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Rapid Detection of Oil Pollution in Soil by Using Laser-Induced Breakdown Spectroscopy

Plasma science and Technology 2016年第12期18卷 1186-1191页

作者： Ali KHUMAENI Wahyu Setia BUDI Asep Yoyo WARDAYA Rinda HEDWIG Koo Hendrik KURNIAWAN Department of Physics Faculty of Science and Mathematics Diponegoro University JI. Prof. Soedharto SH. Tembalang Semarang 50275 Indonesia Master Program in Energy School of Postgraduate Studies (SPS) Diponegoro University JI. Imam Barjo SH. Pleburan Semarang 50241 Indonesia Computer Engineering Department Bina Nusantara University K. H. Syahdan 9 Jakarta 11480 Indonesia Research Center of Maju Makmur Mandiri Foundation 40 Srengseng Raya Kembangan Jakarta Barat 11630 Indonesia

Detection of oil pollution in soil has been carried out using laser-induced breakdown spectroscopy（LIBS）. A pulsed neodymium-doped yttrium aluminum garnet（Nd：YAG） laser（1,064 nm, 8 ns, 200 mJ） was focused onto pelletized soil samples. Emission spectra were obtained from oil-contaminated soil and clean soil. The contaminated soil had almost the same spectrum profile as the clean soil and contained the same major and minor elements. However, a C–H molecular band was clearly detected in the oil-contaminated soil, while no C–H band was detected in the clean soil. Linear calibration curve of the C–H molecular band was successfully made by using a soil sample containing various concentrations of oil. The limit of detection of the C–H band in the soil sample was 0.001 mL/g. Furthermore, the emission spectrum of the contaminated soil clearly displayed titanium（Ti） lines, which were not detected in the clean soil. The existence of the C–H band and Ti lines in oil-contaminated soil can be used to clearly distinguish contaminated soil from clean soil. For comparison, the emission spectra of contaminated and clean soil were also obtained using scanning electron microscope-energy dispersive X-ray（SEM/EDX） spectroscopy,showing that the spectra obtained using LIBS are much better than using SEM/EDX, as indicated by the signal to noise ratio（S/N ratio）.

关键词： laser-induced breakdown spectroscopy LIBS oil pollution soil analysis C–H molecular band

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Predicting Relegation Clubs in Italian Serie A with Method based C4.5 Decision Tree Algorithm

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Journal of Physics: Conference Series 2020年第1期1471卷

作者： F Syukmana E Wahyudi W Gata H Wahono N I Febianto A Y Kuntoro R O Nitra L Effendi D D Saputra O R Sulaeman Master of Computer Science Postgraduate Program STMIK Nusa Mandiri Indonesia Graduate School Master's Degree Computer Science STMIK Nusa Mandiri Indonesia

The purpose of this study is to help small clubs from Italian Serie A in finding the minimum targets to avoid relegation into Serie B competition (below Serie A league). Relegation will reduce the club's income from TV revenues and the decline of enthusiastic supporters. Based on the data from the final standings (seasons 2006 until 2018), this can be explained by the Decision Tree method using the C4.5 algorithm. The methods used in this study are data collection, data pre-processing, model proposal, model testing, and model validation. In this study, it is expected that the value of accuracy exceeds 85% to achieve a proper classification.

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Information Retrieval System to Find Articles and Clauses in UUD 1945 Using Vector Space Model Method

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Journal of Physics: Conference Series 2020年第1期1471卷

作者： Sulaeman, O R Wahyudi, E Hakim, M J Subandi, R Setiyawan, R Pratama, B Gata, W Master of Computer Science Postgraduate Program STMIK Nusa Mandiri Indonesia Graduate School Master’s Degree Computer Science STMIK Nusa Mandiri Indonesia

This study aims to find articles and clauses from the 1945 Constitution (UUD 1945) using the Vector Space Model method that calculates the similarity of many documents. One document is represented by one clause from each article of the 1945 Constitution. The next step is pre-processing by deleting unnecessary words (stopwords) and changing it into basic words (stemmer) in the Indonesian language. Each document will be indexed to speed up query and simplify the weighting. Words weighting in documents is performed using the TF-IDF (Term Frequency-Inverse Document Frequency) algorithm by calculating the frequency of words in documents and all documents. The document search results will be presented in the ranking with the largest number of scoring appears at the top (descend sorting). The word search in this system more or less takes 90-100 milliseconds in 73 documents.

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RepositORE: A Learning Objects Repository for Educational Robotics

RepositORE: A Learning Objects Repository for Educational Ro...

