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Neural Collaborative For Music Recommendation System

IOP Conference Series: Materials science and Engineering 2021年第1期1071卷

作者： Abba Suganda Girsang Antoni Wibowo Jason Roslynlia Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

In music there are various types of genres and every person has their own choice of the type of music they want to hear. Recommendation system is an important feature in an application, especially with the large number of choices for a particular item. With a good recommendation system, users will be helped by the suggestions given and can improve the user experience of the application. It is better provided by using collaborative filtering (CF) approach by recommending products related to one's preferences history. However, CF approach still lacking in integrating complex users data. Therefore, hybrid technique could be the solution to polish the CF approach. Combining neural network and CF also called NCF thought to be better than CF alone. This study focuses on collaborative filtering approach combined with neural network or called neural collaborative filtering. In this study, we use 20,000 users, 6,000 songs, and 470,000 transaction ratings then predict the score using CF and NCF approach. The aim of this study is to differentiate recommendation systems with the use of CF alone and NCF. Through this research, it was found that NCF is better than user-based collaborative filtering in gather those playlist they really want to hear, but requires more time to build it.

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A review of traffic violation detection technology in reporting mechanism

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IOP Conference Series: Earth and Environmental science 2021年第1期729卷

作者： A Alaydrusl W K Putra Y Nugroho Muhammad N Surantha Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Traffic Violation Detection system using radio frequency identification (RFID) has been applied to detect vehicles with limited power sources through RFID Tag. Camera sensors are also applied to identify a vehicle and its plate number through image and video processing known as computer vision. On the other hand, vehicular ad hoc network (VANET) to gain information about location, speed, and so on through the vehicle-to-vehicle (V2V) connection. Lastly, the internet-of-things that is backed-up by cloud computing helps to store various information from each of these technologies and process them to get results. Many researchers have proposed and developed algorithms or technology with astonishing experimental results of them. However, there has been no review of the integration and reporting mechanism that correlates them. There has also been no review about how to connect the information to the authority and violator. Therefore, the review was made to explain each technology's method with their experiment's results and issues. Moreover, the future challenge also had been given to further research.

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Physiological Biomarkers for Assessment of Pain during Routine Blood Tests for Older Adults with Dementia in Long-Term Residential Care

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Journal of the American Medical Directors Association 2024年第8期25卷 105050页

作者： Feng, Po-Chung Khan, Mohammad Anwar Yeh, Ting-Ting Shieh, Wann-Yun Tsai, Hsiu-Hsin Master Degree Program in Health and Long-term Care Industry College of Medicine Chang Gung University Taoyuan Taiwan Department of Internal Medicine National Taiwan University Hospital Hsinchu Branch Hsinchu Taiwan Department of Computer Science and Information Engineering Chang Gung University Taoyuan Taiwan Division of Endocrinology and Metabolism Chang Gung Memorial Hospital at Linkou Taoyuan Taiwan School of Nursing College of Medicine Chang Gung University Taoyuan Taiwan Department of Psychiatry Chang Gung Memorial Hospital at Linkou Taoyuan Taiwan

Objective: Evaluating pain in individuals with dementia can be difficult when verbal communication is limited. Vocalization has emerged as a potential avenue for assessments of pain in nonverbal populations. This study aimed to evaluate if physiological assessments of vocalization were correlated with observational assessments of pain during routine blood tests for persons with dementia. Design: A cross-sectional descriptive study. Setting and Participants: Sixty older adults (aged ≥65 years old) with dementia requiring routine finger puncture and peripheral venipuncture for routine blood tests were recruited by purposive sampling from 3 long-term care facilities in Taiwan. Methods: Observational assessments were conducted with the Pain Assessment in Advanced Dementia (PAINAD) instrument;physiological biomarkers of vocalization were assessed with a noninvasive sensing device and microphone (NISDM). Assessments were conducted simultaneously in one session during situations of increasing pain levels: at rest, making a sound, finger puncture, and peripheral venipuncture. PAINAD scores were compared with signal recording measures from the NISDM. Analysis of variance and Pearson correlation coefficient assessed correlations between observational and physiological measures. Results: Most participants were female (63.3%);mean age was 81.27 years (SD = 9.69);Clinical Dementia Rating was 2.23 ± 0.70;and Mini-Mental State Examination was 7.07 ± 6.95. Signal recording measures using the NISDM during finger puncture and venipuncture were significantly greater compared with measures at rest and making sound, indicating higher signal levels were associated with pain. PAINAD scores were significantly correlated with physiological measures for vocalization variables of sound amplitude (r = 0.49, P <.001), shimmer (r = 0.63, P <.001), and inhalation-to-exhalation amplitude ratio (r = 0.48, P <.001). Conclusions and Implications: Elevated vocalizations detected with the NISDM were co

关键词： Biomarkers dementia long-term care pain physiological assessment

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Design and Performance Evaluation of a P4 based Load Balancer 8

Design and Performance Evaluation of a P4 based Load Balance...

