THE DESIGN OF STANDARD GRAPH FOR TODDLER GROWTH USES NONPARAMETRIC PENALIZED SPLINE REGRESSION

  • Alif Yuanita Kartini Department of Statistics, Faculty of Science and Technology, Universitas Nahdlatul Ulama Sunan Giri, Indonesia https://orcid.org/0009-0007-4651-9763
  • Jauhara Rana Budiani Department of Statistics, Faculty of Science and Technology, Universitas Nahdlatul Ulama Sunan Giri, Indonesia https://orcid.org/0009-0009-7026-817X
  • Muhammad Arifat Department of Statistics, Faculty of Science and Technology, Universitas Nahdlatul Ulama Sunan Giri, Indonesia https://orcid.org/0009-0000-0800-491X
Keywords: Nonparametric, Penalized Spline, Toddler Growth

Abstract

One way to carry out early detection of toddler growth is through the Healthy Way Card (KMS). The KMS used in Indonesia does not describe the growth behavior of toddlers. The KMS used is the standard from the World Health Organization (WHO). Apart from that, the growth chart for toddlers at each age will show different patterns. This pattern does not form a linear graph or a particular pattern. Therefore, the Nonparametric Regression method was used using a penalized spline estimator which produces a local Indonesian standard KMS which is used to assess the growth of toddlers. Designing KMS with a confidence interval approach to nonparametric regression values using a penalized spline estimator. Data was obtained from the results of the recapitulation of Posyandu in Bojonegoro from January to December 2023, totaling 120 data. The variables used in this research are the toddler's weight (y) as the response variable and the toddler's age (x) as the predictor variable. In nonparametric regression modeling using a penalized spline estimator with several combinations of numbers and knot point locations. Selection of optimal knot points using minimum Generalized Cross Validation (GCV). Based on the results of the analysis, it shows that there are different times of weight change for male toddlers and female toddlers in Bojonegoro. The weight of male toddlers in Bojonegoro has 3 patterns of change, namely the weight of male toddlers increases drastically until the age of 16 months, then increases slowly until the age of 55 months. Then the weight of male toddlers will increase again drastically after the age of 55 months. Meanwhile, the weight of female toddlers in Bojonegoro has three patterns of change, namely the weight of female toddlers increases drastically until the age of 5 months, then increases slowly until the age of 15 months, and again increases drastically after the age of 15 months. This can be caused by physical differences in babies based on gender. To create a standard chart for toddlers' weight growth based on age, it was analyzed by calculating the percentile values consisting of P3, P15, P50, P85, and P97 for each toddler age category.

Downloads

Download data is not yet available.

References

U. Nopriansyah, H. Wulandari, and R. Pangastuti, “PENGEMBANGAN APLIKASI KESEHATAN BERBASIS MOBILE UNTUK PEMANTAUAN DETEKSI DINI TUMBUH KEMBANG (DDTK) ANAK USIA 4-6 TAHUN,” Al-Athfaal J. Ilm. Pendidik. Anak Usia Dini, vol. 3, no. 1, pp. 98–111, 2020.

D. Low, A. Jamil, N. Md Nor, S. B. Kader Ibrahim, and B. K. Poh, “FOOD RESTRICTION, NUTRITION STATUS, AND GROWTH IN TODDLERS WITH ATOPIC DERMATITIS,” Pediatr. Dermatol., vol. 37, no. 1, pp. 69–77, 2020.

D. Arini, N. Nursalam, M. Mahmudah, and I. Faradilah, “THE INCIDENCE OF STUNTING, THE FREQUENCY/DURATION OF DIARRHEA AND ACUTE RESPIRATORY INFECTION IN TODDLERS,” J. Public health Res., vol. 9, no. 2, p. jphr-2020, 2020.

L. Lin, E. Amissah, G. D. Gamble, C. A. Crowther, and J. E. Harding, “IMPACT OF MACRONUTRIENT SUPPLEMENTS ON LATER GROWTH OF CHILDREN BORN PRETERM OR SMALL FOR GESTATIONAL AGE: A SYSTEMATIC REVIEW AND META-ANALYSIS OF RANDOMISED AND QUASIRANDOMISED CONTROLLED TRIALS,” PLoS Med., vol. 17, no. 5, p. e1003122, 2020.

R. Ernawati, F. Fadzlul Rahman, S. Khoiroh M, D. Rahmah F, M. Milkhatun, and J. Sulistiawati, “THE EFFECTIVENESS OF WEB-BASED AUDIOVISUAL MEDIA APPLICATIONS IN MONITORING CHILDREN’S GROWTH TO PREVENT STUNTING,” 2021.