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IEEE Latin American Robotics Symposium, LARS

作者： Kefton David Nunes De Melo Cleyton Carlos Santos Costa Thalia Katiane Sampaio Gurgel Sebastião Emidio Alves Filho Computer Science Course State University of Rio Grande do Norte Mossoró RN Brazil Master's Course in Computer Science Rio Grande do Norte State University (UERN) and Federal University of the Semi-Arid Region (UFERSA) Mossoró RN Brazil Postgraduate Program in Computer Science - PPgCC UERN/UFERSA Rio Grande do Norte State University (UERN) and Federal University of the Semi-Arid Region (UFERSA) Mossoró RN Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

Education is a motivating area for the use of technologies because the learning process can become more dynamic and interesting. Among the technological resources used in education, Educational Robotics stands out by enabling the development of technological projects that can involve techniques of construction and manipulation of robots and enable the development of the creative process, logical reasoning, and interdisciplinarity. However, acquiring knowledge in this area can be a complex task since the learning objects are spread due to the increase in content production brought by the massive use of the Internet. Thus, the present work has as a general objective present RepositORE, a repository where these objects of Educational Robotics can be stored and searched by users who need to acquire specific abilities. For Educational Robotics objects to be found faster and achieve their technical and pedagogical goals, the system uses metadata for the correct description of stored objects based on the Dublin Core Metadata standard. To improve and simplify the search for objects, an adaptation and extension of the Dublin Core standard was made to represent the specific information for Educational Robotics. RepositORE allows users to insert new content and collaborate through complementing information from objects registered by other users.

关键词： Conferences Education Production Metadata Search problems Cognition Internet

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Sentiment Analysis of the Indonesian Police Mobile Brigade Corps Based on Twitter Posts Using the SVM And NB Methods

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Journal of Physics: Conference Series 2019年第1期1201卷

作者： Bryan Pratama Dedi Dwi Saputra Deny Novianti Endah Putri Purnamasari Antonius Yadi Kuntoro Hermanto Windu Gata Nia K Wardhani Sfenrianto Sfenrianto Sularso Budilaksono Master of Computer Science-Postgraduate Program STMIK Nusa Mandiri Jakarta Indonesia Graduate School Master's Degree Computer Science STMIK Nusa Mandiri Jakarta Indonesia Master Faculty of Computer Science-Postgraduate Program Universitas Mercubuana Jakarta Indonesia Information Systems Management Department BINUS Graduate Program–Master of Information Systems Management Bina Nusantara University Jakarta Indonesia Graduate School Master's Degree Computer Science Universitas Persada Indonesia YAI. Jakarta Indonesia

The Brimob Corps is a special police force, just like the special military detachments held by the TNI such as Paskhas and so on. At present brigade corps police national is busy being discussed in the real world and cyberspace, especially on social media twitter. Many opinions about the brigade corps police national so there are positive and negative opinions. Social media twitter is now one places to spread information about brigade corps police national. This study cases uses text mining techniques with support vector machine (SVM) method which aims to classify public sentiments towards brigade corps police national on twitter. The dataset used is tweet in Indonesian with keyword 'Brimob' with a total dataset of 1000 tweets. Text mining, transform, tokenize, stemming, and classification, etc. techniques are useful for building classification and analysis of sentiment. RapidMiner and Gataframework are also used to help create sentiment analysis to measure classification values. Accuracy values obtained with support vector machine (SVM) approach 86,96%, with precision values of 86,96%, and recall values of 86,96%.

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Optimization Sentiments of Analysis from Tweets in myXLCare using Naïve Bayes Algorithm and Synthetic Minority Over Sampling Technique Method

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Journal of Physics: Conference Series 2020年第1期1471卷

作者： Dedi Dwi Saputra Windu Gata Nia Kusuma Wardhani Ketut Sakho Parthama Hendra Setiawan Sularso Budilaksono Dimas Yogatama Agus Hadiyatna Endah Putri Purnamasari Bryan Pratama Deny Novianti Master of Computer Science-Postgraduate Program Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri Jakarta Indonesia Graduate School Master's Degree Computer Science Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri Jakarta Indonesia Master Faculty of Computer Science-Postgraduate Program University of Mercubuana Jakarta Indonesia Graduate School Master's Degree Computer Science University Paramita Indonesia Jakarta Indonesia Graduate School Master's Degree Computer Science STMIK Bani Saleh Jakarta Indonesia Graduate School Master's Degree Computer Science University of Persada Indonesia YAI Jakarta Indonesia Graduate School Master's Degree Computer Science University of Gadjah Mada Jakarta Indonesia

