychan Artanto Nora Fitriawati Fanny Angelia Valentina Vincent Kartamulya Santoso Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

This research focuses on the use of machine learning methods, especially Random Forest, in designing tuberculosis drugs more effectively and efficiently. The research process begins with the creation of a QSAR (Quantitative Structure-Activity Relationship) model using a dataset from ChEMBL that includes compounds with activity against Mycobacterium tuberculosis. This model aims to predict the pIC50 value, which is an indicator of a compound's biological activity as a tuberculosis drug. The results of the Random Forest model showed high accuracy, which is 92%. This accuracy indicates that the model has a good ability in predicting the effectiveness of compounds against Mycobacterium tuberculosis. With this result, the developed model can be used as an auxiliary tool in the discovery of tuberculosis drugs and can be further developed to increase the effectiveness in drug research.

关键词： Drugs Accuracy Tuberculosis Biological system modeling Linear regression Predictive models Compounds Reliability Random forests Overfitting

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The Utilization of Fuzzy Logic and Bollinger Bands to Enhance Trading Decision-Making During the Bitcoin Halving Phase

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Procedia computer science 2024年 245卷 272-281页

作者： Oscar Adam Darmawan Yaya Heryadi Lukas Lili Ayu Wulandhari Ilvico Sonata Computer Science Department Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta 12930 Indonesia

The volatile behavior of Bitcoin's price, especially during its halving periods, poses considerable obstacles for forecasting and decision-making in cryptocurrency trading. This paper presents a novel method that combines application fuzzy logic with Bollinger Bands to improve trading decision-making in times of high market volatility. This study conducted an experiment utilizing three fuzzy logic controllers and Bollinger Bands (BB) to determine the strength of buy, hold, and sell signals. This dataset includes the initial and final prices that are used to calculate the BB. The raw and computed values serve as the precise input parameters for the Fuzzy Inference System (FIS). The membership functions were categorized into four levels: very low, low, high, and very high, based on the input default settings utilized by traders. Rulesets were created using fuzzy logic to produce signals that indicate the level of strength of a trading advice. This study evaluate the effectiveness of this hybrid method in comparison to the traditional utilization of the Bollinger Band only indicator and Moving Average Convergence Divergence (MACD) indicator, which is widely favored by traders to identify possible market fluctuations. This methodology involves creating a trading simulation that is based on past Bitcoin halving events. The objective is to assess the efficacy of these strategies in managing heightened volatility. The application of fuzzy logic with the Bollinger Bands model yielded a success rate of 92.47% while analyzing 93 daily data points from the previous Bitcoin halving event on May 11, 2020.

关键词： fuzzy logic crypto price prediction bitcoin bollinger bands macd cryptocurrency

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Single and Multi-Documents Text Summarization Technologies for Natural Language Processing: a Systematic Review on Method and Dataset

Single and Multi-Documents Text Summarization Technologies f...

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Creative Communication and Innovative Technology (ICCIT), IEEE

作者： Arief Agus Sukmandhani Arief Ramadhan Edi Abdurachman Agung Trisetyarso Computer Science Department Binus Online Learning Binus Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Binus Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia

The summarization technologies have been increasingly used in recent decades. Those technologies are a very important part of emerging topics in computer science and engineering, such that Natural Language Processing (NLP). Several methods have been used for analysis to get good summary results. There are two types of document summaries: single document summaries and multi-document summaries. Single document summaries aim to extract information from a single document to get new and relevant summary information, while multi-document summaries extract information from multiple documents. This study focuses on the activities of the semantic literature in previous studies to obtain the basis of the widely used base methods and data sets used in this study. Data was collected from Scopus publication sources from 2019 until 2022 Q2 for analysis. Researchers use guidelines from the semantic literature method by using the basis of Kitchenham and Charters as a reference in its design. In this study, there were forty-eight articles obtained from the filtering results of several criteria used, including exclusion and quality assessment.

关键词： computer science Systematics Filtering Semantics Redundancy Bit error rate Natural language processing

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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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Dagang Yuk Yuk As Smartphone Application for MSME Product Sales 2

Dagang Yuk Yuk As Smartphone Application for MSME Product Sa...

