K-Means Clustering of Science and Technology Programs at Universitas Gadjah Mada Based on SNMPTN 2021 Applicants and SNMPTN 2022 Capacity
National Selection for State Universities (SNMPTN) is a nationwide admission selection process for state universities in Indonesia. One common strategy for participating in SNMPTN is to assess the likelihood of being admitted to a specific program by understanding the capacity and demand for each program. By analyzing data on capacity, number of applicants, and the number of students admitted for each program, we can categorize programs into those with higher or lower chances of admission.
The aim of this study is to categorize science and technology programs at Universitas Gadjah Mada based on the SNMPTN 2021 applicant data and the SNMPTN 2022 capacity for these programs. The resulting categories from this analysis can provide information for prospective students, helping them choose programs with better admission chances.
The data used in this research was obtained from the official website of the National Entrance Test Agency (LTMPT) through web scraping. The data was analyzed using K-means Clustering, a clustering analysis method, to create categories based on the 2022 capacity and 2021 applicant numbers. The analysis resulted in three clusters: Cluster 0, Cluster 1, and Cluster 2.
- Cluster 1: Programs with low demand and low capacity.
- Cluster 0: Programs with moderate demand and capacity.
- Cluster 2: Programs with high demand and high capacity.
This categorization helps prospective students better understand the admission landscape for science and technology programs at Universitas Gadjah Mada.