Hasil Prediksi Masa Studinya Adalah

TERLAMBAT

Hasil prediksi ini diperoleh dari perhitungan menggunakan algoritma k-NN dan bukan merupakan hasil yang bersifat Mutlak

Dengan Jenis Kelamin =L, Nikah =B, Cuti =T

Jumlah MK =4, Jumlah SKS = 3

IPS S1 = 8, IPS S2 = 7, IPS S3 = 8, IPS S4 = 6,

Evaluation Test Data
Nilai k Jenis Kelamin Nikah Cuti Jumlah MK Jumlah SKS 1-4 IPS S1 IPS S2 IPS S3 IPS S4 Kelas Asli Kelas Prediksi
20 L B Y 37 83 2.25 2.82 1.8 2.25 Terlambat Terlambat
20 L B T 26 60 1.58 2.05 0.1 0 Terlambat Terlambat
20 L B T 35 83 1.97 2.82 2.77 2.76 Terlambat Terlambat
20 L B Y 43 82 2.26 1.81 1.37 0.68 Terlambat Terlambat
20 P B T 35 83 3.03 2.71 2.7 2.61 Terlambat Terlambat
20 P B T 17 39 2.53 0 0 0 Terlambat Terlambat
20 L B T 60 85 2.67 2.98 3.26 3.03 Tepat Terlambat
20 L B T 60 87 3.03 3.18 3.43 3.54 Tepat Terlambat
20 L B T 63 83 3 2.67 2.74 2.58 Tepat Terlambat
20 L B T 63 86 2.55 3.11 2.84 2.94 Tepat Terlambat
20 L B T 67 81 2.62 2.45 2.53 2.25 Tepat Terlambat
20 L S Y 3 120 3.4 3.4 3.5 3.3 Tepat Terlambat
20 L B T 20 4 20 20 20 20 Tepat Terlambat
20 L S T 12 1 3 3 3 3 Terlambat Terlambat
20 L B Y 1 1 1 1 1 1 Terlambat Terlambat
20 L B T 5 5 5 5 5 5 Terlambat Terlambat
20 L B Y 3 3 3 3 3 3 Terlambat Terlambat
20 L S Y 4 4 4 4 4 4 Terlambat Terlambat
20 P B T 5 21 3.51 3.23 3.67 3.65 Terlambat Terlambat
20 L B T 10 2 11 10 10 10 Terlambat Terlambat
20 L B T 251 251 251 251 251 251 Tepat Tepat
20 P B T 13 14 12 12 12 12 Terlambat Terlambat
20 L B T 34 121 3.04 3.4 2.9 1.4 Terlambat Terlambat
20 L B T 4 3 8 7 8 6 Terlambat Terlambat
Evaluation Table
# Variable Nilai
1 Accuracy
70.83 %
2 Precission
12.5 %
3 Recall
100 %
4 F Rate
29.17 %
5 F1 Score
22.22 %
6 Specificity
69.57 %
7 AUC/(Area Under Curver)
84.79
Confusion Matrix Table
Jumlah = 24 Kelas Tepat Kelas Terlambat
Kelas Tepat 1 7
Kelas Terlambat 0 16
N = 1 N = 23
Normalisasi Test Data
Jenis Kelamin Nikah Cuti Jumlah MK Jumlah SKS IPS S1 IPS S2 IPS S3 IPS S4
0 1 0 0.144 0.328 0.005 0.011235059760956 0.0071713147410359 0.0089641434262948
0 1 1 0.1 0.236 0.00232 0.0081673306772908 0.00039840637450199 0
0 1 1 0.136 0.328 0.00388 0.011235059760956 0.011035856573705 0.010996015936255
0 1 0 0.168 0.324 0.00504 0.0072111553784861 0.0054581673306773 0.0027091633466135
1 1 1 0.136 0.328 0.00812 0.010796812749004 0.010756972111554 0.010398406374502
1 1 1 0.064 0.152 0.00612 0 0 0
0 1 1 0.236 0.336 0.00668 0.011872509960159 0.012988047808765 0.01207171314741
0 1 1 0.236 0.344 0.00812 0.012669322709163 0.013665338645418 0.014103585657371
0 1 1 0.248 0.328 0.008 0.010637450199203 0.010916334661355 0.010278884462151
0 1 1 0.248 0.34 0.0062 0.012390438247012 0.011314741035857 0.011713147410359
0 1 1 0.264 0.32 0.00648 0.0097609561752988 0.0100796812749 0.0089641434262948
0 0 0 0.008 0.476 0.0096 0.013545816733068 0.01394422310757 0.013147410358566
0 1 1 0.076 0.012 0.076 0.079681274900398 0.079681274900398 0.079681274900398
0 0 1 0.044 0 0.008 0.01195219123506 0.01195219123506 0.01195219123506
0 1 0 0 0 0 0.0039840637450199 0.0039840637450199 0.0039840637450199
0 1 1 0.016 0.016 0.016 0.0199203187251 0.0199203187251 0.0199203187251
0 1 0 0.008 0.008 0.008 0.01195219123506 0.01195219123506 0.01195219123506
0 0 0 0.012 0.012 0.012 0.01593625498008 0.01593625498008 0.01593625498008
1 1 1 0.016 0.08 0.01004 0.012868525896414 0.014621513944223 0.014541832669323
0 1 1 0.036 0.004 0.04 0.039840637450199 0.039840637450199 0.039840637450199
0 1 1 1 1 1 1 1 1
1 1 1 0.048 0.052 0.044 0.047808764940239 0.047808764940239 0.047808764940239
0 1 1 0.132 0.48 0.00816 0.013545816733068 0.011553784860558 0.0055776892430279
0 1 1 0.012 0.008 0.028 0.027888446215139 0.031872509960159 0.02390438247012