Abstract: One of the methods in knowledge management that can be used is the SECI Model. The SECI Model transfers tacit and explicit knowledge in each quadrant. However, without using tools, the transfer of technical knowledge will experience various obstacles. These obstacles included limited knowledge of the informants, difficulty in translating what was conveyed by the informants, limited time and opportunities, and unclear results obtained. The transfer of knowledge needed by college institutions is in the form of input from graduates who have graduated from college institutions. Graduates' knowledge must be obtained to determine whether their competence is following their respective fields of knowledge. Information technology can help overcome technical problems in transferring knowledge, including the problem of large amounts of data. Data science will deliver results from a combination of technology and mathematics. Meanwhile, data mining, especially with classification, grouping, and association functions, can provide a clear picture of the needs of higher education institutions for the knowledge of their graduates to assess the curriculum that has been provided so far. The design formulation of the SECI model and the implementation of this data mining use an empirical approach through observation and experimentation with quantitative data, as well as theoretical thinking in supporting the development of the model development concept. Data mining and data science will clarify processes in the SECI Model quadrant regarding technological tools in the context of knowledge transfer in a circular manner between tacit and explicit, in order to be more directed and precise. Information extracted from graduate competencies can assist college institutions in formulating future strategies in the academic field, especially the curriculum in study program. This result will impact students in the future, where the developed curriculum will focus more on the results of the input of graduate students.

Mardiani , Ermatita, Samsuryadi and Abdiansah, “SECI Model Design with a Combination of Data Mining and Data Science in Transfer of Knowledge of College Graduates’ Competencies” International Journal of Advanced Computer Science and Applications(IJACSA), 14(7), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140736

@article{2023,
title = {SECI Model Design with a Combination of Data Mining and Data Science in Transfer of Knowledge of College Graduates’ Competencies},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140736},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140736},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {7},
author = {Mardiani and Ermatita and Samsuryadi and Abdiansah}
}