Penerapan Algoritma K-Nearest Neighbor Untuk Penentuan Peminatan Studi (Studi Kasus : Program Studi Teknik Informatika STMIK Amik Riau)

Authors

  • Nora Lizarti STMIK Amik Riau
  • Aniq Noviciatie Ulfah STMIK Amik Riau

DOI:

https://doi.org/10.21111/fij.v4i1.2822

Keywords:

Study Interest, Classification, K-Nearest Neighbor (K-NN) Algorithm

Abstract

AbstrakPeminatan studi pada STMIK Amik Riau merupakan pilihan minat berdasarkan kemampuan khusus dan ketertarikan mahasiswa. Program studi Teknik Informatika STMIK Amik Riau memiliki dua bidang peminatan, yaitu bisnis dan jaringan. Peminatan disesuaikan dengan kemampuan dan ketertarikan dari mahasiswa serta harus dipilih dengan baik dan tepat. Pengambilan peminatan sangat berpengaruh terhadap tugas akhir dan tingkat kelulusan mahasiswa. Pemilihan peminatan studi oleh mahasiswa saat ini hanya mengikuti teman dan tidak berdasarkan kemampuan, sehingga sebuah Sistem klasifikasi peminatan merupakan salah satu solusi untuk menyelesaikan permasalahan pemilihan peminatan pada program studi karena dianggap mampu memberikan rekomendasi pemintan yang baik dan tepat. Algoritma K-Nearest Neighbor (K-NN) merupakan algoritma klasifikasi yang dapat digunakan sebagai solusi dalam pengelompokan data.  Pada penelitian ini data yang digunakan diperoleh dari nilai mata kuliah prasyarat selama semester satu hingga semester lima. Data diolah dengan membangun aplikasi yang menerapkan algoritma K-NN menggunakan PHP dan MySQL. Hasil keluaran sistem memiliki akurasi 100% dibandingkan hasil perhitungan manual menggunakan Ms. Excel. Pengujian menggunakan tools RapidMiner untuk mengukur performa algoritma. Hasil pengujian yang dilakukan terhadap 183 data latih dan 100 data uji menyatakan algoritma K-NN memiliki performa dengan hasil Acuracy, Recall, Precision, F Measure, dan Clasificassion Error dengan nilai 98%, 100%, 100%, 91.67%, dan 2%. Penelitian ini dapat memberikan rekomendasi peminatan studi kepada mahasiswa Teknik Informatika STMIK Amik Riau.Kata kunci: Peminatan studi, klasifikasi, algoritma K-NN Abstract[Implementation of K-Nearest Neighbor Algorithm For Determining Concentration of Study at Informatics Engineering Program of STMIK AMIK RIAU] Concentration of study at STMIK Amik Riau is a choice of interests based on special abilities and student interests. Informatics Engineering Program at STMIK Amik Riau has two subjects of interest, namely business and networking. The study concentration is tailored to the abilities and interests of students and must be chosen properly and correctly because it is very influential on the final assignment and graduation level of students. The classification system of interest is one of the solutions to solve the problem of choosing a concentration in the study program because it is considered capable of providing good and appropriate spinning recommendations. K-Nearest Neighbor (K-NN) is one of classification algorithm that can be used as a solution in classifying data. In this study, the data used was obtained from the value of prerequisite courses during semester one to semester five. Data is processed by building applications that implement the K-NN algorithm using PHP and MySQL. The output of the system has 100% accuracy compared to the results of manual calculations using Microsoft Excel. The Testing process used RapidMiner software to measure algorithm performance. The results of the tests carried out on 183 training data and 100 test data stated that the K-NN algorithm had a performance with the results of Accuracy, Recall, Precision, Measure, and Classification Error with values of 98%, 100%, 100%, 91.67%, and 2 %. This study can provide a system that can help to give some study concentration recommendations to the student of Informatics Engineering Program at STMIK Amik Riau.Keywords: Study Interest, Classification, K-Nearest Neighbor (K-NN) Algorithm

References

T. H. Simanjuntak and W. F. Mahmudy, “Implementasi Modified K-Nearest Neighbor Dengan Otomatisasi Nilai K Pada Pengklasifikasian Penyakit Tanaman Kedelai,” no. June, 2017.

