Prediction of Student Graduation using the K-Nearest Neighbors Method
Predictions on the accuracy of student graduation are designed to support study programs in
guiding students so that they can graduate on time. The number of student graduations will …
guiding students so that they can graduate on time. The number of student graduations will …
Data Mining Classification Untuk Prediksi Jumlah Mahasiswa Aktif dan Cuti Angkatan 2020 Menggunakan Metode K-Nearest Neighbor
SA Fitria, HOL Wijaya, D Irawan - KLIK: Kajian Ilmiah Informatika dan …, 2024 - djournals.com
Active students are students who attend lectures, while students on leave are students who
do not attend lectures. To remain active, students must re-register at the start of the …
do not attend lectures. To remain active, students must re-register at the start of the …
MODEL ALGORITMA KNN UNTUK PREDIKSI KELULUSAN MAHASISWA STIKOM CKI
TR Alifia, T Tundo, M Syazidan… - Jurnal Ilmiah …, 2024 - ejournal.gunadarma.ac.id
Penelitian ini mengembangkan model prediksi kelulusan mahasiswa menggunakan
algoritma K-Nearest Neighbor (KNN) dengan mempertimbangkan variabel usia, Indeks …
algoritma K-Nearest Neighbor (KNN) dengan mempertimbangkan variabel usia, Indeks …
Implementasi Algoritma k-Nearest Neighbor (k-NN) dalam Klasifikasi Status Gizi Balita
SS Choeriyah, RS Fanhas, A Fathah… - Cipasung Techno …, 2022 - journal.sttcipasung.ac.id
Toddlers are children under the age of 5 years or 0-60 months. This age is included in a
group that is at high risk of disease. Nutritional status in toddlers is an important factor that …
group that is at high risk of disease. Nutritional status in toddlers is an important factor that …