3rd South American International Conference on Industrial Engineering and Operations Management

CLASSIFICATION OF DRUG DATA PLANNING USING K-NEAREST NEIGHBORS ALGORITHM

Lisa Dwi Novitasari, Wina Witanti, Melina & Asep Id Hadiana
Publisher: IEOM Society International
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Track: Undergraduate Student Paper Competition
Abstract

Puskesmas is one of the government agencies that handles community services. Puskesmas activities in providing public health services certainly store a lot of data. In general, the Puskesmas records data to make reports. One of them is the drug management report. Generally, the drug management system at the puskesmas is an activity that involves aspects of planning, requesting, receiving, storing, distributing, using, recording and reporting by utilizing available sources. This research focuses on the planning aspect. Drug planning activities are useful for ensuring drug availability. The drug planning stage is very important. Inaccurate drug planning can lead to drug accumulation, drug vacancies, and drug damage which can lead to less than optimal health services at the Puskesmas. The planning stage will also affect the following stages. The case study of this research is the Cicangkanggirang Health Center. This research is related to data mining. One of the algorithms/methods/techniques of extracting or searching for information in data mining is data classification. One method that can be used in data classification is using the K-Nearest Neighbors method. The purpose of this study is to analyze the classification of drug data regarding planning aspects at the Cicangkanggirang Health Center by using the K-Nearest Neighbors method, in order to facilitate drug managers in preparing a Needs Plan. Drugs (RKO) at the time of submitting a drug requirement. This study uses the K-Nearest Neighbors method by applying several research stages, namely, data collection, Knowledge Discovery in Databases (KDD) process, classification techniques (K-Cross validation, Euclidean Distance, results and accuracy), and software development.

Keywords
Data Mining, Classification, K-Nearest Neighbor, Drug Planning.

 

Published in: 3rd South American International Conference on Industrial Engineering and Operations Management

Publisher: IEOM Society International
Date of Conference: May 10-12, 2022

ISBN: 978-1-7923-9159-0
ISSN/E-ISSN: 2169-8767