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Fast artificial bee colony for clustering

Informatica (Slovenia) 2018年第2期42卷 211-219页

作者： Girsang, Abba Suganda Muliono, Yohan Fanny, Fanny Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Artificial Bee Colony (ABC) is one of good heuristic intelligent algorithm to solve optimization problem including clustering. Generally, the heuristic algorithm will take the high computation time to solve optimization problem. Likewise, ABC also consumes too much time to solve clustering problem. This paper intends solving clustering problem using ABC with focusing reduction computation time called FABCC. This idea proposes detecting the pattern of redundant process then compacting it to effective process to diminish the computation process. There are five data sets to be used to prove the performance of FABCC. The results shows that FABCC is effective to prune the duration process up to 46.58 %. © 2018 Slovene Society Informatika. All rights reserved.

关键词： Heuristic algorithms

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The accuracy of the F statistic for structural health monitoring

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AIP Conference Proceedings 2020年第1期2227卷

作者： Fergyanto E. Gunawan Benfano Soewito Nico Surantha Tuga Mauritsius Nobumasa Sekishita 1Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480 2Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 3Information Systems Management Department BINUS Graduate Program – Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 4Department of Mechanical Engineering Toyohashi University of Technology Toyohashi Aichi 441-8580 Japan

Understanding the reliability of engineering methods is crucial for its adoption and deployment. This research focuses on the reliability of the Power Spectral Density (PSD) method via the use of the F statistic for damage detection. To the author best knowledge, the method is rather classic but its realibility has not been discussed in the context of a large data size. Priory, the research anticipates that the accuracy is a function of the damage level. In this study, we evaluate 3500 cases with five levels of structural integrity, namely, healthy condition and damaged conditions with 1%, 5%, 10%, and 20% damage levels. The dataset is established via a numerical analysis of a seven degree-of-freedom system loaded with a concentrated dynamic force with random magnitude. A spring on the system is reduced in its stiffness to simulate damages. Our significant findings are the following: it is challenging for the PSD-based method to differentiate the healthy condition from the damaged conditions when the damage level is small. However, the reliability is high at 95% probability when the structural integrity has dropped by five percent.

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Genetic Algorithm in Image Inserting with Modified Least Significant Bit Method to Find The Best MSE Value

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Journal of Physics: Conference Series 2020年第1期1566卷

作者： S F Ramadhan P Sihombing Sutarman Department of Information and Technology Faculty of Computer Science and Information Technology University of Sumatera Utara Medan Indonesia Master Program (S2) of Informatics Engineering Faculty of Computer Science and Information Technology University of Sumatera Utara Medan Indonesia.

Inserting data into digital media tends to change the large size of the media cover file, this is because the inserted pixel has a different size from the insertion value, i.e. with a larger or smaller value, for example a pixel value of 10 is inserted with larger or smaller data from the value 10. So that the pixel value is getting further from the value of 10, this causes the value of Mean Squared Error (MSE) of the media of the cover (cover) to become larger. In this study, the selection of pixels in the image is in accordance with the value of the insertion data as the insertion place with the Genetic algorithm (GA). Insertion of data on selected pixels using the GA algorithm is performed using the Modified Least Significant Bit (MLSB) algorithm at the position of the least significant bits. To find out the reliability of the proposed algorithm, the data insertion experiment was carried out by comparing the conventional LSB algorithm with the proposed algorithm where the results obtained a significant MSE value, i.e. the average MSE value of the LSB algorithm was 20.54 and the proposed algorithm was 7.12.

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Numerical analysis of general-vibration-based method for structural health monitoring

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AIP Conference Proceedings 2020年第1期2227卷

作者： Fergyanto E. Gunawan Benfano Soewito Nico Surantha Tuga Mauritsius Nobumasa Sekishita 1Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480 2Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 3Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 4Department of Mechanical Engineering Toyohashi University of Technology Toyohashi Aichi 441-8580 Japan

For damage detection, this research article discusses an easy-to-compute damage index derived from the governing dynamic of the structure that has potential practical application in Structural Health Monitoring (SHM). The research uses simplified structural models to explore the sensitivity of the index to damages, to compare the index performance with a traditional but popular damage detection method, and to understand the local/global predictive capability of the index. The research uses two simple models, namely, single- and two-degree-of-freedom systems. The results suggest that the damage index is local, that can only monitor damages occurring near the points of measurements, but it is sensitive to damages, unlike the natural frequency, which is global but less sensitive.

