INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 9, ISSUE 03, MARCH 2020 ISSN 2277-8616 4358 IJSTR©2020 www.ijstr.org Data Mining Techniques In HR Analytics: A Review Of Domain Specific Concepts And Technicalities Banajit Changkakati, Chayanika Das Abstract— The review tries to deal with the usage, scope and nature of the various data mining techniques for better analysis and prediction of HR functionalities in an organization. The paper here describes with atleast 30 papers mostly based on sample outside India. The author here tries to bring out few quality papers, all accumulated from known databases for review and give a vivid picture of the techniques that can be used for analyzing domain specific data. These techniques might also help the future researches to effectively predict various HR functionalities specific to region and industry. Key words — HR analytics, Data mining, Prediction, Human Resource Management. ——————————  —————————— 1 INTRODUCTION Human Resource is one of the core competency and competitive advantage of a particular organisation. Therefore, dealing and maintaining them with utmost care is important because this capital is both qualitative as well quantitative nature. So, only stringent strategies are not sufficient, they are to be dealt with both emotion, tactics, techniques and science. In various papers, it is seen that the management perspective from the researchers end is missing or lagging behind as only technical modeling is done by the researchers on the data provided. The researches are solely on the basis of either demographic factors or domain experts knowledge of the particular organisation or industry. As management academicians few new factors can be incorporated as suggested in the models established. In recent years, a quickly growing number of research contributions aim at supporting the practical adoption of HRM data mining[Strohmeier and Piazza].An increasing number of data mining researches have come out in the last few years. In this paper the researcher tries to compile various articles and papers that has been published along times and thus tries to find out the most accurate method for predicting various HR functions from recruiting and selection, training and development, performance management andretention of the employees in various organisations spread over various arena or industry. The researcher also tries to analyse the most accurate and user friendly techniques which the vendors can use and incorporate the model to be designed to develop commercial products to help the organisations. The paper would thus try to put a systematic angle for suggesting future scope. 2 METHOD AND FRAMEWORK The research articles have been collected from search engines like scholar.google.com and also from online research databases (Business Source Premier, Scopus, and Science Direct). HRM data mining refers to an intersection of method and domain, respective pairs of search terms such as ‗‗data mining‘‘ and ‗‗HRM‘‘ were employed. Beyond synonyms such as ―Knowledge discovery database‖ and ‗‗talent management‘‘, multiple HRM sub-domains such as ―retention‖, ―performance management‖ ‗‗recruiting‘‘, ‗‗compensation‘‘, method-categories such as ‗‗decision trees‘‘, ‗‗cluster analysis‘‘ etc. were used as search terms. The search was however restricted to only English language publications. 2.1 The Systematic Review of Research Papers Chien and Chen (2008) in their paper describes about data mining techniques as discovery driven rather than assumption driven. They have opined that these techniques used in HR related areas are very rare. They proposed decision tree analysis, clustering, association techniques. In details, they proposed various algorithms for decision tree like CART, CHAID, ID3, and C4.5 and compared them. From the study, using the CHAID algorithm in the sample organisation, they were able to design various rules which in turn helped the organisation to design strategies to decrease the turnover of their employees and help the organisation. They also said that with use of more factors in hand and usage of neural network can yield better results. Yee and Chen(2009) used multi factorial evaluation model which is an application of fuzzy theory to design a performance appraisal system in a IT and Telecommunication organisation of Malaysia which in turn can segregate the poor , average and top score of performers. The architecture tends to use various aspects of performance measurement as given by the HR section too calculate an overall performance score which in turn helped in categorising and ranking the employees based on the performance . This model is supposed to be applicable for other organisations as well only by altering the aspects as relevant to the organisation and the weightages assigned to the aspects. The researcher believes that ―This model follows a systematic step in determining a staff‘s performance, and therefore, it creates a system of appraisal which is able to consistently produce reliable and valid results for the appraisal process. In order to ————————————————  Banajit Changkakati is currently working as an Assistant Professor in Gauhati University,India. PH-9864086082.. E-mail: banajit.changkakati@gauhati.ac.in  Chayanika Das is currently working as Assistant Professor in Assam DonBosco University , India.PH-8876749005 E-mail: chayanika.das@dbuniversity.ac.in