Chronic gastrointestinal disorders impose a heavy economic burden and stress on society and the health care system. Among these chronic disorders is irritable bowel syndrome. This disease can be diagnosed by careful evaluation of clinical signs, medical records and simple tests that only require a lot of time and high knowledge. On the other hand, data mining is one of the multidisciplinary fields derived from scientific fields such as statistics, mathematics, computers and artificial intelligence, whose applications are expanding in various fields such as health and treatment. Applying data mining on medical data brings vital, valuable and effective achievements and can enhance the physician’s knowledge to take the necessary measures and also speed up the diagnosis process. Therefore, in this study, the best data mining algorithm for the diagnosis of irritable bowel syndrome was determined using WEKA software. For this purpose, the data mining process using Decision Stump, Random Tree and j48 algorithms on 59 samples collected from the files of people referring to Erfan Hospital in Tehran (to collect information about patients) and questionnaires distributed among employees of a company. Software was used to collect information from healthy individuals. Finally, the total data included 55.93% male sample and 44.06% female sample. The results were compared in terms of speed, accuracy and computational cost. Finally, j48 algorithm with 96.6% accuracy was introduced as the optimal algorithm for IBS detection.

The growth and development of e-government communities is shown as a sovereign asset in developing societies, as a way for governments to employ new technologies, make people more accessible to government information and services, improve the quality of these services and provide the possibility of people’s participation in democratic processes and activities. The purpose of this study is to evaluate the feasibility and importance of using metadata in the implementation of e-government services. In this research, which was conducted over a period of 6 months, 146 senior, operational and middle managers of Islamic Azad University in Khorasan Razavi province were selected through stratified random sampling. The research tool was a questionnaire whose validity was confirmed by experts and its reliability was confirmed by Cronbach’s alpha coefficient. Based on partial least squares analysis (PLS) which is a model fitting based on validity and reliability analysis, the results showed that macro data volume, macro data speed, and macro data variability are based on three criteria of e-government implementation ie e-government core. , The extended layer of e-services and the outer layer of e-services based on the t-statistic, which is higher than 1.96, has a positive and significant effect.

The most important features of the proposed method include: 1) introducing an innovation in Leach algorithm and applying it in a different field from its common application, 2) using standard centrality indicators to calculate the correlation degree in order to improve the identification of opinion leaders in social networks, 3)this algorithm is completely automatic and works without operator intervention.