E. Prasetyo, Data Mining Konsep dan Aplikasi menggunakan MATLAB. Yogyakarta: Andi Offset, 2012.

J. Han, M. Kamber, and J. Pei, Data Mining Concepts and Techniques. Waltham: Morgan Kaufmann, 2012.

E. Turban, J. E. Aronson, and T. Liang, Decision Support Systems and Intelligent Systems. New Delhi: Prentice-Hall of India Private Limited, 2007.

S. Arikunto, Prosedur Penelitian: Suatu Pendekatan Praktis. Jakarta: Rineka Cipta, 2010.

R. S. Pressman, Software Engineering : A Practitioner’s Approach, 7th ed. New York, USA: Mc Graw Hill Higher Education, 2010.

Y. Kustiyahningsih and D. R. Anamisa, Pemrograman Basis Data Berbasis Web Menggunakan PHP & MySQL. Yogyakarta: Graha Ilmu, 2011.

Anhar, Panduan Menguasai PHP & MySQL secara Otodidak. Jakarta: Mediakita, 2010.

P. Mittal and N. S. Gill, “A Comparative Analysis Of Classification Techniques On Medical Data Sets,” pp. 454–460, 2014.

D. Kurniawan, “Evaluasi Sistem Temu Kembali Informasi Model Ruang Vektor,” vol. 16, no. 3, pp. 155–162, 2010.

I. M. K. Wicaksana and I. M. Widiartha, “Penerapan Metode Ant Colony Optimzation Pada Metode K-Harmonic Means Untuk Klasterisasi Data,” J. Ilmu Komput., vol. 5 No 1, 2012.

Downloads

Submitted

2019-01-17

Accepted

2019-02-24

Published

2019-05-01

Issue

Vol. 4 No. 1 (2019): Mei

Section

Articles

License

Please find the rights and licenses in the Fountain of Informatics Journal (FIJ). By submitting the article/manuscript of the article, the author(s) agree with this policy. No specific document sign-off is required.

1. License

The non-commercial use of the article will be governed by the Creative Commons Attribution license as currently displayed on Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. 

2. Author(s)' Warranties

The author warrants that the article is original, written by the stated author(s), has not been published before, contains no unlawful statements, does not infringe the rights of others, is subject to copyright that is vested exclusively in the author, and free of any third party rights, and that any necessary written permissions to quote from other sources have been obtained by the author(s).

3. User/Public Rights

FIJ's spirit is to disseminate articles published are as free as possible. Under the Creative Commons license, FIJ permits users to copy, distribute, display, and perform the work for non-commercial purposes only. Users will also need to attribute authors and FIJ on distributing works in the journal and other media of publications. Unless otherwise stated, the authors are public entities as soon as their articles got published. 

4. Rights of Authors

Authors retain all their rights to the published works, such as (but not limited to) the following rights;

  • Copyright and other proprietary rights relating to the article, such as patent rights,
  • The right to use the substance of the article in own future works, including lectures and books,
  • The right to reproduce the article for own purposes,
  • The right to self-archive the article (please read out deposit policy),
  • The right to enter into separate, additional contractual arrangements for the non-exclusive distribution of the article's published version (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal (Jurnal Optimasi Sistem Industri).

5. Co-Authorship

If the article was jointly prepared by more than one author, any authors submitting the manuscript warrants that he/she has been authorized by all co-authors to be agreed on this copyright and license notice (agreement) on their behalf, and agrees to inform his/her co-authors of the terms of this policy. FIJ will not be held liable for anything that may arise due to the author(s) internal dispute. FIJ will only communicate with the corresponding author.

6. Royalties

Being an open accessed journal and disseminating articles for free under the Creative Commons license term mentioned, author(s) aware that FIJ entitles the author(s) to no royalties or other fees. 

7. Miscellaneous

FIJ will publish the article (or have it published) in the journal if the article’s editorial process is successfully completed. FIJ's editors may modify the article to a style of punctuation, spelling, capitalization, referencing, and usage that deems appropriate. The author acknowledges that the article may be published so that it will be publicly accessible and such access will be free of charge for the readers as mentioned in point 3.