PEMILIHAN SEKOLAH TERBAIK DENGAN MENGGUNAKAN METODE K-NEAREST NEIGHBORS DAN TAXONOMIC MATCHER

Bidari Ayu Lestari, Muhammad Hasbi, Teguh Susyanto

Abstract


The accuracy of choosing the right school is what every prospective student and parent wants. But in making the decision to choose the right school is not easy to do, because many aspects that are not simple must be taken into account. Mistakes in making decisions for prospective students must risk the loss of opportunities. Calculations in choosing a prospective student must be able to measure rationally the level of ability themselves with the quality of the school to be chosen. The quality of the school is determined based on the school's favorite level, the value of school accreditation, facilities owned, and achievements that have been achieved by the destination school. The purpose of this study was to apply the K-Nearest Neighbors (KNN) and Taxonomic Matcher methods to the creation of a system for selecting schools. The results of the development of the school selection application have been running in accordance with its functions and the results of the user acceptance test have been approved because it has a higher value than the answer agreed on the Likert scale which is 4.188571 on a scale of 1-5.

Keywords: K-Nearest Neighbors (KNN), Taxonomic Matcher, Choosing a School


Full Text:

PDF

References


Faisal and S. D. H. Permana, “Sistem Penunjang Keputusan Pemilihan Sekolah Menengah Kejuruan Teknik Komputer Dan Jaringan Yang Terfavorit Dengan Menggunakan Multi-Criteria Decision Making,” J. Teknol. Inf. dan Ilmu Komput., vol. 2, no. 1, pp. 11–19, 2015.

A. A. Harahap, “Sistem Pendukung Keputusan Penentuan Jurusan Dengan Metode Analytical Hierarchy Process ( Studi Kasus : Smk Swasta Kartini Utama Sei Rampah ),” Pelita Inform. Budi Darma, vol. 9, no. 2, pp. 13–20, 2015.

M. Arifin, “Sistem Pendukung Keputusan Pemilihan Sekolah Terbaik Pada Kabupaten Serdang Bedagai Menggunakan Metode AHP dan SAW,” J. INFOTEK, vol. 1, no. 2, pp. 96–105, 2016.

I. Aqli, D. E. Ratnawati, and M. Data, “Sistem Rekomendasi Pemilihan Sekolah Menengah Atas Sederajat Kota Malang Menggunakan Metode AHP ELECTRE Dan TOPSIS,” J. Teknol. Inf. dan Ilmu Komput., vol. 3, no. 4, p. 279, 2016.

T. D. Salma and Y. S. Nugroho, “Sistem Rekomendasi Pemilihan Sekolah Menengah Tingkat Atas Menggunakan Metode Naive Bayes,” Khazanah Inform. J. Ilmu Komput. dan Inform., vol. 2, no. 2, p. 85, 2016.

S. Dewi, G. Abdillah, and A. Komarudin, “Sistem Pendukung Keputusan Pemilihan Sekolah Menengah Atas Boarding School di Jawa Barat Menggunakan TOPSIS,” in Seminar Nasional Sistem Informasi dan Teknologi Informasi (SENSITEK) 2018, 2018, pp. 132–136.

R. Oldakowski and C. Bizer, “SemMF: A framework for calculating semantic similarity of objects represented as RDF graphs,” 4th Int. Semant. Web Conf., pp. 2–4, 2005.

E. Turban, J. E. Aronson, and T.-P. Liang, Decision Support Systems and Intelligent Systems, 7th Edition. Pearson, 2005.

D. Coomans and D. L. Massart, “Alternative k-nearest neighbour rules in supervised pattern recognition : Part 1. k-Nearest neighbour classification by using alternative voting rules,” Anal. Chim. Acta, vol. 136, pp. 15–27, Jan. 1982.




DOI: http://dx.doi.org/10.30646/tikomsin.v6i2.382

Refbacks

  • There are currently no refbacks.


Editorial Office :
TIKomSiN : Jurnal Teknologi Informasi dan Komunikasi Sinar Nusantara
Published by STMIK Sinar Nusantara Surakarta
Address KH Samanhudi 84 - 86 Street, Laweyan Surakarta, Central Java, Indonesia
Postal Code: 57142, Phone & Fax: +62 271 716 500
Website: https://p3m.sinus.ac.id/jurnal/index.php/TIKomSiN
Email: tikomsin @ sinus.ac.id

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Stats of tikomsin