Analisis Clustering Data Penyandang Disabilitas Menggunakan Metode Agglomerative Hierarchical Clustering dan K-means

Alun Sujjada, Gina Purnama Insany, Silvia Noer

Abstract


Disability issues are still a major concern in society due to the discrimination often faced by people with disabilities. Many of them have abilities that are equal to individuals without physical limitations. Through this case study, this research aims to Cluster disability data by considering three types of disabilities: physical, visual and hearing, and hearing and speech using agglomerative hierachical Clustering and kmeans methods. This research was conducted by analyzing data from people with disabilities in 7 provinces in Indonesia. K-means to group data and agglomerative hierarchical Clustering as a centroid determinant in k-means. to enrich the results of data analysis, the EDA (Exploratory Data Analysis) process is used to identify outliers and anomalies. The results of the data analysis show that there are three main Clusters. The first Cluster has a high level of disability and includes 62 cities and districts, the second Cluster has a medium level of disability with 37 cities and districts, and the third Cluster has a low level of disability with 27 cities and districts. The best evaluation using the Davies Bouldin Index method resulted in two Clusters, indicating a better quality of Cluster division. The results of this study provide a better understanding of the distribution of disability in Indonesia, which can be used as a foundation to improve inclusion and accessibility for people with disabilities. Further recommendations can be made based on these findings to improve their situation in terms of employment and education.


Keywords


Persons with disabilities; Agglomerative Hierarchical Clustering; K-means; EDA (Exploratory Data Analysis); DBI Davies Bouldin Index;

Full Text:

PDF

References


Basysyar Fadhil, M. (2021). Clustering Data Disabilitas Menggunakan Algoritma K-Means Di Kabupaten Cirebon. STMIK GICI. vol. 9.

Muningsih, E. (2021). Penerapan Metode K-Means dan Optimasi Jumlah Cluster dengan Index Davies Bouldin untuk Clustering Propinsi Berdasarkan Potensi Desa. Jurnal Sains dan Manajemen. vol. 9, no. 1.

Akbar, M. P. (2023). Kesetaraan Akses Bagi Penyandang Disabilitas. Accessed: Jun. 05.

Enterprise, J. (2019). Phyton untuk Programmer Pemula.

Setiawan Suparno, D. (2021). Target Pasar Menggunakan Metode EDA, K-Means, Hierarchial Clustering, Confusion Matrix..

Najwa, N. F. (2021). Akuisisi Data Media Sosial Pemerintah Untuk Menganalisis Keterbukaan Informasi Penyebaran Covid-19. Jurnal Sosioteknologi. vol. 20, no. 1. 46–55, Apr.

Wahyuni, E. D. (2019). Exploratory Data Analysis dalam Konteks Klasifikasi Data Mining. pp. 263–269.

Radhi, M. (2021). Analisis Big Data Dengan Metode Exploratory Data Analysis (Eda) Dan Metode Visualisasi Menggunakan Jupyter Notebook. Jurnal Sistem Informasi dan Ilmu Komputer Prima. vol. 4, no. 2.

Ilmu, J., Sosial, K. (2019). Penyandang Disabilitas Di Indonesia: Perkembangan Istilah Dan Definisi.

Wahyudi, N. (2021). Komparasi Algoritma K-Means, K-Medoid, Agglomeartive Clustering Terhadap Genre Spotify. vol. 7, no. 1.

Wahyuni D. (2019). Analisa Clustering Pada Data Pelanggaran Lalulintas Di Pengadilan Negeri Dumai Dengan Menggunakan Metode K-Means.

Arientawati. (2023). Analisis Pengelompokan Gangguan TIK Pada Sistem Pencatatan Layanan Menggunakan Algoritma K-Means dan Metode Elbow. Techno.COM. vol. 22, May.

Dewi Dewa, A. I. C. (2019). Analisis Perbandingan Metode Elbow dan Sillhouette pada Algoritma Clustering K-Medoids dalam Pengelompokan Produksi Kerajinan Bali. JURNAL MATRIX. vol. 9, Nov.

Mulyono, U. W. (2020). Klasterisasi Perkara Pelanggaran Lalu Lintas Menggunakan Algoritma K-Means Dan Davies-Bouldin Index. Vol. 5.

Septiani, I. W. (2022). Implementasi Algoritma K-Medoids Dengan Evaluasi Davies-Bouldin-Index Untuk Klasterisasi Harapan Hidup Pasca Operasi Pada Pasien Penderita Kanker Paru-Paru. Jurnal Sistem Komputer dan Informatika (JSON), vol. 3, no. 4, p. 556, Jul.




DOI: https://doi.org/10.26905/jtmi.v10i1.10654

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Jurnal Teknologi dan Manajemen Informatika

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

Indexing by:
width="150"

SINTA - Science and Technology Index

Index Copernicus International (ICI)

Tools

Turnitin

crossref

Mendeley

Jurnal Teknologi dan Manajemen Informatika 


Fakultas Teknologi Informasi
University of Merdeka Malang

Alamat:

Jl. Terusan Raya Dieng No. 62-64, Malang, Indonesia, 65146
(0341) 566462
Email: [email protected]


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