Data Mining Menggunakan Algoritma K-Means untuk Klasifikasi Penyakit Infeksi Saluran Pernafasan Akut

Ariyanto, Davit

doi:10.37034/jsisfotek.v4i1.117

Cited by 8 publications

(8 citation statements)

References 15 publications

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“…Pada tahap ini dilakukan proses encoding atribut nama_penyakit, nama_kecamatan dan nama_desa menjadi nilai numerik, kemudian dilakukan proses summary atau agregasi data dengan menambahkan atribut baru yaitu atribut jumlah_pasien untuk kebutuhan dapam proses data mining [13]. Hasil transformasi dapat dilihat pada Tabel 2.…”

Section: Data Transformationunclassified

Application of Data Mining in Disease Clustering at Klinik Keluarga

Kadafi,

Finandhita

2024

KOMPUTA

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The purpose of this study is to provide recommendations for counseling materials to assist the Promkes and Marketing Coordinator at the Klinik Keluarga in determining appropriate health counseling materials in an area. Counseling is conducted on a scheduled basis to a predetermined area. However, many of the materials presented are not in accordance with the majority of diseases suffered by the community in the area. This causes clinic services to be not optimal due to lack of awareness of a disease in the region. Data Mining with Clustering method and K-Means algorithm is used in this study to determine the pattern of disease distribution based on its characteristics from the data sources used, consisting of visit data, parent disease data, disease category data, sub-district data, and village data. The evaluation results show that the disease clustering process produces an average accuracy of 0.263. These results show that data mining with the clustering method can help the Promkes and Marketing Coordinator at the Family Clinic in determining the right counseling material for the community.

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Section: Data Transformationunclassified

Application of Data Mining in Disease Clustering at Klinik Keluarga

Kadafi,

Finandhita

2024

KOMPUTA

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“…Adiputra I., in 2022 conduct research on grouping DHF data at Dharma Kerti Hospital to find out in-depth information about DHF that occurs, so that hospitals can make the right decisions based on data [8]. In 2022, Ariyanto Analyze and classify data using the K-Means algorithm to be able to group data on patients with ARI symptoms quickly and accurately [9]. In 2020, Al-Rizki et al apply data mining to determine the spread of TB disease with a case study at RSU Aisyiyah Ponorogo [10].…”

Section: Related Workmentioning

confidence: 99%

Implementation of K-Means Algorithm for Diseases Clustering in Elderly Posyandu Participants

Firdaus

Devi²

2022

ATCSJ

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The Posyandu of Tirem Village is one of the integrated service posts for the elderly, where they can get proper health services. To get the right health services, Posyandu officers group elderly posyandu participants who suffer from chronic diseases for counseling and treatment. The problems that occur during the data collection and counseling process carried out by Posyandu officers are in the calculations that are still basic and are carried out alternately on the elderly Posyandu participants in Tirem village. So this method has the risk of inaccurate data collection and inconsistent handling for the treatment of elderly residents due to different health histories among the elderly. This study aims to classify the data of elderly posyandu participants in Tirem Village who suffer from chronic diseases with predetermined attributes. This grouping process uses the Clustering method using the K-Means Algorithm. The data used in the form of 40 elderly posyandu participant data in October 2022. The results of data processing using the K-Means algorithm with Microsoft Excel tools and using RapidMiner obtained the same results, namely Cluster 1 and cluster_0 have a total of 32 data from 40 data, Cluster 2 and cluster_1 have a total of 8 data from 40 data.

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“…Acute Respiratory Infection (ARI) is an acute infection that attacks one or more parts of the respiratory tract from the nose to the alveoli, including the adnexa (sinuses, middle ear cavity, and pleura) [8] [13]. Infected individuals spread microorganisms through inhalation when coughing, sneezing, or talking.…”

Section: Literature Reviewmentioning

confidence: 99%

The Rationality of Antibiotic Prescription in Acute Upper Respiratory Infection Patients in Baun Puskesmas, Kupang Regency in 2020

Sihombing

Djojosaputro

2022

Int J Sci Healthcare Res

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Acute upper respiratory tract infection is an infectious disease caused by microorganisms, one of which is bacteria, so antibiotics are given. Rational use of antibiotics can provide benefits for recovery and does not provide harm that can cause problems or threats to the patient's health. Inappropriate administration of antibiotics can harm patients, one of which is antibiotic resistance. The purpose of this study was to obtain an overview of the rationale for prescribing antibiotics in patients with acute upper respiratory tract infections at the Baun Health Center, Kupang Regency, in 2020. This study was conducted using a descriptive non-experimental study with retrospective medical record data collection and guidelines from PERMENKES No. .5 of 2014 concerning Clinical Practice Guidelines for Doctors in Primary Health Care Facilities and KMK HK.02.02/MENKES/514/2015 concerning Clinical Practice Guidelines for Doctors in First Level Health Care Facilities to determine the accuracy of indications, drug accuracy, patient accuracy, and accuracy dose. The results showed 100% correct indication, 90.3% right drug, 100% right patient, 65% right dose, and 55.3% rational use of antibiotics. Keywords: Acute upper respiratory tract infection, antibiotics, rationality, right indication, right drug, right patient, right dose.

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Data Mining Menggunakan Algoritma K-Means untuk Klasifikasi Penyakit Infeksi Saluran Pernafasan Akut

Cited by 8 publications

References 15 publications

Application of Data Mining in Disease Clustering at Klinik Keluarga

Application of Data Mining in Disease Clustering at Klinik Keluarga

Implementation of K-Means Algorithm for Diseases Clustering in Elderly Posyandu Participants

The Rationality of Antibiotic Prescription in Acute Upper Respiratory Infection Patients in Baun Puskesmas, Kupang Regency in 2020

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