Overview of Infant Nutrition Status Classification with Rough Set Method

Authors

  • Jessica Evonella Napitupulu STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
  • Dimas Trianda STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
  • Refly Natalius Nababan STIKOM Tunas Bangsa, Pematangsiantar, Indonesia

DOI:

https://doi.org/10.55123/jomlai.v2i3.2893

Keywords:

Overview, Classification, Status, Baby Nutrition, Rough Set

Abstract

Infant growth and development is an important issue that can be known through nutritional status assessment. A measure of the fulfillment of nutrition in children that can be predicted based on their weight. In assessing the nutritional status of infants, there are concerns in the community about nutritional problems that are good to know, many babies are malnourished and also want to know which children whose nutrition is really ideal]. Rough Set Algorithm can be used as a mathematical tool to overcome uncertainty and imprecise information. This study aims to classify the percentage of nutritional status of infants, using Microsoft Excel and Rosetta version 2.0.0.0 for research and data analysis. The research produced 20 rules in the form of rule patterns as a reference for classifying the nutritional status of infants as poor, less, normal and more. Based on the rules generated, it is concluded that the most influential condition attributes in classifying the nutritional status of infants are gender, age, weight, height and gender, weight, height.

References

D. F. Uramako, ‘Faktor Determinan yang Berpengaruh Terhadap Status Gizi Remaja’, Jurnal Ilmiah Kesehatan Sandi Husada, vol. 10, no. 2, pp. 560–567, 2021, doi: 10.35816/jiskh.v10i2.651.

Ufiyah Ramlah, ‘Gangguan Kesehatan Pada Anak Usia Dini Akibat Kekurangan Gizi Dan Upaya Pencegahannya’, Ana’ Bulava: Jurnal Pendidikan Anak, vol. 2, no. 2, pp. 12–25, 2021, doi: 10.24239/abulava.vol2.iss2.40.

Nuraeni, Haniarti, and Fitriani Umar, ‘Pengaruh Status Sosial Ekonomi Dan Pola Makan Terhadap Status Gizi Ibu Hamil Di Wilayah Kerja Puskesmas Mattombong Kecamatan Mattiro Sompe Kabupaten Pinrang’, Jurnal Ilmiah Manusia Dan Kesehatan, vol. 4, no. 2, pp. 201–217, 2021, doi: 10.31850/makes.v4i2.558.

Q. N. Sahroji, R. Hidayat, and R. Nababan, ‘Implementasi Kebijakan Dinas Kesehatan Dalam Penanganan Stunting Di Kabupaten Karawang’, Jurnal Pemerintahan dan Politik, vol. 7, no. 1, pp. 34–39, 2022, doi: 10.36982/jpg.v7i1.1983.

L. Mulyana and E. Farida, ‘Pola Pemberian Makan yang Tepat dalam Mengurangi Resiko Obesitas pada Balita’, Indonesian Journal of Public Health and Nutrition, vol. 2, no. 1, pp. 36–42, 2022, doi: 10.15294/ijphn.v2i1.51661.

P. Y. Pane, A. Anaria, and A. S. Eveline, ‘Perbedaan Status Gizi pada Balita Sebelum dan Sesudah Pandemi Covid-19’, Jurnal Penelitian Perawat Profesional, vol. 4, no. 1, pp. 7–16, 2022, doi: 10.37287/jppp.v4i1.699.

N. Nurwahyuni, A. Nurlinda, A. Asrina, and Y. Yusriani, ‘Tingkat Sosial Ekonomi Ibu Baduta Stunting’, Jurnal Ilmiah Kesehatan Sandi Husada, vol. 12, no. 2, pp. 331–338, 2023, doi: 10.35816/jiskh.v12i2.1080.

R. Z. A. Aziz, ‘Implementasi Algoritma Rough Set Dan Naive Bayes Untuk Mendapatkan Rule Dalam Menyeleksi Pemohon Bantuan Fasilitas Rumah Ibadah ( Studi Kasus : Pemerintah Kabupaten Pringsewu )’, vol. 03, no. 02, 2020.

S. R. Ningsih, R. Wulansari, D. Hartama, A. P. Windarto, and A. Wanto, ‘Analysis of PROMETHEE II Method on Selection of Lecturer Community Service Grant Proposals’, in Journal of Physics: Conference Series, Aug. 2019, p. 012004. doi: 10.1088/1742-6596/1255/1/012004.

P. Alkhairi, L. P. Purba, A. Eryzha, A. P. Windarto, and A. Wanto, ‘The Analysis of the ELECTREE II Algorithm in Determining the Doubts of the Community Doing Business Online’, in Journal of Physics: Conference Series, Institute of Physics Publishing, Sep. 2019, p. 012010. doi: 10.1088/1742-6596/1255/1/012010.

