Image of PENERAPAN TEKNIK DATA MINING DALAM PREDIKSI TINGKAT INDEKS PRESTASI KUMULATIF MAHASISWA MENGGUNAKAN METODE KLASIFIKASI (STUDI KASUS : UNIVERSITAS SRIWIJAYA)

Skripsi

PENERAPAN TEKNIK DATA MINING DALAM PREDIKSI TINGKAT INDEKS PRESTASI KUMULATIF MAHASISWA MENGGUNAKAN METODE KLASIFIKASI (STUDI KASUS : UNIVERSITAS SRIWIJAYA)

Penilaian

0,0

dari 5
Penilaian anda saat ini :  

The grade point average or, abbreviated as GPA is the average value of student learning outcomes during the lecture period. GPA is used as an indicator of student success and is used as one of the requirements proposed by a company when recruiting workers. This study aims to predict the level of student GPA based on the competencies mastered by alumni when they graduate which has a relationship with the GPA level and to design a web-based system that can predict student’s GPA levels using the classification method. The method used is CRISP-DM. The data used is tracer study 2019 as many as 3,906 records. With a significant level of 1% (0.01) it was found that the GPA level had a positive correlation with the variables of the study program, gender, knowledge in the field or discipline, knowledge outside the field or discipline, general knowledge, internet skills, critical thinking, learning skills, communication skills, working under pressure, time management, team work. In this study using 10-fold cross validation with accuracy results in the decision tree algorithm of 68.78%, the K-NN algorithm of 69.30%, the Naive Bayes Classifier algorithm of 71.17% and the Random Forest algorithm of 68.75%. . After that, a T-Test was carried out so that the Naive Bayes Classifer algorithm was obtained as the most dominant algorithm among the other three algorithms so that it could classify and predict the GPA level well.

Availability
Inventory Code Barcode Call Number Location Status
2107002133T54436T544362021Central Library (Referens)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T544362021
Publisher
Inderalaya : Fakultas Ilmu komputer, Prodi Sitem Informasi.,
Collation
xviii, 87 hlm,: ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
004.07
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Pemerosesan Data-Sistem Informasi
Prodi Sitem Informasi
Specific Detail Info
-
Statement of Responsibility
Other version/related

No other version available

File Attachment
Comments
You must be logged in to post a comment