SISTEM CERDAS PREDIKSI JUMLAH KELAS PROGRAM STUDI TEKNIK INFORMATIKA MENGGUNAKAN ALGORITMA REGRESI LINEAR BERGANDA

Pratama, Satrio Bagas and Aziz, RZ Abdul (2024) SISTEM CERDAS PREDIKSI JUMLAH KELAS PROGRAM STUDI TEKNIK INFORMATIKA MENGGUNAKAN ALGORITMA REGRESI LINEAR BERGANDA. Skripsi thesis, Institut Informatika dan Bisnis Darmajaya.

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Abstract

In practice, the number of classes for each subject is different and classes often open or close when preparing the KRS as a result of the number of classes not matching the number of students. In practice, the number of classes opened during the Study Plan Card (KRS) preparation process did not match the number of students who would take the course. Errors in predicting the number of classes in certain courses were caused by the secretariat of the Informatics Engineering Department only referring to the number of classes in the previous semester and statistical data on the score of not passing a course in the previous academic year. For example, to predict the number of classes for computer network courses in semester 5, the department will refer to the number of classes in the previous semester, namely semester 4 and taking into account the percentage of statistical data on student scores that did not pass the computer network scores in the previous academic year. Some of these possibilities can be determine the number of enthusiasts for each course so that it can predict the number of classes more efficiently and minimize problems when classifying a course that will occur when the KRS preparation takes place. By using this algorithm, an intelligent system can determine classes as a linear combination of attributes with predetermined weights and produce more accurate and efficient predictions of the number of classes needed each semester.

Item Type: Thesis (Skripsi)
Subjects: Ilmu Komputer
eSkripsi
Divisions: Skripsi/TA & PKPM/KP - Fakultas Ilmu Komputer > Teknik Informatika
Depositing User: Satrio Bag Satrio Satrio
Date Deposited: 28 Aug 2024 01:41
Last Modified: 28 Aug 2024 01:41
URI: http://repo.darmajaya.ac.id/id/eprint/17098

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