TY - JOUR AU - Rahmat Izwan Heroza, AU - Haniifah Putriani, AU - Ahmad Rifai, AU - Putri Eka Sevtiyuni, PY - 2021/01/31 Y2 - 2024/03/28 TI - Expertise Locator For Lecturers Based on Publication JF - Data Science: Journal of Computing and Applied Informatics JA - Data Science: J. of Computing and Appl. Informatics VL - 5 IS - 1 SE - DO - 10.32734/jocai.v5.i1-5112 UR - https://talenta.usu.ac.id/JoCAI/article/view/5112 SP - 11-17 AB - <p lang="en-US" align="justify"><span style="font-family: Times New Roman, serif;"><span style="font-size: small;">Among the KM processes that function to guarantee access to knowledge is knowledge sharing. This process allows knowledge assets and experiences possessed by the organization to be accessed by anyone in the organization. Especially by using IT, this process can be done more optimally by capturing existing knowledge into a system so that this valuable information can be monitored anytime and anywhere. There are times when the knowledge possessed by experts is difficult to capture and represent in the system as in the case of tacit knowledgesuch as instincts, insights, and experiences of the experts. One of the challenges in inventorying these experts is the process of creating expert profiles automatically based on a particular approach. This research create an Expert Locator for lecturers who are considered as experts in their field of research using publication data produced by these lecturers as an indication of their expertise. The search feature is made as an implementation of the extraction results that can be used by other parties to find experts by entering keywords in the form of the desired expertise.</span></span></p> ER -