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Pool Water Acidity Gauge Using Fuzzy Mamdani Method

Journal of Physics: Conference Series 2019年第1期1361卷

作者： Abdul Jabbar Lubis Ummul Khair Arnes Sembiring Ade Zulkarnain Dodi Siregar Student Doctor of Philosophy Computer Engineering Universitiy Malaysia Perlis Study Program of Informatics Faculty of Engineering and Computer Science Universitas Harapan Medan Jl. H.M. Jhoni No. 70 C Medan 20217 Indonesia

Swimming pool is one of the means of sports and play that is fun. Swimming pools must also be considered clean. In order to be replaced with new water. The goal is so that pool users are not infected with infectious diseases due to the dirty water inside the pool. The Mamdani method is the most common method when discussing fuzzy methodology. It was Ebrahim Mamdani who first proposed this method in 1975 when building a steam engine and boiler control system. Mamdani uses a collection of IF-THEN rules obtained from experienced operators / experts. Mamdani's work is actually based on the article 'The Father of Fuzzy, Lotfi A. Zadeh: fuzzy algorithms for complex systems and decision processes.

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A review of collisions in cryptographic hash function used in digital forensic tools

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Procedia computer science 2017年 116卷 381-392页

作者： Zulfany Erlisa Rasjid Benfano Soewito Gunawan Witjaksono Edi Abdurachman Doctor of Computer Science School of Computer Science Bina Nusantara University Binus Graduate Program Bina Nusantara University Binus Graduate Program School of Statiatics Bina Nusantara University

Digital forensic tool is a software used by digital evidence investigators to extract data and information from a digital evidence. The integrity of the digital evidence must be maintained through the chain of custody in order to be admissible in court. Most digital extraction tool use either MD5 (Message Digest) or SHA (Secured Hash Algorithm) hashing to check the integrity of digital evidence. The hashing algorithm has been found to have a weakness known as collision in which two different messages have the same hashing values. Although the probability of producing such weakness is very small, this collision can be used to deny the usage of the evidence in court of justice. After the first collision has been found, many cryptanalysts have tried to explore various methods to detect the collisions with shorter and efficient time. This paper is to review the existing methods in digital forensic tools that have been used to create a collision attacks in digital evidence.

关键词： MD5 digital evidence hash function collision digital forensic cryptography

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Data mining technique with cluster anaysis use K-means algorithm for LQ45 index on Indonesia stock exchange 1

Data mining technique with cluster anaysis use K-means algor...

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1st International Conference on Information and Communications Technology, ICOIACT 2018

作者： Condrobimo, A. Raharto Abbas, Bahtiar Saleh Trisetyarso, Agung Suparta, Wayan Kang, Chul-Ho Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Information System Department School of Information System Bina Nusantara University Jakarta11480 Indonesia Civil Engineering Department University of Technology Yogyakarta Yogyakarta Indonesia Department of Electronic and Communication Engineering Kwangwoon University Korea Republic of

ISBN: (纸本)9781538609545

This study aims to apply data mining techniques with cluster analysis on stock data registered in LQ45 in Indonesia Stock Exchange. The cluster analysis used in this method is k-means algorithm, the data in this research is taken from Indonesia Stock Exchange. The cluster analysis in this study analyzed the characteristics of data volumes and stock values, while the results in this study were presented in the form of cluster members visually. Therefore, this cluster analysis in this research can be used for quick and efficient identifier for each member of LQ45 index cluster based on share value for each cluster and its volume. The identification results can be used by beginner-level investors that begun to be interested in stock investments to help make informed decisions about stock trading on desired cluster groups. © 2018 IEEE.

关键词： Cluster analysis

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Tackling Imbalanced Class on Cross-Project Defect Prediction Using Ensemble SMOTE

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IOP Conference Series: Materials science and Engineering 2019年第6期662卷

作者： A Saifudin S W H L Hendric B Soewito F L Gaol E Abdurachman Y Heryadi Department of Informatics Engineering Pamulang University Jalan Raya Puspitek 46 Banten 15310 Indonesia Doctor of Computer Science Program Bina Nusantara University Jalan Kebon Jeruk Raya 27 Jakarta 11530 Indonesia

The dataset with imbalanced class can reduce the performance of the classifiers. In this study proposed a cross-project software defect prediction model that applies the SMOTE (Synthetic Minority Oversampling Technique) to balance classes in datasets and ensembles technique to reduce misclassification. The ensemble technique using AdaBoost and Bagging algorithms. The results of the study show that the model that integrates SMOTE and Bagging provides better performance. The proposed model can find more software defects and more precise.