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2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Erinda, Muhammad Fandi Warnars, Harco Leslie Hendric Spits Sumardin, Winters Arianto, Jimmy Vinarycha, Devi Wahyu Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Bina Nusantara Univesity Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665400527

Many MSMEs manually close their businesses in today's competition, especially those caused by the COVID19 pandemic, and besides that, the lack of technology implementation is even more aggravating. Like it or not, Micro, Small, and Medium Enterprises (MSMEs) must equip their businesses with the application of technology, and unfortunately, there are still many MSMEs that have not been able to take advantage of the benefits of technological developments. Many companies see this condition as an opportunity;for example, Gojek and Grab partner with MSME players to make it easier to trade their products or services. In this paper, a smartphone application for MSMEs called 'Dagang Yuk Yuk, ' which consists of activities such as Login, Create Order, Input Delivery Location, Select Courier, and Select Payment Method has been proposed. Dagang Yuk Yuk tries to give different ideas for implementing MSME actors where this application is only for MSME players as part of an MSME business unit. This paper discusses the application's design using use case diagrams to describe the business process, while class diagrams model the database design. This application was developed using Arduino studio and MySQL database for database storage. © 2022 IEEE.

关键词： Competition

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YOLOS-MCI: Automating Microservices Coupling Index Calculation using Vision Transformers

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Procedia computer science 2024年 245卷 924-933页

作者： Gintoro Yaya Heryadi Lukas Lili Ayu Wulandhari Ilvico Sonata Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta 12930 Indonesia

Microservice Architectures (MSA) provide flexibility and scalability in software development. However, accurately measuring the level of interdependence among Microservices continues to be a difficult task. Precisely evaluating this connection is essential for efficient MSA design, maintenance, and future development. Conventional techniques for assessing Microservice coupling are frequently done by hand, require a significant amount of time, and are susceptible to mistakes. This impedes the capacity to make well-informed judgments regarding the integration and adjustment of services. This study introduces a new method for automating the computation of the Microservice Coupling Index (MCI) by utilizing the You Only Look at One Sequence (YOLOS) object identification technique in combination with Vision Transformer (ViTs) technology. YOLOS is utilized for identifying constituents within Unified Modeling Language (UML) Component Diagrams, facilitating precise classification and effective assessment of coupling. The model exhibits varying performance over multiple Intersection over Union (IoU) thresholds and object sizes, with an average precision (AP) of 0.406 over IoU values ranging from 0.50 to 0.95. The maximum precision is achieved at an IoU of 0.50, with an AP of 0.709. The model demonstrates good performance in identifying smaller components, especially when evaluated at a 0.75 IoU threshold. However, it faces challenges in detecting small items, suggesting potential areas for improvement in future iterations. Initial results indicate that this automation greatly decreases the need for manual, labor-intensive tasks and enhances the precision of measuring coupling in MSA, hence facilitating effective decision-making in service integration and modification. Automating the computation of the coupling index has the potential to significantly influence the design and management of durable and readily controllable microservice architectures.

关键词： Coupling Microservices Microservices Coupling Index UML Component Diagrams Vision Transformer YOLO

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Model of Text-to-Text Transfer Transformer for Hadith Question Answering System

Model of Text-to-Text Transfer Transformer for Hadith Questi...

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International Conference on Information Technology, computer and Electrical Engineering (ICITACEE)

作者： Bambang Sulistio Derwin Suhartono Haryono Soeparno Widodo Budiharto Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Doctor of Computer Science Program Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350389302

ISBN: (纸本)9798350389319

The advancement of Artificial Intelligence (AI), notably in Natural Language Processing (NLP), has been remarkable. Among its applications, Question-Answering (QA) systems stand out, assisting users in accessing pertinent information across various topics, including religious contexts. Religion plays a significant role in providing guidance on moral values to modern society, such as tolerance, compassion and social norms. Religious practices taught by religion serve as significant foundations for addressing the increasingly advancing influence of technology. The primary goal of this paper is to create a question-answering system proficient in analyzing user inquiries and precisely extracting data from translated Indonesian Hadith datasets. This research endeavors to enhance question-answering accuracy through Deep Learning techniques. Employing pre-processing methods, the system interprets user query intents. Furthermore, the Text-to-Text Transfer Transformer (T5), a text-based language Transformer model, is utilized to streamline the retrieval process for Hadith-related queries based on relevant subjects. The research findings demonstrate the precision of answers through BLEU and ROUGE scores. The novelty of this study lies in the creation of a dataset of hadith translations in Indonesian and the fine-tuning of the T5 model that has been trained using a dataset of questions and answers based on these translations. This research demonstrates the following evaluation scores: BLEU: 0.606, ROUGE-1: 0.702, ROUGE-2: 0.548, and ROUGE-L: 0.701, indicating that the answers generated by this particular research model are better compared to those produced using the standard mT5 model.

关键词： Electrical engineering Deep learning Ethics Large language models Transformers Question answering (information retrieval) Data mining Information technology Standards Testing

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