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Journal of Computer System and Informatics (JoSYC)
Published by Forum Kerjasama Pendidikan TInggi
ISSN : 27147150     EISSN : 27148912     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering
Journal of Computer System and Informatics (JoSYC) covers the whole spectrum of Artificial Inteligent, Computer System, Informatics Technique which includes, but is not limited to: Soft Computing, Distributed Intelligent Systems, Database Management and Information Retrieval, Evolutionary computation and DNA/cellular/molecular computing, Fault detection, Green and Renewable Energy Systems, Human Interface, Human-Computer Interaction, Human Information Processing Hybrid and Distributed Algorithms, High Performance Computing, Information storage, Security, integrity, privacy and trust, Image and Speech Signal Processing, Knowledge Based Systems, Knowledge Networks, Multimedia and Applications, Networked Control Systems, Natural Language Processing Pattern Classification, Speech recognition and synthesis, Robotic Intelligence, Robustness Analysis, Social Intelligence, Ubiquitous, Grid and high performance computing, Virtual Reality in Engineering Applications Web and mobile Intelligence, Big Data
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 32 Documents
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Search results for , issue "Vol 4 No 4 (2023): August 2023" : 32 Documents clear
Penerapan Metode CART Dalam Klasifikasi Jurusan Siswa Baru Destia Arini Hairunnisa; Cucu Suhery; Rahmi Hidayati
Journal of Computer System and Informatics (JoSYC) Vol 4 No 4 (2023): August 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i4.3860

Abstract

SMK Negeri 3 Pontianak is one of the vocational education schools in Pontianak City. Every new academic year SMK Negeri 3 Pontianak accepts around 320 new students. The large number of prospective new students makes the majoring process carried out by the school become less effective and takes a long time to determine majors for new students. With a system that can classify new student majors, it helps in the process of determining student majors. This study uses the Classification and Regression Trees (CART) algorithm for the classification process in determining majors for new students. The assessment indicators used for classification consist of interest, MTK (US) school exam scores, school exam IPA scores, school exam Indonesian language scores, math report cards, science report cards, social science report cards, Indonesian language report cards, and English report cards. Classification of majors at SMK 3 Pontianak consists of accounting, office, marketing, and hospitality majors. The amount of data used is 320 data which is divided into 224 training data and 96 test data. The CART algorithm generates decision trees, rules, and new student majors that have been classified. Based on the test results using the confusion matrix, the system accuracy results are 84.38%.
Sistem Pendukung Keputusan Kelulusan Peserta Pelatihan Menggunakan Metode Naïve Bayes Jajang Nurjaman; Andrianingsih Andrianingsih
Journal of Computer System and Informatics (JoSYC) Vol 4 No 4 (2023): August 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i4.4074

Abstract

A decision support system (DSS) is a system that helps decision making in a particular process or situation. In the context of trainee permits, SPK can be used to help predict graduation or not based on several relevant factors, the main objective of this research is to change the system calculation method from manual to automatic. The Center for Tourism and Creative Economy Human Resource Development (PPSDM Parekraf) uses this system to help automate graduation calculations from manual to automatic by inputting several values ​​(Pre & Post Test, Behavior, Assignments and Quizzes, Reports and Comprehensive Test) with all the value provisions reached the test threshold (70). The Naive Bayes method is one of the general classification methods used by SPK and is based on the Bayes theorem with the assumption that each feature or factor used in classification is independent of one another. This system is designed to facilitate an effective and efficient decision-making process in transmitting training participants whether they can continue to the next level of training. This research was carried out in the period from March to June 2023 at PPSDM Parekraf. The data studied uses and analyzes by taking samples of ongoing training data. Hopefully, this SPK will help with more accurate and efficient decisions in determining the graduation of Basic Tourism training participants, the current conditions regarding value processing are still carried out manually. This system is recommended to be used as a medium or tool to support the results of participants' agreements which initially used manual calculations to become automatic. To test the data, it is done by collecting the data and values ​​of the training participants, then preprocessing the data using the Naïve Bayes method into a decision support system.

Page 4 of 4 | Total Record : 32

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