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8th International Conference on Innovation, Communication and Engineering, ICICE 2019

作者： Hsu, Shih-Jung Ke, Chih-Heng Chen, Yeong-Sheng Hung, Cheng-Feng Lo, Yu-Wen Master Degree Program of Computational Intelligence and Applications National Quemoy University Taiwan National Taipei University of Education Department of Computer Science Taiwan Master of Information Technology and Application National Quemoy University Taiwan National Quemoy University Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9781728158396

Being increasingly dense and mature in layout, Internet has become an infrastructure for a state. The traditional single server can no longer bear the network traffic in rapid growth. For example, once the booking service for concert tickets is made available to the public, we are always prompted when clicking into the booking system that the server is busy. And when the system is finally restored normal, the tickets have been sold out. The load issue puzzling the ticket system also occurs in the transportation section every time when a long holiday is coming. Even though the system is updated on a yearly basis, net- work congestion still happens frequently. Therefore, there is still great space for the development of the ways and mechanisms of load balance in traditional multi-servers. Evaluation of the mech- anism and efficacy of load balance through P4Switch is proposed in this paper in the hope to achieve more efficient server load balance. © 2019 IEEE.

关键词： loadbalance openflow p4switch sdn

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Accuracy for Sentiment Analysis of Twitter Students on ELearning in Indonesia using Naive Bayes Algorithm Based on Particle Swarm Optimization 1

Accuracy for Sentiment Analysis of Twitter Students on ELear...

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1st International Conference on computer, science, Engineering and Technology, ICComSET 2018

作者： Kartiko, Mohamad Sfenrianto Master of Computer Science Postgraduate Programs STMIK Nusa Mandiri Jakarta Indonesia Information Systems Management Department BINUS Graduate Program-Master of Information Systems Management Universitas Bina Nusantara Jakarta Indonesia

Students can use social media such as Twitter for online learning (E-Learning). This study aims to analyse an accuracy for the sentiments of students about E-Learning who use Indonesian on Twitter social media both positive and negative opinions. The algorithms used are Naive Bayes (NB). Then to optimize the accuracy of the calculation results, the Particle Swarm Optimization (NB-PSO) approach is used. In order to optimize accurate results, this study uses three experimental sequences (scenario 1, scenario 2, and scenario 2) for both NB and NB-PSO algorithms. Each scenario uses different positive and negative comments. The results of the experiment show that in scenario 1 an increase in accuracy is 10.00% for NB-PSO. Scenario 2 there is an increase in accuracy of 13.33% on NB-PSO. Meanwhile, in scenario 3 an increase in accuracy is 27.22% for NB-PSO. These results prove that the accuracy of NB-PSO is better than NB for all scenarios. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Students

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Detecting Hemileia vastatrix using Vision AI as Supporting to Food Security for Smallholder Coffee Commodities

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IOP Conference Series: Earth and Environmental science 2022年第1期998卷

作者： Teddy Suparyanto Erick Firmansyah Tjeng Wawan Cenggoro Digdo Sudigyo Bens Pardamean Faculty of Agricultural Technology Institute of Agriculture STIPER Yogyakarta Indonesia 55282 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

The loss of food crops during the COVID-19 pandemic threatens food security in Indonesia as one of the world's top coffee producers. This affects the insecurity of coffee commodities which is influenced by several factors other than the pandemic such as pests, plant diseases, and extreme weather. Plant diseases, such as leaf rust, are a significant factor in the insecurity problem in coffee commodities. The fungus Hemileia vastatrix B et Br causes leaf rust disease, which is a pest that frequently damages coffee plants. This disease not only interferes with plant growth but also causes a decrease in coffee quality and quantity. This initial research aims to carry out early prevention of these diseases as supporting to food security in smallholder coffee commodities. An AI-based visual detection application is the result of this research. We collected 100 images of coffee leaves from various coffee plants. The image is reshaped to 256 x 256 pixels and randomly trimmed to 224 x 224 pixels to fulfill the size requirements of a standard Deep Learning technique. Each image was classified into two classes by a plant pest and disease specialist. The dataset was divided into training, validation, and testing series with a ratio of 60:20:20 for training procedures. The Convolutional Neural Network (CNN) research method used a variation of the ResNet CNN model with 18 layers. The best model validation was 59%.

