KLASIFIKASI STATUS GIZI MENGGUNAKAN NAIVE BAYESIAN CLASSIFICATION
DOI:
https://doi.org/10.21512/commit.v3i1.506Abstract
Until recently, Body Mass Index (BMI) has been used as a method for measuring the nutrient state of an individual. Two people having the same weight and height may have different nutrient states. Whenever this occurs, the use of BMI for measuring the nutrient state shall be deemed irrelevant. The anthropometry will be vital in measuring the nutrient state. On the contrary, as the development of IT progresses, so does the improvement of numerical computation. One of the computational algorithms that have been improving is probabilistic reasoning with Naive Bayesian Classification (NBC) as its method. This algorithm is intended to data classification. In this research, the NBC algorithm will be applied for measuring the human nutrient status by using anthropometry data as input system. The result of this research shows that NBC can solve this problem adequately. Research results shows total performance of this system as 93.2%.Keywords: classification, Naive Bayesian Classification (NBC), nutrition
Plum Analytics
Downloads
Published
Issue
Section
License
Authors who publish with this journal agree to the following terms:
a. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License - Share Alike that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
b. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
c. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
USER RIGHTS
All articles published Open Access will be immediately and permanently free for everyone to read and download. We are continuously working with our author communities to select the best choice of license options, currently being defined for this journal as follows: Creative Commons Attribution-Share Alike (CC BY-SA)
