Alleyda Irzky Shafarindu, . (2021) PENERAPAN ALGORITMA NAIVE BAYES UNTUK KLASIFIKASI TINGKAT KEBUGARAN JASMANI BERDASARKAN HASIL PENGUKURAN PADA PEGAWAI. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
In order to do an activity, physical fitness is needed so that activities can be carried out optimally and efficiently. Physical fitness has an important role that can affect work productivity. The State Civil Apparatus (ASN) is a worker of productive age who needs good physical fitness in carrying out his duties and functions. In order of the national health day, Dinas Kesehatan Provinsi Kepulauan Bangka Belitung does a physical fitness check to check physical fitness level of employees, the measurements performed with Rockport Test or a 6 minute Walk Test for employees who have high-risk diseases. In this research, the results of measurements of physical fitness for employees will be classified. The classification using the Naïve Bayes algorithm. The Naive Bayes algorithm is one of the algorithms that can be used in the classification method. This algorithm was chosen because it has a fairly high accuracy value and is suitable for this research. For splitting data, this research uses k-fold cross validation with value of k is 4.The result of this research is value of accuration is 94%, value of precision is 92%, value of recall is 94%, and value of F1-Score is 93
Item Type: | Thesis (Skripsi) |
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Additional Information: | [No.Panggil: 1710511047], [Pembimbing 1: lin Ernawati], [Pembimbing 2: Ati Zaidiah], [Penguji 1: Ermatita], [Penguji 2: Nurul Chamidah] |
Uncontrolled Keywords: | measurement of physical fitness, classification, naïve bayes |
Subjects: | T Technology > T Technology (General) Z Bibliography. Library Science. Information Resources > ZA Information resources Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4450 Databases |
Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
Depositing User: | Alleyda Irzky Shafarindu |
Date Deposited: | 21 Dec 2021 07:17 |
Last Modified: | 21 Dec 2021 07:17 |
URI: | http://repository.upnvj.ac.id/id/eprint/11680 |
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