JOURNAL ARTICLE

Penerapan Algoritma K-Nearest Neighbor untuk Prediksi Kelulusan Siswa pada SMK Anak Bangsa

Sekar Rizkya RaniSundari Retno AndaniDedi Suhendro

Year: 2019 Journal:   Prosiding Seminar Nasional Riset Information Science (SENARIS) Vol: 1 Pages: 670-670

Abstract

Student graduation is very important for world education achievement, student graduation also influences the value of accreditation of an educational unit itself, therefor research on graduation prediction becomes a very interesting thing study, this study proposes the use of the K-Nearest Neighbor method to do predict student graduation at Anak Bangsa Private Vocational School. The result of the research is the value of k=5 with an accuracy rate of 93.55% which is determined as K-Optimal. The value of k=5 is applied to the K-NN algoritma to predict student graduation based on attendance, attitude, and value of knowledge.

Keywords:
Graduation (instrument) Attendance Accreditation Vocational education Value (mathematics) Mathematics education Mathematics Psychology Medical education Pedagogy Statistics Political science Medicine

Metrics

6
Cited By
0.73
FWCI (Field Weighted Citation Impact)
3
Refs
0.79
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Data Mining and Machine Learning Applications
Physical Sciences →  Computer Science →  Information Systems
Multimedia Learning Systems
Physical Sciences →  Computer Science →  Information Systems
Edcuational Technology Systems
Physical Sciences →  Computer Science →  Artificial Intelligence

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