R. Watrianthos, W. A. Ritonga, A. Rengganis, A. Wanto, and M. Isa Indrawan, ‘Implementation of PROMETHEE-GAIA Method for Lecturer Performance Evaluation’, Journal of Physics: Conference Series, vol. 1933, no. 1, p. 012067, 2021, doi: 10.1088/1742-6596/1933/1/012067.

S. Sundari, A. Wanto, Saifullah, and I. Gunawan, ‘Sistem Pendukung Keputusan Dengan Menggunakan Metode Electre Dalam Merekomendasikan Dosen Berprestasi Bidang Ilmu Komputer (Study Kasus di AMIK & STIKOM Tunas Bangsa)’, in Seminar Nasional Multi Disiplin Ilmu, 2017, pp. 1–6. doi: 10.17605/OSF.IO/4TWG6.

M. Widyasuti, A. Wanto, D. Hartama, and E. Purwanto, ‘Rekomendasi Penjualan Aksesoris Handphone Menggunakan Metode Analitycal Hierarchy Process (AHP)’, Konferensi Nasional Teknologi Informasi dan Komputer (KOMIK), vol. I, no. 1, pp. 27–32, 2017.

K. Fatmawati et al., ‘Analysis of Promothee II Method in the Selection of the Best Formula for Infants Under Three Years’, Journal of Physics: Conference Series, vol. 1255, no. 1, p. 012009, Aug. 2019, doi: 10.1088/1742-6596/1255/1/012009.

N. Rofiqo, A. P. Windarto, and A. Wanto, ‘Penerapan Metode VIKOR Pada Faktor Penyebab Rendahnya Minat Mahasiswa Dalam Menulis Artikel Ilmiah’, Seminar Nasional Sains & Teknologi Informasi (SENSASI), vol. 1, no. 1, pp. 228–237, 2018.

S. R. Ningsih, D. Hartama, A. Wanto, I. Parlina, and Solikhun, ‘Penerapan Sistem Pendukung Keputusan Pada Pemilihan Objek Wisata di Simalungun’, in Seminar Nasional Teknologi Komputer & Sains (SAINTEKS), 2019, pp. 731–735.

I. A. R. Simbolon, F. Yatussa’ada, and A. Wanto, ‘Penerapan Algoritma Backpropagation dalam Memprediksi Persentase Penduduk Buta Huruf di Indonesia’, Jurnal Informatika Upgris, vol. 4, no. 2, pp. 163–169, 2018, doi: 10.26877/jiu.v4i2.2423.

W. Saputra, J. T. Hardinata, and A. Wanto, ‘Resilient method in determining the best architectural model for predicting open unemployment in Indonesia’, IOP Conference Series: Materials Science and Engineering, vol. 725, no. 1, p. 012115, Jan. 2020, doi: 10.1088/1757-899X/725/1/012115.

E. Hartato, D. Sitorus, and A. Wanto, ‘Analisis Jaringan Saraf Tiruan Untuk Prediksi Luas Panen Biofarmaka Di Indonesia’, SemanTIK, vol. 4, no. 1, pp. 49–56, 2018, doi: 10.55679/semantik.v4i1.4201.

B. K. Sihotang and A. Wanto, ‘Analisis Jaringan Syaraf Tiruan Dalam Memprediksi Jumlah Tamu Pada Hotel Non Bintang’, Jurnal Teknologi Informasi Techno, vol. 17, no. 4, pp. 333–346, 2018, doi: 10.33633/tc.v17i4.1762.

I. S. Purba and A. Wanto, ‘Prediksi Jumlah Nilai Impor Sumatera Utara Menurut Negara Asal Menggunakan Algoritma Backpropagation’, Jurnal Teknologi Informasi Techno, vol. 17, no. 3, pp. 302–311, 2018, doi: 10.33633/tc.v17i3.1769.

A. Wanto, S. Defit, and A. P. Windarto, ‘Algoritma Fungsi Perlatihan pada Machine Learning berbasis ANN untuk Peramalan Fenomena Bencana’, RESTI (Rekayasa Sistem dan Teknologi Informasi), vol. 5, no. 2, pp. 254–264, 2021, doi: 10.29207/resti.v5i2.3031.

A. Wanto and J. T. Hardinata, ‘Estimations of Indonesian poor people as poverty reduction efforts facing industrial revolution 4.0’, IOP Conference Series: Materials Science and Engineering, vol. 725, no. 1, p. 012114, Jan. 2020, doi: 10.1088/1757-899X/725/1/012114.

N. Arminarahmah, A. D. GS, G. W. Bhawika, M. P. Dewi, and A. Wanto, ‘Mapping the Spread of Covid-19 in Asia Using Data Mining X-Means Algorithms’, IOP Conference Series: Materials Science and Engineering, vol. 1071, no. 1, p. 012018, 2021, doi: 10.1088/1757-899x/1071/1/012018.