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Measurement of activeness lecturers in SmartLecturer based learning using fuzzy Mamdani and Sugeno

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IOP Conference Series: Materials science and Engineering 2020年第1期725卷

作者： Sfenrianto Sfenrianto Muhammad Yasin Kaman Nainggolan Mesra Betty Yel Information Systems Management Department BINUS Graduate Program – Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Informatics Management Politeknik LP3I Jakarta Indonesia 10450 Master of Computer Science - Postgraduate Programs STMIK Nusa Mandiri Faculty of Computer Science STIKOM CKI Jakarta Indonesia

The success of learning in a classroom that uses supporting media demands lecturer activity. The level of activity of lecturers in class and using learning media such as Smart lecturer can be measured using a fuzzy logic approach. This study aims to measure the level of active lecturers using the approach, namely: Mamdani and Sugeno method. Stages of lecturer activity measurement by forming a fuzzy set, composition rules as many as 24 rules and the defuzzification process using the centroid method that produces the level of activity of each is low, medium and high. Based on 173 lecturer activity data, the results of the Mamdani method indicates low 66%, medium 31%, and high 3%. While the Sugeno method produces a level of activity low 75%, moderate 17%, and high 8%. Therefore, Mamdani method is more suitable for the calculation because the spread of results is relatively evenly distributed at each level.

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Assessment of the implementation of customer relationship management systems to support the competitive advantage of the company

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IOP Conference Series: Earth and Environmental science 2021年第1期747卷

作者： W Sardjono M N F Izrullah E Selviyanti M Mukhlis G R Putra Information Systems Management Department BINUS Graduate Program – Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Health Department Politeknik Negeri Jember Jember Jawa Timur Indonesia 68124 Faculty of Teacher Training and Education State Islamic Institute of Jember Indonesia Indonesia Computer Science Study Program Faculty of Mathematics & Natural Sciences Pakuan University Bogor Indonesia

The purpose of this study is to look for factors, indicators, and build a model of readiness for effective and efficient implementation in order to answer the problems that arise at PT XYZ related to the readiness of Customer Relationship Management (CRM) implementation. The research method used is the method of collecting data by observing, interviewing, and distributing questionnaires to respondents using the CRM Value Chain theory as a conceptual framework and the research method used in this research is factor analysis to process data obtained from questionnaires. In this study managed to get new factors along with the constituent indicators of these factors as well as an ideal readiness model. It can be concluded that factors related to the readiness of implementing Customer Relationship Management among others are Customer Service Information, Customer Relations Value, Lack of Service and Communication.

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Transfer Learning from Chest X-Ray Pre-trained Convolutional Neural Network for Learning Mammogram Data

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Procedia computer science 2018年 135卷 400-407页

作者： Bens Pardamean Tjeng Wawan Cenggoro Reza Rahutomo Arif Budiarto Ettikan Kandasamy Karuppiah Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 NVIDIA Corporation

Breast cancer is one of the deadliest cancer for female nowadays. Despite of the rapid advancement in medical image analysis with the rise of deep learning, development of breast cancer detection system is limited due to relatively small size of the publicly available mammogram dataset. In this paper, we discover an effective configuration for transfer learning from Chest X-Ray pre-trained Convolutional Neural Network to overcome the small-size mammogram dataset problem. We found that the best configuration achieve 90.38% validation accuracy for modified.

关键词： Transfer learning Convolutional neural network Medical image analysis Chest X-ray Mammogram

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EBITDA Time Series Forecasting Case study: Provincial Waterworks Authority

EBITDA Time Series Forecasting Case study: Provincial Waterw...

