ANALISIS KLASTER MAHASISWA INSTITUT TEKNOLOGI KALIMANTAN MENGGUNAKAN ALGORITMA K-PROTOTYPES UNTUK PERUMUSAN STRATEGI PROMOSI

Hafidzha, Zhahira Syahwa (2026) ANALISIS KLASTER MAHASISWA INSTITUT TEKNOLOGI KALIMANTAN MENGGUNAKAN ALGORITMA K-PROTOTYPES UNTUK PERUMUSAN STRATEGI PROMOSI. Bachelor thesis, Institut Teknologi Kalimantan.

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Abstract

The decline in the number of prospective students from the initial registration stage to actual enrollment at the Kalimantan Institute of Technology (ITK) indicates that current promotion and admission strategies have not fully succeeded in attracting candidates who align with the institution's needs. Therefore, this study aims to segment students based on social, economic, geographic, and academic characteristics using the K-Prototypes algorithm, thereby supporting the formulation of more targeted student recruitment strategies. The study utilizes secondary data from 4,850 active ITK students (enrolled between 2023 and 2025), comprising 12 mixed variables (3 numerical and 9 categorical). The research process involves data preprocessing, Exploratory Data Analysis (EDA), encoding, scaling, clustering via the K-Prototypes algorithm, and determining the optimal number of clusters using the Silhouette Index. Results indicate that the optimal clustering for the overall ITK student dataset consists of two clusters, with a Silhouette Index of 0.515. Meanwhile, optimal clustering results for individual study programs at ITK yielded Silhouette Index values ranging from 0.306 to 0.612, with an optimal cluster count of 2 to 3. Key variables distinguishing the clusters— both for the aggregate student body and within individual study programs—include parents'/guardians' occupation and income, admission pathway, region of origin, school of origin, school status, and scholarship status. Based on these findings, a recommended promotional strategy involves optimizing the dissemination of scholarship information, specifically targeting public high school students located within Balikpapan City and outside East Kalimantan Province. Thus, the KPrototypes algorithm effectively generates representative student segments to support the development of student recruitment strategies at ITK.

Item Type: Thesis (Bachelor)
Subjects: L Education > LB Theory and practice of education > LB2300 Higher Education
L Education > LC Special aspects of education > LC5201 Education extension. Adult education. Continuing education
Q Science > Q Science (General)
Divisions: Jurusan Matematika dan Teknologi Informasi > Statistik
Depositing User: Zhahira Syahwa Hafidzha
Date Deposited: 06 Jul 2026 07:20
Last Modified: 06 Jul 2026 07:20
URI: http://repository.itk.ac.id/id/eprint/25848

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