HRIS with Decision Support for Faculty Appraisal and Promotion
Maria Jackie Lou L. Zinampan

Maria Jackie Lou L. Zinampan, Management Information Systems Office, Cagayan State University, Tuguegarao City, Philippines.

Manuscript received on 18 April 2023 | Revised Manuscript received on 24 April 2023 | Manuscript Accepted on 15 May 2023 | Manuscript published on 30 May 2023 | PP: 54-59 | Volume-12 Issue-1, May 2023 | Retrieval Number: 100.1/ijrte.A76020512123 | DOI: 10.35940/ijrte.A7602.0512123

Open Access | Editorial and Publishing Policies | Cite | Zenodo | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: Of all the resources of the organization, manpower is the only live generating resource. It is one that utilizes all other resources and as a matter of fact, without which none of the other resources will be able to produce anything. Being such, manpower should be managed properly in such a way that they would be encouraged to be productive and help in the realization of organization’s goals. This study aimed to come up with an online decision support system that would aide the management of Cagayan State University manage its human resources particularly in terms of appraisal and promotion by providing relevant and timely information. The system is designed to streamline processes in the HR department so as to simplify generation of needed analytics for decision support.Moreover, the study utilized classification data mining technique to classify faculty members to appropriate ranks and sub-ranks based on their CCE and QCE points and identify faculty members whose rank did not improve in the past 6 years. Decision tree was also used to predict the faculty performance based on the three (3) consecutive NBC 461 cycle results. This decision support information is essential for the management to know so that necessary intervention can be made to help the faculty member improve and get promoted. With the use of ISO/IEC 25010:2011 Software Quality Standards, the system was evaluated by IT Experts with a mean 4.70, qualitatively described as “Very Great Extent”.
Keywords: Classification Technique, Data Mining, Human Resource Management, Information System.
Scope of the Article: Classification