Analisis Grafologi Berdasarkan Huruf a dan t Menggunakan Algoritme K-Nearest Neighbor
ABSTRACT
AMANDA KARATIKA HUBEIS. Graphology Analysis Based on Letter a and t Using kNearest Neighbor (kNN) Algorithm. Under the supervision of AZIZ KUSTIYO.
Graphology or handwriting analysis is a method of identifying, analyzing, evaluating, and
understanding personality through the strokes and patterns revealed by handwriting. People who
can analyze handwriting are called graphologist. Graphologist can have a subjective assesment.
Different graphologists can analyze the same handwriting but give different results. In addition,
the accuracy of handwriting analysis depends on the graphologist’s ability. A system that can
recognize handwrititng patterns is required to overcome these problems. The identification system
which is implemented in this research uses k-Nearest Neighbor Algorithm. This research used 135
images of the letter a and 150 images of the letter t. This research is divided into five parts, three
for the letter t and two for the letter a. We use a value of k from 1 to 20 for searching the best.
Identifying personality based on the letter a, and identifying personality based on the letter t then
clasifying them into one of the three character classes available. The results of this research is that
the system has 88.89% accuracy for the letter a and 70% accuracy for the letter t.
Keyword : k-Nearest Neighbor, Graphology, Personality Analysis.
AMANDA KARATIKA HUBEIS. Graphology Analysis Based on Letter a and t Using kNearest Neighbor (kNN) Algorithm. Under the supervision of AZIZ KUSTIYO.
Graphology or handwriting analysis is a method of identifying, analyzing, evaluating, and
understanding personality through the strokes and patterns revealed by handwriting. People who
can analyze handwriting are called graphologist. Graphologist can have a subjective assesment.
Different graphologists can analyze the same handwriting but give different results. In addition,
the accuracy of handwriting analysis depends on the graphologist’s ability. A system that can
recognize handwrititng patterns is required to overcome these problems. The identification system
which is implemented in this research uses k-Nearest Neighbor Algorithm. This research used 135
images of the letter a and 150 images of the letter t. This research is divided into five parts, three
for the letter t and two for the letter a. We use a value of k from 1 to 20 for searching the best.
Identifying personality based on the letter a, and identifying personality based on the letter t then
clasifying them into one of the three character classes available. The results of this research is that
the system has 88.89% accuracy for the letter a and 70% accuracy for the letter t.
Keyword : k-Nearest Neighbor, Graphology, Personality Analysis.