Thesis
Published
COMPARISON OF SUPPORT VECTOR MACHINE AND RANDOM FOREST METHODS IN ANALYZING THE EFFECT OF MUSIC ON REDUCING STRESS LEVELS AMONG 7TH-SEMESTER FEMALE STUDENTS DURING THESIS WRITING (Case Studi: Darussalam Gontor University)
Abstract
Universitas Darussalam Gontor is a boarding-based university designed to
support learning efficiency. During their academic journey, students completing
their theses often experience stress due to academic demands, making it a primary
cause of stress. One effective way to reduce stress is by listening to music, which
can enhance focus and productivity. This study aims to classify and analyze the
influence of music on stress reduction among seventh-semester female students and
compare the performance of the SVM and Random Forest algorithms in data
analysis. The results show that out of a total of 340 collected data points, 22.4% of
students found music to be highly effective in reducing stress, while 70.3% felt it
was moderately effective. However, 7.4% reported no significant impact of music
on stress reduction. The most effective and frequently listened-to music genre during
thesis writing was pop music, particularly subgenres such as K-pop, J-pop, and Ipop, with more than 180 students out of the total 340 respondents preferring these
genres. Regarding the effectiveness of the algorithms, SVM outperformed Random
Forest with an accuracy of 97% compared to 79%. These findings indicate that
music plays a role in managing and reducing stress levels among students during
thesis writing and demonstrate that SVM is an effective algorithm for processing
similar types of data.
Keywords: Students, Stress, Music, SVM, Random Forest
Publication Details
InstitutionUniversitas Darussalam Gontor
DepartmentTeknik Informatika
SubjectsQ Science > Q Science (General)
Q Science > QP Physiology
T Technology > TA Engineering (General). Civil engineering (General)
Q Science > QP Physiology
T Technology > TA Engineering (General). Civil engineering (General)
KeywordsKeywords: Students, Stress, Music, SVM, Random Forest
Item ID5403
Deposited13 Feb 2025 14:31