Implementasi Metode K-Means berbasis Chi-Square pada Sistem Pendukung Keputusan untuk Identifikasi Disparitas Kebutuhan Guru

M. Nishom; Dega Surono Wibowo

doi:10.21456/vol8iss2pp187-194

DOI: https://doi.org/10.21456/vol8iss2pp187-194

Implementasi Metode K-Means berbasis Chi-Square pada Sistem Pendukung Keputusan untuk Identifikasi Disparitas Kebutuhan Guru

*M. Nishom

- Politeknik Harapan Bersama Tegal, Indonesia

Dega Surono Wibowo - Politeknik Harapan Bersama Tegal, Indonesia

BibTex Citation Data :

@article{JSINBIS20093,
    author = {M. Nishom and Dega Wibowo},
    title = {Implementasi Metode K-Means berbasis Chi-Square pada Sistem Pendukung Keputusan untuk Identifikasi Disparitas Kebutuhan Guru},
    journal = {Jurnal Sistem Informasi Bisnis},
  volume = {8},
    number = {2},
    year = {2018},
    keywords = {Clustering; K-Means; Chi-Square; Teacher disparity; Student-teacher ratio.},
    abstract = { In this research, the Chi-Square-based K-Means method was implemented in the Decision Support System (DSS) to identify the disparity in Teacher's needs compared to the real conditions of Teacher's availability in the education unit (school). This is very important, because based on data from the UNESCO Institute for Statistics shows that the ratio between teachers and students in Indonesia is the lowest in the world. This is influenced by the distribution of Teachers who do not meet the needs and exceed the number of student enrollments at all levels of education, resulting in less optimal quality of education produced in various regions in Indonesia. Thus, it is necessary to group data and label the disparity of Teacher's needs in educational units in various regions in Indonesia, especially in the Tegal City. In this case, the K-Means Clustering method was used to group data based on Teacher's availability data, and Chi-Square analysis was used to determine the disparity in Teacher's needs with the condition of Teacher's availability. Data collection methods used in research are observation methods. The results showed that the DSS application that had been produced could dynamically determine the education unit cluster based on the teacher availability disparity category in the Tegal City. In addition, labeling of the K-Means cluster based on the Chi-square test has a high degree of accuracy, which is 84.47%. },
   issn = {2502-2377},   pages = {187--194}  doi = {10.21456/vol8iss2pp187-194},
    url = {https://ejournal.undip.ac.id/index.php/jsinbis/article/view/20093}
}

Citation Format:

Abstract

In this research, the Chi-Square-based K-Means method was implemented in the Decision Support System (DSS) to identify the disparity in Teacher's needs compared to the real conditions of Teacher's availability in the education unit (school). This is very important, because based on data from the UNESCO Institute for Statistics shows that the ratio between teachers and students in Indonesia is the lowest in the world. This is influenced by the distribution of Teachers who do not meet the needs and exceed the number of student enrollments at all levels of education, resulting in less optimal quality of education produced in various regions in Indonesia. Thus, it is necessary to group data and label the disparity of Teacher's needs in educational units in various regions in Indonesia, especially in the Tegal City. In this case, the K-Means Clustering method was used to group data based on Teacher's availability data, and Chi-Square analysis was used to determine the disparity in Teacher's needs with the condition of Teacher's availability. Data collection methods used in research are observation methods. The results showed that the DSS application that had been produced could dynamically determine the education unit cluster based on the teacher availability disparity category in the Tegal City. In addition, labeling of the K-Means cluster based on the Chi-square test has a high degree of accuracy, which is 84.47%.

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Keywords: Clustering; K-Means; Chi-Square; Teacher disparity; Student-teacher ratio.

Funding: Politeknik Harapan Bersama

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Article Info

Section: Research Articles

Language : EN

In Vol 8, No 2 (2018): Volume 8 Nomor 2 Tahun 2018

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