IMPLEMENTASI ALGORITMA APRIORI DALAM DATA MINING UNTUK MEMBANTU MENENTUKAN STRATEGI PROMOSI UNIVERSITAS (STUDI KASUS: UIN SUNAN KALIJAGA YOGYAKARTA)

Zulaicha Hana Purbaningrum, NIM.: 19106050031 (2023) IMPLEMENTASI ALGORITMA APRIORI DALAM DATA MINING UNTUK MEMBANTU MENENTUKAN STRATEGI PROMOSI UNIVERSITAS (STUDI KASUS: UIN SUNAN KALIJAGA YOGYAKARTA). Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

Understanding the urgency of education makes people begin to have awareness to complete compulsory education and continue it to tertiary institutions. Compared to the previous year, the number of students in 2021 has increased by 4.1%. This increase is directly proportional to the increase in enthusiasts at UIN Sunan Kalijaga Yogyakarta from year to year. In order to continue to increase the number of enthusiasts, this can be done by knowing the distribution of origins and schools of origin of new students in the previous year. The objects of the case study in this research are new undergraduate students in 2022 who are accepted at UIN Sunan Kalijaga Yogyakarta. By utilizing the data in the form of majors, district of origin, province of origin, and high school origin, it will be known the region of origin and type of school for most of the new students. Based on this knowledge, information is then obtained as material for consideration of the location and type of high school which will be the main target in socialization activities to promote UIN Sunan Kalijaga Yogyakarta and its study programs. New student data processing is carried out using a data mining method, namely the Apriori algorithm implemented in the Python programming language. After processing the data, association rules were obtained which showed that some of the existing departments were associated with the provinces of D.I Yogyakarta, Central Java and East Java with the types of high schools being MAS and SMA.

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