Text mining can be used to classify opinions about complaints or not complaints experienced by XL customers. This study aims to find and compare classifications in the sentiments of analysis from the view of XL customers. This dataset was derived from tweets of XL customers written on myXLCare Twitter account. In text mining techniques, 'transform case', 'tokenize', 'token filters by length', 'n-gram', 'stemming' were used to build classification and sentiments of analysis. Gataframework tools were used to help during preprocessing and cleansing processes. RapidMiner is used to help create the sentiment of analysis to search and compare two different classifications methods between datasets using the Naïve Bayes algorithm only and Naïve Bayes algorithm with Synthetic Minority Over-sampling Technique (SMOTE). The results of the two methods in this study found that the highest results were using the Naïve Bayes algorithm with Synthetic Minority Over-sampling Technique (SMOTE) with an accuracy of 86.33%, precision 82.85%, and recall ratio 92.38%.

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Unbalanced Data Clustering with K-Means and Euclidean Distance Algorithm Approach Case Study Population and Refugee Data

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Journal of Physics: Conference Series 2020年第2期1477卷

作者： NM Faizah Surohman L Fabrianto Hendra R Prasetyo Information Systems Department Tama Jagakarsa University Jakarta Indonesia Master of Computer Science-Postgraduate Program STMIK Nusa Mandiri Jakarta Indonesia

There is a lot of data that does not have a pattern and unbalanced that is difficult to classify, such as the total population of each country in the world is very varied especially when compared with the number of refugees from each of these countries, China and India numbered more than 2 billion people but the number of refugees is only 0, 01%, while Syria around 70% of the 18 million more residents are refugees. By using the K-Means algorithm, we can group countries that have similar characteristics of population and number of refugees, the average percentage of refugees to the population in each cluster is the character of the cluster. The methodology used in this study are: measures the distance of the data using the Euclidean distance formula, runs the K-Means algorithm, calculate the percentage value of each cluster and find conclusions from the characteristics of the clusters formed. We found how machine learning made a pattern of data without political and social issues, the result is K-Means describing machine learning can grouped every country in cluster that make sense.

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

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Journal of Physics: Conference Series 2019年第1期1179卷

作者： Mohamad Kartiko 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.

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Evaluation of PHP Framework Measured Using Object-Oriented Metrics with the Analytic Hierarchy Process

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IOP Conference Series: Materials science and Engineering 2020年第1期874卷

作者： R Setiyawan W Gata Elbiansyah D Ardiansyah D Yuliandari D Wijayanti F P Harmono Y Komalasari M Lase M H Fakhriza Master of Computer Science Postgraduate Program STMIK Nusa Mandiri Indonesia Information System Universitas Bina Sarana Informatika Indonesia Information Technology Universitas Bina Sarana Informatika Indonesia Information Technology Postgraduate Program STMIK Nusa Mandiri Indonesia

The existence of various PHP frameworks may become one alternative choice in developing a web application that PT XYZ wants to evaluate its Wisanggeni internal PHP framework in order to measure how far the design quality of Wisanggeni framework is working. An evaluation on PHP framework using object-oriented metric parameter and design quality is then conducted in this research. The results of measurement conducted using object-oriented metric parameters for each framework are evaluated with the Analytic Hierarchy Process (AHP) method to determine the best framework model design quality used as a reference for the development of Wisanggeni. This study also uses a combination of PHPDepend and PHPMetrics devices to measure the values of object-oriented metrics in each PHP framework. The research final result is that each framework has one value representing each framework's quality in which the quality of Wisanggeni framework is almost to the same with the Laravel and CodeIgniter framework.

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Performance comparison of CATA's information retrieval system application vs WTS

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Journal of Physics: Conference Series 2019年第1期1367卷

作者： Jajang Jaya Purnama Sri Rahayu Sfenrianto Fitra Septia Nugraha Ridan Nurfalah Hendri Mahmud Nawawi Muhammad Ja'far Shidiq Nurul Ichsan Haerul Fatah Master of Computer Science-Postgraduate Program STMIK Nusa Mandiri Jakarta Indonesia Information Systems Management Department BINUS Graduate Program – Master of Information Systems Management Bina Nusantara University Indonesia Information Systems Bina Sarana Informatika University Indonesia

Searching for data or documents that are always a necessity in the world of education, work, research an others requires convenience so that time efficiency occurs. This is supported by the emergence of various Information Retrieval system applications, one of which is cata, which is built on the Java programming language and applies the Generalized Vector Space Model method which can search based on similar keywords. Other facilities need to be developed, one of which is by applying the stemmer porter algorithm applied to the WTS (Web Tokenization Stemming) web which is built with the laravel framework that can search data or documents simply by typing the basic words so that searches are easier and faster.

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