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Ensemble Undersampling to Handle Unbalanced Class on Cross-Project Defect Prediction

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IOP Conference Series: Materials science and Engineering 2019年第6期662卷

作者： A Saifudin Y Heryadi Lukas Deparement of Informatics Engineering Pamulang University Jalan Raya Puspitek 46 Banten 15310 Indonesia Doctor of Computer Science Program Bina Nusantara University Jalan Kebon Jeruk Raya 27 Jakarta 11530 Indonesia

There has been much research which proposed for cross-project software defect prediction models but no models that perform very well with various datasets in general. Software defect dataset usually imbalanced because it contains far more the not defected modules than the defected modules. Class imbalances in the dataset can reduce the performance of classifiers in the software defect prediction model. In this study proposed a Random Undersampling algorithm to balance classes and ensemble techniques to reduce misclassification. The ensemble technique used is the AdaBoost and Bagging algorithm. The results showed that the software defect prediction model that integrates the Random Undersampling algorithm and AdaBoost provides better performance and can find more defects than other models.

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Plagiarism Detection for Indonesian Language using Winnowing with Parallel Processing

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Journal of Physics: Conference Series 2018年第1期978卷

作者： Y Arifin S M Isa L A Wulandhari E Abdurachman Computer Science Department BINUS Graduate Program – Doctor of Computer Science 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 Bina Nusantara University Jakarta Indonesia 11480

The plagiarism has many forms, not only copy paste but include changing passive become active voice, or paraphrasing without appropriate acknowledgment. It happens on all language include Indonesian Language. There are many previous research that related with plagiarism detection in Indonesian Language with different method. But there are still some part that still has opportunity to improve. This research proposed the solution that can improve the plagiarism detection technique that can detect not only copy paste form but more advance than that. The proposed solution is using Winnowing with some addition process in pre-processing stage. With stemming processing in Indonesian Language and generate fingerprint in parallel processing that can saving time processing and produce the plagiarism result on the suspected document.

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Performance test for prototype game for children with adhd

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Journal of Physics: Conference Series 2018年第1期978卷 012004-012004页

作者： Bahana, R Gaol, F L S W H L Hendric Abdurachman, E Wiguna, T Soewito, B Nugroho, E Dirgantoro, B P Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department Faculty of Computing and Media Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Faculty of Medicine University of Indonesia Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Kummara Game Design Studio Bandung Indonesia Graphic Design and New Media Program Visual Communication Design Department BINUS Northumbria School of Design Bina Nusantara University Jakarta Indonesia 11480

The gaming industry has become one of the fastest growing industries in the world. In recent years there have been several studies that have used games, especially computer-based ones to improve the executive function of children with Attention Deficit Hyperactivity Disorder (ADHD) especially in working memory improvements. There are still several obstacles in using computer-based games that have been circulating today in Indonesia. The aim of this research is to develop and create a prototype game that can be used to improve working memory of children with ADHD using Bahasa Indonesia. The prototype game application is a race game with matching colors and memory work tasks; developed using Construct2. Players will play as a driver, delivering certain fruits to specific homes with different colors. The game also included visuospatial tasks such as remembering the objects. For performance test, CPU utilization, average FPS and image memory usage has been tested in several browsers. In conclusion, the performance tests results show that the first type of the prototype game is good enough to be played in desktop or laptop.

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The prediction of scholarship recipients in higher education using k-Nearest neighbor algorithm

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IOP Conference Series: Materials science and Engineering 2018年第1期434卷

作者： D Kurniadi E Abdurachman H L H S Warnars W Suparta Department of Informatics Sekolah Tinggi Teknologi Garut Jalan Mayor Syamsu 1 Garut 44151 Indonesia Department of Computer Science Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

This article aims to implement the algorithm model of k-Nearest Neighbor (k-NN) in analyzing, predicting, and classifying students who have potentials to get scholarships in universities. The k-NN algorithm works by making a prediction based on the closest data points between the old data history as training data and the new data as testing data. The data collected totals 1018 students with 24 scholarship receiver candidate students are used as the dataset for the test purposes. The attributes used in the prediction process are a semester, parents' income, number of family dependents, and Cumulative Grade Point Average. The distance calculation of the value from testing attribute to each training attribute uses Euclidean Distance equation, while the test of the model accuracy value is calculated using Confusion Matrix. The results of the simulation of the prediction model show that the determining factor of training data from both the number and the variation of different values can improve the performance of the k-NN algorithm with the best accuracy rate of 95.83 percent in predicting students who have the greatest chance of getting the scholarship.

