PERBANDINGAN METODE LVQ DAN BACKPROPAGATION UNTUK KLASIFIKASI STATUS GIZI ANAK DI KECAMATAN SANGKUP

Fahima Alamri; Setia Ningsih; Ismail Djakaria; Djihad Wungguli; Isran K. Hasan

doi:10.14710/j.gauss.12.3.314-321

DOI: https://doi.org/10.14710/j.gauss.12.3.314-321

PERBANDINGAN METODE LVQ DAN BACKPROPAGATION UNTUK KLASIFIKASI STATUS GIZI ANAK DI KECAMATAN SANGKUP

Fahima Alamri - Universitas Negeri Gorontalo, Indonesia

*Setia Ningsih - Universitas Negeri Gorontalo, Indonesia

Ismail Djakaria - Universitas Negeri Gorontalo, Indonesia

Djihad Wungguli - Universitas Negeri Gorontalo, Indonesia

Isran K. Hasan - Universitas Negeri Gorontalo, Indonesia

How to cite (IEEE): F. Alamri, S. Ningsih, I. Djakaria, D. Wungguli, and I. K. Hasan, "PERBANDINGAN METODE LVQ DAN BACKPROPAGATION UNTUK KLASIFIKASI STATUS GIZI ANAK DI KECAMATAN SANGKUP," Jurnal Gaussian, vol. 12, no. 3, pp. 314-321, Sep. 2023. https://doi.org/10.14710/j.gauss.12.3.314-321

How to cite (APA): Alamri, F., Ningsih, S., Djakaria, I., Wungguli, D., & K. Hasan, I. (2023). PERBANDINGAN METODE LVQ DAN BACKPROPAGATION UNTUK KLASIFIKASI STATUS GIZI ANAK DI KECAMATAN SANGKUP. Jurnal Gaussian, 12(3), 314-321. https://doi.org/10.14710/j.gauss.12.3.314-321

How to cite (BCREC): Alamri, F., Ningsih, S., Djakaria, I., Wungguli, D., K. Hasan, I. (2023). PERBANDINGAN METODE LVQ DAN BACKPROPAGATION UNTUK KLASIFIKASI STATUS GIZI ANAK DI KECAMATAN SANGKUP. Jurnal Gaussian, 12 (3), 314-321 (doi:10.14710/j.gauss.12.3.314-321)

How to cite (Chicago): Alamri, Fahima, Setia Ningsih, Ismail Djakaria, Djihad Wungguli, and Isran K. Hasan. "PERBANDINGAN METODE LVQ DAN BACKPROPAGATION UNTUK KLASIFIKASI STATUS GIZI ANAK DI KECAMATAN SANGKUP." Jurnal Gaussian 12, no. 3 (2023): 314-321. Accessed : April 5, 2025. https://doi.org/10.14710/j.gauss.12.3.314-321

How to cite (Vancouver): Alamri F, Ningsih S, Djakaria I, Wungguli D, K. Hasan I. PERBANDINGAN METODE LVQ DAN BACKPROPAGATION UNTUK KLASIFIKASI STATUS GIZI ANAK DI KECAMATAN SANGKUP. Jurnal Gaussian [Online]. 2023 Sep;12(3):314-321. https://doi.org/10.14710/j.gauss.12.3.314-321.

How to cite (Harvard): Alamri, F., Ningsih, S., Djakaria, I., Wungguli, D., and K. Hasan, I., 2023. PERBANDINGAN METODE LVQ DAN BACKPROPAGATION UNTUK KLASIFIKASI STATUS GIZI ANAK DI KECAMATAN SANGKUP. Jurnal Gaussian, [Online] Volume 12(3), pp. 314-321. https://doi.org/10.14710/j.gauss.12.3.314-321 [Accessed : 5 Apr. 2025].

How to cite (MLA8): Alamri, Fahima, Setia Ningsih, Ismail Djakaria, Djihad Wungguli, and Isran K. Hasan. "PERBANDINGAN METODE LVQ DAN BACKPROPAGATION UNTUK KLASIFIKASI STATUS GIZI ANAK DI KECAMATAN SANGKUP." Jurnal Gaussian, vol. 12, no. 3, 05 Sep. 2023, pp. 314-321 , https://doi.org/10.14710/j.gauss.12.3.314-321. Retrieved : 5 Apr. 2025.

BibTex Citation Data :

@article{J.Gauss37612,
    author = {Fahima Alamri and Setia Ningsih and Ismail Djakaria and Djihad Wungguli and Isran K. Hasan},
    title = {PERBANDINGAN METODE LVQ DAN BACKPROPAGATION UNTUK KLASIFIKASI STATUS GIZI ANAK DI KECAMATAN SANGKUP},
    journal = {Jurnal  Gaussian},
  volume = {12},
    number = {3},
    year = {2023},
    keywords = {Status Gizi; Klasifikasi; LVQ; Backpropagation},
    abstract = {The problem of children nutrition isi still a problem in various regions in Indonesia. Poor or poor nutrition of children is influenced by several factors, namely insufficient food intake and infectious diseases. Undernutrition or poor nutrition can be known from the nutritional status assessment obtained from classifying the nutrional status of children. Classification is a part of data mining that is often used to classify data based on certain data or variables. This study aims to compare the classification of the nutritional status of children using data mining with the learning vector quantization (LVQ) and backpropagation methods. Test were carried out using a comparasion ratio of training and testing data, namely 75% and 25%. From the research results, LVQ is superior with an accuracy of 95.12% and backpropagation of 80.49%.},
   issn = {2339-2541},   pages = {314--321}  doi = {10.14710/j.gauss.12.3.314-321},
    url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/37612}
}

Refworks Citation Data :

@article{{J.Gauss}{37612}, author = {Alamri, F., Ningsih, S., Djakaria, I., Wungguli, D., K. Hasan, I.}, title = {PERBANDINGAN METODE LVQ DAN BACKPROPAGATION UNTUK KLASIFIKASI STATUS GIZI ANAK DI KECAMATAN SANGKUP}, journal = {Jurnal Gaussian}, volume = {12}, number = {3}, year = {2023}, doi = {10.14710/j.gauss.12.3.314-321}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/37612} }

Citation Format:

Abstract

The problem of children nutrition isi still a problem in various regions in Indonesia. Poor or poor nutrition of children is influenced by several factors, namely insufficient food intake and infectious diseases. Undernutrition or poor nutrition can be known from the nutritional status assessment obtained from classifying the nutrional status of children. Classification is a part of data mining that is often used to classify data based on certain data or variables. This study aims to compare the classification of the nutritional status of children using data mining with the learning vector quantization (LVQ) and backpropagation methods. Test were carried out using a comparasion ratio of training and testing data, namely 75% and 25%. From the research results, LVQ is superior with an accuracy of 95.12% and backpropagation of 80.49%.

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Keywords: Status Gizi; Klasifikasi; LVQ; Backpropagation

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In Vol 12, No 3 (2023): Jurnal Gaussian