S. Hendrawati et al., “PEMBERDAYAAN KADER POSYANDU DALAM STIMULASI DETEKSI DAN INTERVENSI DINI TUMBUH KEMBANG (SDIDTK) PADA ANAK USIA 0–6 TAHUN DI DESA CILELES KECAMATAN JATINANGOR KABUPATEN SUMEDANG,” Media Karya Kesehat., vol. 1, no. 1, 2018.

B. A. Paramashanti and S. Sulistyawati, “PENGARUH INTEGRASI INTERVENSI GIZI DAN STIMULASI TUMBUH KEMBANG TERHADAP PENINGKATAN BERAT BADAN DAN PERKEMBANGAN BALITA KURUS,” J. Gizi Klin. Indones., vol. 15, no. 1, pp. 16–21, 2019.

D. Ernawati and F. Agiwahyuanto, “HUBUNGAN PERILAKU HIDUP SEHAT ORANG TUA BALITA DENGAN LITERASI KMS (KARTU MENUJU SEHAT) SEBAGAI SUMBER INFORMASI TUMBUH KEMBANG BALITA,” Visikes J. Kesehat. Masy., vol. 18, no. 2, 2020.

S. Rahmawati and D. Ratnawati, “PENGETAHUAN IBU TENTANG KARTU MENUJU SEHAT DAPAT MENSTIMULUS STATUS GIZI BALITA,” J. Ilm. Ilmu Keperawatan Indones., vol. 10, no. 03, pp. 59–64, 2020.

W. Ramadan, N. Chamidah, B. Zaman, L. Muniroh, and B. Lestari, “STANDARD GROWTH CHART OF WEIGHT FOR HEIGHT TO DETERMINE WASTING NUTRITIONAL STATUS IN EAST JAVA BASED ON SEMIPARAMETRIC LEAST SQUARE SPLINE ESTIMATOR,” in IOP Conference Series: Materials Science and Engineering, IOP Publishing, 2019, p. 52063.

K. Osaki, S. Kosen, E. Indriasih, K. Pritasari, and T. Hattori, “FACTORS AFFECTING THE UTILISATION OF MATERNAL, NEWBORN, AND CHILD HEALTH SERVICES IN INDONESIA: THE ROLE OF THE MATERNAL AND CHILD HEALTH HANDBOOK,” Public Health, vol. 129, no. 5, pp. 582–586, 2015.

N. Chamidah and M. Rifada, “LOCAL LINEAR ESTIMATOR IN BI-RESPONSE SEMIPARAMETRIC REGRESSION MODEL FOR ESTIMATING MEDIAN GROWTH CHARTS OF CHILDREN,” Far East J. Math. Sci., vol. 99, no. 8, pp. 1233–1244, 2016.

M. L. Alfiani, I. M. Nur, and T. W. Utami, “MODEL REGRESI NONPARAMETRIK BERDASARKAN ESTIMATOR POLINOMIAL LOKAL KERNEL PADA KASUS PERTUMBUHAN BALITA,” J. Stat. Univ. Muhammadiyah Semarang, vol. 2, no. 1, 2014.

N. Rochow et al., “Z-SCORE DIFFERENCES BASED ON CROSS-SECTIONAL GROWTH CHARTS DO NOT REFLECT THE GROWTH RATE OF VERY LOW BIRTH WEIGHT INFANTS,” PLoS One, vol. 14, no. 5, p. e0216048, 2019.

N. Chamidah, B. Lestari, A. Y. Wulandari, and L. Muniroh, “Z-SCORE STANDARD GROWTH CHART DESIGN OF TODDLER WEIGHT USING LEAST SQUARE SPLINE SEMIPARAMETRIC REGRESSION,” in AIP Conference Proceedings, AIP Publishing LLC, 2021, p. 60031.

N. Novina et al., “INDONESIAN NATIONAL GROWTH REFERENCE CHARTS BETTER REFLECT HEIGHT AND WEIGHT OF CHILDREN IN WEST JAVA, INDONESIA, THAN WHO CHILD GROWTH STANDARDS,” J. Clin. Res. Pediatr. Endocrinol., vol. 12, no. 4, p. 410, 2020.

P. G. Dwipoerwantoro, M. Mansyur, H. Oswari, M. Makrides, G. Cleghorn, and A. Firmansyah, “GROWTH OF INDONESIAN INFANTS COMPARED WITH WORLD HEALTH ORGANIZATION GROWTH STANDARDS,” J. Pediatr. Gastroenterol. Nutr., vol. 61, no. 2, p. 248, 2015.

A. Widiastuti and S. P. Winarso, “PROGRAM PMT DAN GRAFIK PERTUMBUHAN BALITA PADA MASA PANDEMI COVID,” J. Sains Kebidanan, vol. 3, no. 1, pp. 30–35, 2021.

D. E. Kusumawati, L. