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International Conference of computer and Informatics Engineering (IC2IE)

作者： Eric Sunjaya Kurniadi Christian Daniel Afdhal Kurniawan Maria Susan Anggreainy 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

Traffic accidents are a serious problem in developing countries. These accidents can be caused by poor infrastructure and the arrogance of drivers. In addition, semi-autonomous systems are automotive technologies that have been developed in recent years and are starting to be implemented in existing vehicles. This literature review paper will mainly discuss how object detection works in semi-autonomous systems, how semi-autonomous systems operate, and whether semi-autonomous cars can reduce the number of traffic accidents. Its main objective is to build driver confidence in semi-autonomous systems by assisting in driving and supporting the development of them. In the process of writing this paper, the method we use follows the guidelines stated in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P).

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Design of an Automatic Price Tag System for Web-Based Retail Business

Design of an Automatic Price Tag System for Web-Based Retail...

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International Conference on Information Management and Technology (ICIMTech)

作者： Suryadiputra Liawatimena Devina Gunawan Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Computer Science Deparment BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350390025

ISBN: (纸本)9798350390032

Modern retail businesses face a significant challenge with the inefficiency of manually changing price labels on shelves. This manual process not only consumes valuable time and resources but also increases the likelihood of errors, leading to potential inaccuracies in pricing and a less streamlined shopping experience for customers. The proposed solution is the implementation of an Electronic Shelf Label (ESL) system that automatically displays the prices of goods on retail business shelves. This system connects a website (front end and back end) to e-paper via a Wi-Fi network and microcontroller, allowing retail business owners to update prices more easily. Additionally, buyers can search for desired items through the website. The results are the time to send data from the website to the e-paper, namely, to know the performance of the e-paper used. The average time required from 10 attempts to send data from the website to the e-paper is 20.935 seconds. Since the data is connected to the server and will be updated automatically, using this system will be more efficient than manually changing the price label, although it takes time to transfer data from the website to the e-paper.

关键词： Electric potential Microcontrollers Pricing Manuals Information management Servers Wireless fidelity Faces Business

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Diagnosing Diabetes Using Soft Voting Ensemble Machine Learning Model

Diagnosing Diabetes Using Soft Voting Ensemble Machine Learn...

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International Conference on ICT For Smart Society (ICISS)

作者： Christian Chandra Kusuma Nathalia Chandra Galang Nurbudi Utomo Putu Agus Parimartha Jessica Hidayat Maria Susan Anggreainy Ivan Halim Parmonangan 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

Diabetes is a metabolic disorder caused by a dysfunction in insulin secretion which leads to an increase in blood sugar levels in the body. The disease has dangerous risks for those who suffer from it, as it can lead to various complications and even death. Because of the dangerous risks associated with diabetes, early detection of the disease is important. Machine learning can help the process of diagnosing diabetes quickly and accurately because of its ability to learn and process data independently. The goal of this research is to develop a diabetes detection system using ensemble learning with a soft voting classifier. In predicting diabetes, this research uses 14 types of algorithms with the help of the PyCaret library, including extra trees classifier, random forest, light gradient boosting, machine, gradient boosting classifier, decision tree, adaboost classifier, logistic regression, linear discriminant analysis, k-neighbors classifier, quadratic discriminant analysis, naive bayes, support vector machine-linear kernel, dummy classifier, and ridge classifier. From the evaluation process, the five best algorithms are chosen with an accuracy level of 91.3%, 91.3%, 89.5%, 92.2% and 85.3 % These five algorithms are then blended using ensemble learning with a soft voting classifier. The accuracy produced by the soft voting classifier method is higher than using a single classifier, at 97.3%.

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Security and Privacy Issues in Cloud-Based Databases: A Literature Review

Security and Privacy Issues in Cloud-Based Databases: A Lite...

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International Conference on ICT For Smart Society (ICISS)

作者： Oliver Sebastian Marpaung David Adriel Alvyn Vincent William Maria Susan Anggereainy Afdhal Kurniawan 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

Nowadays, technology is getting more sophisticated. It can be seen with the emergence of Cloud Computing. One application of Cloud Computing is Cloud databases. In a cloud environment, there will be privacy and security issues. From the literature results, data leaks and attacks from outsiders are still found when using cloud databases. Cloud service providers already have the technology to maintain data privacy and security. Three procedures can be carried out to maintain data privacy and security: encryption, access control, and third-party audits. Data privacy and security will be maintained with cloud service providers and procedures technology.