T. H. Sinaga, A. Wanto, I. Gunawan, S. Sumarno, and Z. M. Nasution, ‘Implementation of Data Mining Using C4.5 Algorithm on Customer Satisfaction in Tirta Lihou PDAM’, Journal of Computer Networks, Architecture, and High-Performance Computing, vol. 3, no. 1, pp. 9–20, 2021, doi: 10.47709/cnahpc.v3i1.923.

A. Pradipta, D. Hartama, A. Wanto, S. Saifullah, and J. Jalaluddin, ‘The Application of Data Mining in Determining Timely Graduation Using the C45 Algorithm’, IJISTECH (International Journal of Information System & Technology), vol. 3, no. 1, pp. 31–36, 2019, doi: 10.30645/ijistech.v3i1.30.

N. A. Febriyati, A. D. Gs, and A. Wanto, ‘GRDP Growth Rate Clustering in Surabaya City uses the K- Means Algorithm’, International Journal of Information System & Technology, vol. 3, no. 2, pp. 276–283, 2020, doi: 10.30645/ijistech.v3i2.60.

I. Parlina et al., ‘Naive Bayes Algorithm Analysis to Determine the Percentage Level of visitors the Most Dominant Zoo Visit by Age Category’, in Journal of Physics: Conference Series, Aug. 2019, p. 012031. doi: 10.1088/1742-6596/1255/1/012031.

E. Mardiani et al., ‘Membandingkan Algoritma Data Mining Dengan Tools Orange untuk Social Economy’, Digital Transformation Technology, vol. 3, no. 2, pp. 686–693, 2023, doi: 10.47709/digitech.v3i2.3256.

E. Astuti, N. E. Saragih, and P. Yunita, ‘Analisis Tingkat Kepuasan Pelanggan Terhadap Penjualan Air Minum Kangen Water Dengan Metode Rough Set’, Bulletin of Information Technology (BIT), vol. 3, no. 3, pp. 179–188, 2022, doi: 10.47065/bit.v3i3.318.

Z. A. Gultom, K. Erwansyah, and A. Calam, ‘Implementasi Data Mining untuk Memprediksi Penghasilan Penjualan Handphone di Toko Ponsel Takasimura dengan Metode Rough Set’, Jurnal Cyber Tech, vol. 2, no. 1, pp. 1–14, 2021.

Downloads

Published

2023-09-30

How to Cite

Napitupulu, J. E., Trianda, D., & Nababan , R. N. . (2023). Overview of Infant Nutrition Status Classification with Rough Set Method . JOMLAI: Journal of Machine Learning and Artificial Intelligence, 2(3), 171–178. https://doi.org/10.55123/jomlai.v2i3.2893

Issue

Vol. 2 No. 3 (2023): September

Section

Articles

License

Copyright (c) 2023 Jessica Evonella Napitupulu, Dimas Trianda, Refly Natalius Nababan

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Copyright (c) 2022 The authors. Published by Yayasan Literasi Indonesia
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License

The author(s) whose article is published in the JOMLAI journal attain the copyright for their article and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. By submitting the manuscript to JOMLAI, the author(s) agree with this policy. No special document approval is required.

The author(s) guarantee that:their article is original, written by the mentioned author(s),

  • has never been published before,
  • does not contain statements that violate the law, and
  • does not violate the rights of others, is subject to copyright held exclusively by the author(s), and is free from the rights of third parties, and that the necessary written permission to quote from other sources has been obtained by the author(s).

The author(s) retain all rights to the published work, such as (but not limited to) the following rights:

  • Copyright and other proprietary rights related to the article, such as patents,
  • The right to use the substance of the article in its own future works, including lectures and books,
  • The right to reproduce the article for its own purposes,
  • The right to archive all versions of the article in any repository, and
  • The right to enter into separate additional contractual arrangements for the non-exclusive distribution of published versions of the article (for example, posting them to institutional repositories or publishing them in a book), acknowledging its initial publication in this journal (JOMLAI: Journal of Machine Learning and Artificial Intelligence).

Suppose the article was prepared jointly by more than one author. Each author submitting the manuscript warrants that all co-authors have given their permission to agree to copyright and license notices (agreements) on their behalf and notify co-authors of the terms of this policy. JOMLAI will not be held responsible for anything that may arise because of the writer's internal dispute. JOMLAI will only communicate with correspondence authors.

Authors should also understand that their articles (and any additional files, including data sets, and analysis/computation data) will become publicly available once published. The license of published articles (and additional data) will be governed by a Creative Commons Attribution-ShareAlike 4.0 International License. JOMLAI allows users to copy, distribute, display and perform work under license. Users need to attribute the author(s) and JOMLAI to distribute works in journals and other publication media. Unless otherwise stated, the author(s) is a public entity as soon as the article is published