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International ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications Engineering (ECTI-NCON)

作者： Kraisak Khusuwan Kitsana Waiyamai Master of Science Program in Information Technology Computer Engineering Kasetsart University Lak Si 343/347 Plum condo Chaengwattana Chaengwattana Rd. Talat Bang Khen Bangkok Computer Engineering Kasetsart University Chatuchak 50 Ngam Wong Wan Rd. Lad Yao Bangkok

EBITDA is a measure of a company's financial performance. It can determine the direction of business decisions for the organization, can be used to analyze and compare profitability among companies. By its linear and non-linear combination, appropriate forecasting technique must be determined. The aim of this paper is to propose a methodology for forecasting EBITDA. We propose a three-steps methodology which is composed of data preparation, forecasting model comparison and evaluation steps. The results from using 10 years monthly data of the Provincial Waterworks Authority (PWA) reveal that the best model is ARIMA-ANN hybrid model. Thus, this model can be used to forecast the other time series data such as Selling Expenses, Operating Expense, General and Administrative Expenses in the future.

关键词： Data models Forecasting Time series analysis Predictive models Computational modeling Artificial neural networks Buildings

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Outliers Detection in Time Series Data : Case study: Provincial Waterworks Authority

Outliers Detection in Time Series Data : Case study: Provinc...

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International ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications Engineering (ECTI-NCON)

作者： Isara Khongsrabut Kitsana Waiyamai Master of Science Program in Information Technology Computer Engineering Kasetsart University 343/313 Plum condo Chaengwattana Chaengwattana Rd. Talat Bang Khen Lak Si Bangkok Computer Engineering Kasetsart University 50 Ngam Wong Wan Rd. Lad Yao Chatuchak Bangkok

One main cause of inaccurate forecasts is that data may contain noises and outliers. In the case of the Provincial Waterworks Authority (PWA), the inaccuracy of analyzing and forecasting the number of water users is due to outliers contained in data sources. Some branches of PWA collected errors such as the very high or very low number of water users. This has a direct impact on the quality and reliability of the predictive accuracy output. The removal of the “outliers” is thus critical for accurate interpretation of the data. The purpose of this paper is to detect outliers in water consumption time series data. We examined two techniques: (1) a method based on autoregressive integrated moving average (ARIMA) time series modeling and (2) median absolute deviation (MAD). A clustering technique (K-Mean) is used as a pre-processing step in order to identify appropriate parameters for the two outliers detection techniques. The results showed that, with the precise parameter values obtained from K-Mean, both ARIMA and MAD performed very well on water consumption time series data. The two techniques are able to generate high sensitivity and specificity outputs.

关键词： Time series analysis Anomaly detection Forecasting Digital art Media Telecommunications High frequency

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Prevention Structured Query Language Injection Using Regular Expression and Escape String

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Procedia computer science 2018年 135卷 678-687页

作者： Benfano Soewito Fergyanto E. Gunawan Hirzi Frumentius Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480 Investment Coordinating Board of the Republic of Indonesia Jakarta Indonesia 12190

Information technology enables for new way of commerce, which is a commerce activities through online media (e-commerce). Security becomes an important issue in online-system, because such system is accessible by anyone through the global network -internet. Security in terms of confidentiality, integrity, and availability becomes goals that must be achieved by any system generally, and commerce system especially, because this kind of system contains many sensitive data like customer data and transaction data. SQL Injection is a vulnerability and threat, with the most occurrence in a web based system. In this research we evaluate and analyze source code against SQL injection, and we use regular expression and escape string to prevent the SQL injection. The results of this study are findings of system vulnerability against SQL injection, which are proven by the ability to get data from database, with SQL injection techniques. System vulnerabilities were analyzed, in order to design and implement the solution for it. The solutions then tested, to validate that it has proven effectively fix the vulnerabilities, and can prevent the exploitation by SQL injection. In the end, the conclusion is that initially the system is vulnerable against SQL injection, but then the solution that being implemented has proven effectively fix the issue.

关键词： SQL Injection regular expression escape string e-commerce vulnerability

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