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Development of Sundanese Stemmer Based on Morphophonemics

Development of Sundanese Stemmer Based on Morphophonemics

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International Conference on ICT For Smart Society (ICISS)

作者： Aries Maesya Yulyani Arifin Amalia Zahra Widodo Budiharto Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Binus Nusantara University Jakarta Indonesia

The Stemming Process is used to get the base word by removing the word affixes. The purpose of this study is to improve the algorithm in previous research by incorporating the Stemming Process into a morphophonemic approach for language processing based on rules (Rule Based) which is named AM Sundanese Stemmer (AMS). The AM Sundanese stemmer algorithm will utilize morpheme information to perform stemming on Sundanese words and analyze the phonemes in a word to identify the morphemes therein contained. The experimental process was carried out with 11,885 existing data and a sample of 546 words were taken to be stemmed. The test was carried out by comparing the algorithms of Nazief and Adriani, UG 18 and AMS. The test results showed that the AMS Algorithm was better than the Nazief Andriani Algorithm and the UG18 Algorithm with a high F-1 score of 87.52% and the comparison of the execution time of the AMS Stemmer Algorithm was 0.041403 seconds faster than the Nazief Andriani and UG 18 Algorithms.

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Deep learning for oil palm fruit ripeness classification with densenet 6

Deep learning for oil palm fruit ripeness classification wit...

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6th International Conference on Information Management and Technology, ICIMTech 2021

作者： Herman, Herman Cenggoro, Tjeng Wawan Susanto, Albert Pardamean, Bens Bina Nusantara University BINUS Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Bioinformatics and Data Science Research Center Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Computer Science Program Bioinformatics and Data Science Research Center Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665449373

Oil palm fruit farming is one of the most leading agriculture industries in the South East Asia region. Unfortunately, most of the harvesting method is still done through manual labor. Multiple research has been conducted to help farmers automatically detect the ripeness level of the oil palm fruit. We conducted an experiment of detecting the ripeness level of oil palm fruit by using one of the state-of-the-art computer vision approaches, which was deep learning with a Convolutional Neural Network (CNN). The dataset used consists of 7 levels of ripeness with 400 images of oil palm fruits. The models used in this test scenario were both AlexNet and DenseNet. The result of this study showed that DenseNet has been proven to outperform AlexNet by 8.5% in terms of accuracy and 8% in F1 score. © 2021 IEEE.

关键词： computer vision

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Multi-Lingual ESG Impact Duration Inference 7

Multi-Lingual ESG Impact Duration Inference

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Joint Workshop of the 7th Financial Technology and Natural Language Processing, 5th Knowledge Discovery from Unstructured Data in Financial Services and 4th Economics and Natural Language Processing, FinNLP-KDF-ECONLP 2024

作者： Chen, Chung-Chi Tseng, Yu-Min Kang, Juyeon Lhuissier, Anaïs Seki, Yohei Lee, Hanwool Day, Min-Yuh Tu, Teng-Tsai Chen, Hsin-Hsi AIST Japan Data Science Degree Program National Taiwan University Academia Sinica Taiwan 3DS Outscale France University of Tsukuba Japan NCSOFT Korea Republic of Graduate Institute of Information Management National Taipei University Taiwan Graduate Institute of International Business National Taipei University Taiwan Department of Computer Science and Information Engineering National Taiwan University Taiwan

ISBN: (纸本)9782493814197

To accurately assess the dynamic impact of a company’s activities on its Environmental, Social, and Governance (ESG) scores, we have initiated a series of shared tasks, named ML-ESG. These tasks adhere to the MSCI guidelines for annotating news articles across various languages. This paper details the third iteration of our series, ML-ESG-3, with a focus on impact duration inference—a task that poses significant challenges in estimating the enduring influence of events, even for human analysts. In ML-ESG-3, we provide datasets in five languages (Chinese, English, French, Korean, and Japanese) and share insights from our experience in compiling such subjective datasets. Additionally, this paper reviews the methodologies proposed by ML-ESG-3 participants and offers a comparative analysis of the models’ performances. Concluding the paper, we introduce the concept for the forthcoming series of shared tasks, namely multi-lingual ESG promise verification, and discuss its potential contributions to the field. © 2024 ELRA Language Resource Association.

