Evaluation of articles published in Mendeley and CrossRef in relation to the Google Scholar pages

This paper aims to show the performance of a researcher from their published articles. Our software crawled 10 (ten) most cited articles on the Google Scholar (GS), Mendeley and CrossRef with several of crawling methods. The method used in data retrieval is scrapping due to the limitations on the Application Programming Interface (API) provided by the Google search engine. To retrieve the Digital Object Identifier (DOI) data from Crossref, the API method has been used. In order to count the number of reader of paper on the Mendeley we used the API method. We used the R programming language, Python and Bash scripting shell. The operating system was based on Ubuntu 8.04 Linux and Mac OS. The Apache webserver were used to serve the website and we used the MySQL database to store the data. The database of MySQL is used for interfacing between R with the PHP language purposes. The Hypertext Preprocessor (PHP) is used for server-side scripting. Data was obtained by scrapping the best 10 articles from 100 Indonesia's scientists indexed on the GS. Firstly, the data samples (S') were obtained from the list of Indonesian scientists in Webometrics as the input of the GS scrapping. Secondly, the data resulted (S") were used as the input of the Crossref's A query to obtain the DOI of each article. Finally, the DOIs were used as the input for the API query to get the number of the result to show the number of readers of each to article on Mendeley. The software produced can crawl the data from Google Scholar, Crossref and Mendeley reader count.