Implementasi Metode K-Medoids Clustering Dalam Pengelompokan Data Penyakit Alergi Pada Anak

Abstract

Allergies are an abnormal response from the immune system. People who experience allergies have an immune system that reacts to a substance that is usually harmless in the environment. There are two limitations in this study, namely, seafood allergy and air allergy. In this study, the data used were sourced from the National Statistics Agency in 2011-2019. This study uses data mining techniques in data processing with the k-medoids clustering method. The k-medoids method is a clustering method that functions to split the dataset into several groups. The advantages of this method are able to overcome the weaknesses of the k-means method which is sensitive to outliers. Another advantage of this method is that the results of the clustering process do not depend on the order in which the dataset is entered. This method can be applied to data on the percentage of children affected by allergies by province, so that it can be seen the grouping of provinces based on this data. From this grouping data obtained 3 clusters namely low cluster (2 provinces), medium cluster (30 provinces) and high cluster (2 provinces) from the percentage of allergy immunization under five in each province. It is hoped that this research can provide information to the health department, especially the public health center regarding data grouping of Allergic Diseases in children in Indonesia which has an impact on equity in giving anti-allergic immunization to children in Indonesia

Description of CRP Levels in Allergic Mice After Ketepeng Leaf Infusa Treatment

“…Alergi dianggap sebagai respon abnormal dari sistem kekebalan tubuh. (Azizah & Kurniati, 2020) World Health Organization (WHO) memperkirakan bahwa di dunia ada sekitar 400 juta orang yang menderita alergi (Ningrum et al, 2021). Beberapa riset mengatakan bahwa pada tahun 2019 prevalensi alergi pada orang dewasa sebesar 10 -30% dan anak-anak 40% di seluruh dunia.…”

“…(Dwi estuningsih, 2020). Pada studi kasus dalam jurnal riset informasi dan teknik informatika pada tahun 2019 didapatkan persentase penderita alergi pada anak di provinsi Kalimantan Timur sebesar 0,96% (Ningrum et al, 2021) Terdapat banyak zat yang dapat menyebabkan alergi. Diantara banyak zat tersebut salah satunya adalah ovalbumin (OVA) yang terdapat pada protein putih telur dan merupakan alergen spesifik, apabila OVA disuntikkan pada subkutan kulit hewan coba terbukti meningkatkan aktivasi T-Helper 2 (Th2) dominan dan produksi IgE spesifik (Caubet et al, 2012).…”

K-Medoids Algorithm to Clustering COVID-19 Patients with Various Age Levels at Hospitals in Yogyakarta Province

“…In previous study conducted by Ningrum et al, K-Medoids algorithm can be applied to data on the percentage of children affected by allergic diseases by province, so 34 provinces are obtained resulting in 21 provinces, namely low clusters, 12 provinces in medium clusters, and 1 province in high clusters allergy immunization percentage in each province (Ningrum et al, 2021).…”

Klasterisasi Penyakit Menggunakan Algoritma K-Medoids pada Dinas Kesehatan Kabupaten Agam

“…Penelitian tentang pengelompokkan data penyakit alergi pada anak dengan mengimplementasikan algoritma k-Medoids membagi klaster menjadi 3, yaitu rendah 21 provinsi, sedang 12 provinsi, dan 1 provinsi untuk klaster tinggi [13]. Penelitian tentang pengelompokkan penyebaran covid-19 di Indonesia berdasarkan gejala suhu badan di atas 36,9 0 C, demam, dan batuk, menghasilkan 3 klaster [14].…”