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8th International Conference on Cyber and IT Service Management, CITSM 2020

作者： Henderi Maulana, Miftah Warnars, Harco Leslie Hendrie S. Setiyadi, Didik Qurrohman, Taufik University of Raharja Department of Informatics Engineering Tangerang Indonesia Postgraduate of Information Engineering University of Raharja Tangerang Indonesia BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Bina Insani University Department of Informatics Engineering Bekasi Indonesia

ISBN: (纸本)9781728177014

The government in Indonesia and its staff work together to make tactical steps to prevent the spread of COVID-19 in the community. From the ministerial level to the heads of the provinces, regencies, and even the government. Therefore, this study aims to make a model decision support system to diagnose patients exposed to Covid-19, such as people in control, patients in oversight, and those who are positive for the Covid-19 Virus. Model decision support system development aims to provide information about the development of COVID- 19 and help the community in diagnosing themselves related to COVID-19 infection. In this study, the authors use the forward chaining method in application to get conclusions from the symptoms of the Covid-19. This research resulted in an application that patients exposed to the Covid-19, and it's also provided a solution for healing from patients. And this could be a reference for patients before consulting further with the doctor. © 2020 IEEE.

关键词： Decision support systems

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The development of video analysis instrument to determine teacher's character

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AIP Conference Proceedings 2023年第1期2594卷

作者： Y. B. Gromang M. A. Rudhito D. Sudigyo T. Suparyanto B. Pardamean Department of Mathematics Education Universitas Sanata Dharma Paingan Maguwoharjo Depok Sleman Yogyakarta Indonesia 55282 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

This study aims to develop a valid and reliable video analysis instrument to determine teachers’ character in the opening lesson in terms of its utterances and produce video analysis on micro-teaching that will be used in training related to Artificial Intelligence (AI). The type of research used is research and development. The subject of this research is the micro-teaching video of class E students’ batch 2019, Mathematics Education Study program at Sanata Dharma University. The product of this research is a video analysis instrument to find out the character of the prospective teachers, such as confidence, enthusiasm, and happiness in terms of voice utterances. This study uses the ADDIE research model. The results show that the video analysis instrument has a validity value of 4.80 which means it's very valid. Video analysis instrument to find out the enthusiastic character has a value of validity of 4.70, which means it's very valid. Then, the video analysis instrument to find out the character of happiness has a validity value of 4.60 which means it's very valid. The practicality of the developed video analysis instrument meets the required criteria with a practicality value of 4.31. Overall, the video analysis instrument developed belongs to an effective category.

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MVC Architecture: A Comparative Study Between Laravel Framework and Slim Framework in Freelancer Project Monitoring System Web Based

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Procedia computer science 2019年 157卷 134-141页

作者： Andri Sunardi Suharjito Computer Science Department Binus Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Currently, the work of freelancers is very much in demand. Because freelancers can work anywhere and anytime without being bound by a contract with a company or person. But freelancers have difficulty managing their tasks and projects because there is no system to monitor and manage the project. Therefore, the solution is to make the project freelancer monitoring system by implementing the MVC (Model View Controller) architecture model with the PHP Laravel and Slim framework. MVC design patterns are well-known patterns and are used for interactive software system architectures. The way the MVC method works is to separate the main components such as data manipulation (model), display/interface (View) and the process (Controller) so that it is more neat, structured and easily developed. The purpose of this study also compares the MVC Laravel and Slim framework architecture with a performance comparison method on load/stress testing on the dashboard page using Apache JMeter tools with 3 scenarios from samples 1, 100, and 500. Tests are done offline and report format results of performance tests is a Summary Report. The results obtained from performance comparisons using Apache JMeter are that the Slim framework is faster and better than Laravel's framework.

关键词： Web Application Mvc Architecture Laravel Framework Slim Framework Compare Apache Jmeter Project Monitoring System

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Solution of SEIRD mathematical model for the COVID-19 transmission using microsoft excel

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AIP Conference Proceedings 2023年第1期2594卷

作者： D. P. W. Putra M. A. Rudhito D. Sudigyo T. Suparyanto B. Pardamean Department of Mathematics Education Faculty of Teacher Training and Education Sanata Dharma University Yogyakarta Indonesia 55281 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Mathematical modeling in the epidemiology study can be applied to describe the current transmission of viruses, one of which is compartments. However, this simulation model is rig...

Mathematical modeling in the epidemiology study can be applied to describe the current transmission of viruses, one of which is compartments. However, this simulation model is rigorous to understand, especially in interpreting the parameter values in influencing the solution. Therefore, it is necessary to present a coherent mathematical model solution. This study aims to determine the SEIRD model solution in the COVID-19 transmission using Microsoft Excel with three conditions (normal, new normal, and lockdown) to facilitate the interpretation of data. The SEIRD model used in this study considers natural population growth, namely natural births and deaths. Three stages to evaluate the model solution in this study are constructing a mathematical model, deciding the parameter intervals, and creating an applet in Microsoft Excel. The system of differential equations is converted into a system of difference equations to obtain numerical model solutions. The results showed that the differences in the infection rates for old normal, new normal, and lockdown conditions were 24%, 4%, and 3%, respectively.