关键词： Iterative methods

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Objective Sleep Quality Measurement based on Fuzzy Logic and Wearable Device

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Procedia computer science 2023年 227卷 1153-1162页

作者： Jason A. Wijaya Pauw D. Andersen Nico Surantha Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Department of Electrical Electronic and Communication Engineering Tokyo City University Japan

Sleep is the natural state of relaxation for human being. Sleep quality is an essential yet frequently neglected aspect of sleep in general. Sleep quality is essential because it allows the body to restore itself and prepare for the next day. The standard method for evaluating sleep quality was subjective evaluation. Actigraphy devices, which can measure the sleep cycle, are now widely available. This study developed a method using Fuzzy Logic and an actigraphy device to measure and classify sleep quality. The fuzzy logic method was developed in several stages, which are determining the sleep quality measurement parameters, constructing the fuzzy set for each input variable, and developing the fuzzy rules. To evaluate the proposed fuzzy model, five individuals were invited to participate in the experiment and required to complete the PSQI subjective sleep questionnaire. The evaluation result shows that our proposed Fuzzy model achieves lower error compared to the existing method.

关键词： sleep sleep quality actigraphy artificial intelligences fuzzy logic

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Diabetes Classification Using Support Vector Machine: Binary Classification Model 4

Diabetes Classification Using Support Vector Machine: Binary...

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4th International Conference on Information and Communications Technology, ICOIACT 2021

作者： Rabiha, Suciana Ghadati Wibowo, Antoni Lukas Heryadi, Yaya Computer Science Department BINUS Graduate Program-Doctor of Computer Science. Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University 11480 Indonesia Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University 11480 Indonesia

ISBN: (纸本)9781665433945

One of the health problems that require special attention is diabetes, besides the growth of this disease infection is increasing in various circles ranging from children, adults, men, women and the elderly. So to detect diabetes at an early stage, machine learning algorithms are the right choice to help detect indications of diabetes. This paper presents experimental results related to the exploration of the use of a Super Vector Machine (SVM) for data classification of Diabetes. The model used in this experiment is the Binary Classification Model. Based on the test results, the highest accuracy is obtained by using a total of 700 lines of data, which is 75,7143%. The Best estimated feasible point in Box Constraint is 272.29 with a KernelScale area of 72.627. © 2021 IEEE

关键词： Face recognition

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Developing an online information portal for enhancing society awareness of RPTRA (A case study RPTRA MAYA ASRI 13)

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Procedia computer science 2023年 216卷 144-150页

作者： Yulyani Arifin Elizabeth Paskahlia Gunawan Margaretha Ohyver Computer Science Departement BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia. Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia. Statistics Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia.

The long COVID-19 pandemic has limited the activities of Ruang Publik Terpadu Ramah Anak (RPTRA) such as environment cleaning, repair of RPTRA infrastructure, learning and others, as well as the lack of public awareness about the existence and importance of RPTRA to the public and foreign tourists encouraging the RPTRA to make changes in the dissemination of information about the activities carried out in the RPTRA through the use of technology to survive and grow even during the Covid-19 Pandemic. The methodology used in this research is Group Discussion Forum with the administrators of the RPTRA Maya ASRI 13 to learn about the needs and expectations of the RPTRA administrators regarding the web portal to be built. Then, the implementation of the conceptual model, development, and evaluation of the effectiveness of the RPTRA information web portal was carried out. The contribution in this research is to implement a conceptual model on the information portal built on the platform of the Website with the PHP framework, which is then evaluated on the results of the pre-test and post-test about RPTRA the Wilcoxon-Signed Rank Test to test the effectiveness of the information web portal for general users. The results obtained from these tests indicate that the RPTRA Information Web Portal can help the public learn more about the existence of RPTRA Maya Asri 13.

关键词： PHP RPTRA The Covid-19 Pandemic Web Portal Web Technology

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