PRAYOGI, AGUS (2020) KLASIFIKASI DATA KARAKTERISTIK PASIEN BERDASARKAN TREATMENT GIZI MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBORS. Undergraduate thesis, UPN"VETERAN" JATIM.
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Abstract
For a company engaged in services and health, it is very important to read the characteristics of consumers in order to develop the company and produce the right product for consumer. With the large number of nutritional treatment patients, it is still difficult to determine the appropriate and accurate follow-up nutritional treatment for each patient each patient. Patient data collection and interviews with patients are required to obtain treatment data that is suitable for the patient. However, for to get the appropriate follow-up treatment, there is still a need for a system that can processing past patient data so as to produce more effective follow-up treatments more accurate. The method used for this research is to calculate the value of training data and K points with the K – Nearest Neighbors Algorithm. Goal namely to determine the treatment package menu recommendations for consumers. The K-Nearest Neighbors algorithm is one of the algorithms that can used for the implementation of this system development. As is patient characteristics and data distance calculation using euclidean function distance, it can generate categories that can be used for determine the nutritional treatment that is more accurate and good for each patient. Scenario in testing with comparison of training data and test data 3:1 has the highest program accuracy reaches 88%, the precision reaches 91% and recall reached 95% among all test scenario results try. Keywords: Euclidean Distance, K-Nearest Neighbors Algorithm, Treatment Nutrition, Patient Characteristics
| Item Type: | Thesis (Undergraduate) | ||||||||
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| Subjects: | Q Science > QA Mathematics > QA76.76.E95 Expert Systems | ||||||||
| Divisions: | Faculty of Computer Science > Departemen of Information Systems | ||||||||
| Depositing User: | Mujari Mujari | ||||||||
| Date Deposited: | 22 Jun 2021 03:20 | ||||||||
| Last Modified: | 22 Jun 2021 03:20 | ||||||||
| URI: | http://repository.upnjatim.ac.id/id/eprint/2055 |
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