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Automatic Sleep Stage Classification using Weighted ELM and PSO on Imbalanced Data from Single Lead ECG

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Procedia computer science 2019年 157卷 321-328页

作者： Oei Kurniawan Utomo Nico Surantha Sani Muhamad Isa Benfano Soewito Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Sleep stage classification is one of important aspects in sleep studies, which can give clinical information for diagnosing sleep disorder and measuring sleep quality. Due to the difference in sleep stage proportion for every person, the collected sleep stage data are imbalanced naturally, which can lead to high probability of misclassification. Various learning method has been developed to classify sleep stage based on electrocardiogram (ECG) signal. However, to the best of our knowledge, there are no researches which consider the imbalanced dataset problem for sleep stage classification. In this research, a classification model of sleep stage based on ECG signal was developed using Weighted Extreme Machine Learning (WELM) to deal with imbalanced learning dataset and Particle Swarm Optimization (PSO) for feature selection. The research will use the MIT-BIH Polysomnographic Database, which contains 10154 sleep stage annotated ECG data which consist of 17.79%, 38.28%, 4.76%, 1.78%, 6.89%, and 30.5% data of NREM1, NREM2, NREM3, NREM4, REM, and awake stage respectively. From each ECG record, a total of 18 features were extracted and the feature selection process resulted in 10 features which highly affect the sleep stage classification. The proposed model successfully obtained a mean accuracy of 78,78% for REM, NREM and Wake stage classification and 73.09% for Light Sleep, Deep Sleep, REM, and Wake stage classification.

关键词： Sleep stage Classification Machine learning Weighted extreme learning machine

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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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Air Pollution Mapping using Mobile Sensor Based on Internet of Things

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Procedia computer science 2019年 157卷 638-645页

作者： Eduard Pangestu Wonohardjo Gede Putra Kusuma Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Air pollution is hazardous to our health, especially carbon monoxide. It can cause diseases such as cough, runny nose, eye irritation, and even death. The main objective of this research is to create a device capable of detecting carbon monoxide pollution levels by using mobile sensors and map the results into heatmaps overlayed on Google Maps. We have implemented an integrated pollution monitoring and mapping system that consists of MQ-7 sensor, GPS, GSM, display module, Arduino board, and web-server. We also evaluated two sampling methods, time-based and distance-based sampling. Based on our experiments, the distance-based sampling method produced well-distributed data and closer to the expected between-samples distances compared to the time-based method. We have also shown that our system can run in real time to monitor the carbon monoxide pollution levels.

关键词： CO pollution Pollution sensor Pollution mapping Mobile sensor Internet of things

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Early Detection of Diabetes Mellitus using Feature Selection and Fuzzy Support Vector Machine

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Procedia computer science 2019年 157卷 46-54页

作者： Rian Budi Lukmanto Suharjito Ariadi Nugroho Habibullah Akbar Computer Science Department Binus Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

The number of patients that were infected by Diabetes Mellitus (DM) has reached 415 million patients in 2015 and by 2040 this number is expected to increase to approximately 642 million patients. Large amount of medical data of DM patients is available and it provides significant advantage for researchers to fight against DM. The main objective of this research is to leverage F-Score Feature Selection and Fuzzy Support Vector Machine in classifying and detecting DM. Feature selection is used to identify the valuable features in dataset. SVM is then used to train the dataset to generate the fuzzy rules and Fuzzy inference process is finally used to classify the output. The aforementioned methodology is applied to the Pima Indian Diabetes (PID) dataset. The results show a promising accuracy of 89.02% in predicting patients with DM. Additionally, the approach taken provides an optimized count of Fuzzy rules while still maintaining sufficient accuracy.

关键词： Diabetes Mellitus Feature Selection Fuzzy Logic Support Vector Machine

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Evaluation Model for the Implementation of Information Technology Service Management using Fuzzy ITIL

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Procedia computer science 2019年 157卷 290-297页

作者： Rudy Yandri Suharjito Ditdit Nugeraha Utama Amalia Zahra Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Information technology (IT) service management is an essential part for development of a company’s IT. This case study discusses how to convalesce IT services using the information technology infrastructure library (ITIL) framework and measure service level management (SLM) using Fuzzy ITIL (FITIL) approach. This paper aims to obtain an appropriate model for the measurement of IT service management by using fuzzy approach. Besides that, this paper aims to be able to provide an improving recommendations and IT governance based on current value (as is) and expected value (to be). The research method functioned is by measuring maturity level using best practice of ITIL v3 to condition before and after of improving process based on a questionnaire that has been performed. After obtaining the value of the maturity level for each cycle within ITIL, then the value will be created as an input for FITIL. The manufacture of FITIL is done in 4 stages, namely fuzzification, knowledge base, inference, and defuzzification. The results of the conditions before and after of the improving process have been successful in increasing the level of maturity in each ITIL cycle. The case study indicates an improvement in the increased level of maturity in SLM with FITIL approach.

关键词： Fuzzy Logic ITIL Maturity Level

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Systematic Literature Review on Decision-Making of Requirement Engineering from Agile Software Development

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Procedia computer science 2019年 157卷 274-281页

作者： Reginald Putra Ghozali Herry Saputra M. Apriadin Nuriawan Suharjito Ditdit Nugeraha Utama Ariadi Nugroho Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

This paper presents a systematic literature review of agile software development at decision making method for requirement engineering. Presently, agile software development method is operated to cope with requirements that changes dynamically. This study seeks to find out and discuss what types of method that have been exploited for decision making on managing feasible requirements and challenges of decision making in agile software development. Papers reviewed in this study are published from 2017 to present. Resulting 8 papers that have been identified of presenting decision making methods. Using these papers, 11 methods and 7 challenges of decision making identified. This study contributes a review of requirement management and engineering by providing decision making methods on agile software development and the challenges of decision making for requirement engineering.

关键词： Systematic Literature Review Agile Software Development Decision Making Requirement Engineering

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