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Development of E-Commerce Approach to Service Oriented Architecture Using SOMA Methodology

Development of E-Commerce Approach to Service Oriented Archi...

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International Conference on Information Management and Technology (ICIMTech)

作者： Muhardany Suharjito Arief Agus Sukmadhani Eric Gunawan BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia BINUS Online Learning Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728170718

ISBN: (纸本)9781728170725

This study aims to provide solutions to problems in the e-commerce system at PT. XYZ This is due to the number of bugs in the e-commerce system at PT. XYZ Some products cannot enter the shopping design page; there are no features that should be available in e-commerce systems such as shipping costs. An e-commerce system with a Service Oriented Architecture (SOA) approach is needed to overcome these problems. The results of the study found that several web services can be combined into one part to help the development process become better and easier.

关键词： Service-oriented architecture computer architecture Companies computer bugs

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Improving Conversion Rates for Fashion e-Commerce with A/B Testing

Improving Conversion Rates for Fashion e-Commerce with A/B T...

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International Conference on Information Management and Technology (ICIMTech)

作者： Reza Rahutomo Yulius Lie Anzaludin Samsinga Perbangsa Bens Pardamean School of Information Systems Bina Nusantara University Jakarta Indonesia BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728170718

ISBN: (纸本)9781728170725

Shopping centers are transformed from physical stores to e-commerce with more varied product and service offerings. Since fashion is the most favorite item category in Indonesia, there are lots of fashion e-commerce grown in the country. One of the unsatisfactory conditions that are occurred in fashion e-commerce in Indonesia is user drop off. By using funnel analysis, the product detail page of fashion e-commerce founded as the page with the most user drop off. To tackle this problem, several experiments were prepared. With A/B testing, the experiments that possibly improved the conversion rate were identified. This research discovered experimental version of the User Interface (UI) of the product detail page by manipulating button colors, layout, and delivering comprehensible information to users.

关键词： Testing Electronic mail Customer relationship management Information systems Image color analysis Google

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Evaluation of IT Governance Implementation Using COBIT 5 Framework and ISO 38500 at Telecommunication Industries

Evaluation of IT Governance Implementation Using COBIT 5 Fra...

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International Conference on Information Management and Technology (ICIMTech)

作者： Alhamd Khalif Rama Suharjito Eric Gunawan BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia BINUS Online Learning Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728170718

ISBN: (纸本)9781728170725

The failure of implementing the IT Governance can lead to the use of technologies which are not effective and efficient. The aim of this research is to evaluate the implementation of IT Governance in Telecommunication Industries focuses mainly on the EDM and DSS domains based on the COBIT 5 and ISO 38500 frameworks. We have conducted an evaluation research and conducting collection of primary and secondary data. The data that we have compiled from questionnaires result were divided into 2 parts; Domain EDM questionnaires and Domain DSS questionnaires. The results of our evaluation from the Telecommunication Industries shows that the EDM Domain scored 4,2 with the rating scale of 76%. Whereas the capability level for Domain DSS reached 4,33 with the rating scale of 82%. In conclusion, our research as well as the evaluation that we have conducted on IT Governance implementation within Telecommunication Industries could be categorized as `satisfactory.

关键词： ISO Standards Companies Monitoring Communications technology Industries computer science

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The Effect of Several Kernel Functions to Financial Transaction Anomaly Detection Performance using One-Class SVM

The Effect of Several Kernel Functions to Financial Transact...

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2019 International Congress on Applied Information Technology, AIT 2019

作者： Heryadi, Yaya Dandalina, D. Bina Nusantara University Computer Science Department Jakarta11530 Indonesia Master of Information and Technology Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781728158624

Anomalies in data become ubiquitous and often unavoidable. Despite it might be caused by various errors during the data collection or transportation, some anomalies potentially give important information such as indication of a new underlying process. The aim of anomaly detection task is to determine all such instances in the input dataset in a data-driven fashion. In the past decade, the proliferation of anomaly data in many domains have raised research interest resulted in a plethora of anomaly detection methods A vast number of previous study reports suggested that there is no single model will achieve the best performance for every dataset. This paper presents empiric results on the effect of several kernel functions to performance of One-Class Support Vector Machine (OC-SVM) as an anomaly detector model. The proposed model is tested using financial transactions of microfinance service dataset from an Indonesian Bank. The empiric results showed that OC-SVM model with Sigmoid and RBF kernels achieve the best statistically significant value of training, validation, and testing accuracies than the OC-SVM model with no-kernel, linear kernel and polynomial (degree 3,4,5,6) kernels. © 2019 IEEE.

关键词： Anomaly detection

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