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Genetic variation of somaclonal mutants from the 8th generation of Pekalongan accession rodent tuber (typhonium flagelliforme lodd.) based on RAPD-PCR analysis

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IOP Conference Series: Earth and Environmental science 2018年第1期195卷

作者： Ragapadmi Purnamaningsih Nesti Fronika Sianipar Khoirunnisa Assidqi Harco Leslie Hendric Spits Warnars Indonesia Center for Agricultural Biotechnology and Genetic Resources Research and Development (BB-Biogen) Bogor 16111 Indonesia Food Technology Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia 11480 Research Interest Group Food Biotechnology Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

Rodent tuber is a potential plant which can be developed as an anticancer drug. The rodent tuber plant has a low anticancer compound which does not have an economic value to be utilized on an industrial scale, particularly to explore as an anticancer drug. The material plant was used 30 clones of Rodent Tuber Pekalongan to increase its bioactive compounds using a combination of in vitro culture with gamma-ray irradiation. The selection process has been done until the 8th generation and obtained 14 somaclonal mutants that have higher bioactive compounds than control plant (non-mutant). This study aimed to analyze the genetic variation of 14 somaclonal mutants of rodent tuber using RAPD with 14 primers. The results were produced 513 total bands with the size of 200-5000 bp and 380 polymorphic bands between somaclonal mutants. OPB-18 primer produced the most polymorphic bands and five specific polymorphic bands of 1336 bp, 1070 bp, 901 bp, 861 bp and 728 bp in the somaclonal mutant M23 (20-4-2-1-1-1). OPD-20 primer produced seven specific polymorphic bands of 1574 bp, 1557 bp, 1501 bp, 1496 bp, 1234 bp, 1229 bp and 1086 bp in the M23 somaclonal mutant. The phylogenetic analysis showed that there were two main groups with the coefficient similarity between 0.77 and 0.83. The highest genetic variation obtained was found in the M23 somaclonal mutant with a genetic difference of 23% compared with control. There are five somaclonal mutants (M24, M22, M21, M16, M14) that have a genetic variation of up to 22% over the control. This study shows that OPB-18 and OPD-20 primers were efficient in detecting somaclonal mutant variants.

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Software size measurement of knowledge management portal with use case point

Software size measurement of knowledge management portal wit...

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International Conference on computer, Control, Informatics and Its Applications (IC3INA)

作者： Karto Iskandar Ford Lumban Gaol Benfano Soewito Harco Leslie Hendric Spits Warnars Raymondus Kosala Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Binus Graduate Program Bina Nusantara University West Jakarta DKI Jakarta ID School of Computer Science

ISBN: (纸本)9781509023240

Knowledge Management portal is a system to support Knowledge Management process, in order to create, capture, develop, share, reuse and optimize the knowledge and particularly in Bina Nusantara University which has implemented Knowledge Management System (KMS) since 2002. However, this KMS need to be measured in order to know how better this KMS in term of the software size. The BINUS KMS will be measured in term of their software size in functionality perspective with use case point method. This metric of KMS will be used by management to know how better the software size, complexity level and effort to development in numbering. Measurement of software size with software metric such as Use Case Point upon use case diagram for BINUS knowledge Management Portal shows that the project has medium software size with score Use Case Point (UCP) = 108.56 and has estimate effort will be developed in 2,064 hours (or in 258 days or 51.6 weeks or 12.9 months) and has development cost for 516,000,000.00 rupiah (Indonesian currency). Use Case Point, estimate effort and project value will powerful to help management in order to make decision regarding the implementation of IT software project development in term of time, money and people.

关键词： Software Software measurement Complexity theory Size measurement Knowledge management Unified modeling language Portals

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