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Öğe Construction Crew Productivity Prediction By Using Data Mining Methods(Elsevier Science Bv, 2014) Kaya, Mumine; Keles, Abdullah Emre; Oral, Emel LaptaliCeramic tiling industry has become one of Turkey's fastest growing industries due to the outstanding achievements of Turkish ceramic producers with respect to producing high quality products with lower costs than their equivalents worldwide. Conversely high costs of the end product of Turkish building industry in general show that there is an important problem with the productivity and quality of construction crews. That's why most construction firms begin to realize the need for a detailed research on the factors affecting construction crew productivity. The purpose of this study is thus to classify the factors that affect the productivity of ceramic tiling crews by using data mining methods. To achieve the purpose of our study, a systematic time study was undertaken with ceramic tiling crews in Turkey. Daily productivity values of ceramic tiling crews were collected together with the information related with the factors like the crew size, age and experience of crewmembers. Collected data was classified by using Weka program. The outlier values were first removed from the dataset and decision tree method was used to classify the new dataset. Decision tree method was preferred due to its easiness of use and rapidness in classification. Apriori algorithm, which is the mostly preferred association algorithm in previous studies, was also used to highlight the general trend in the dataset. (C) 2014 The Authors. Published by Elsevier Ltd.Öğe Integrating an Online Compiler and a Plagiarism Detection Tool into the Moodle Distance Education System for Easy Assessment of Programming Assignments(Wiley, 2015) Kaya, Mumine; Ozel, Selma AyseIn this study, an online compiler and a source code plagiarism detection tool have been included into the Moodle based distance education system of our Computer Engineering department. For this purpose Moodle system has been extended with the GCC compiler, and the Moss source code plagiarism detection tool. We observed that using the online compiler and the plagiarism detection tool reduces time and effort needed for the assessment of the programming assignments; prevents our students from plagiarism; and increases their success in their programming based Data Structures course. (c) 2014 Wiley Periodicals, Inc. Comput Appl Eng Educ 23:363-373, 2015; View this article online at ; DOI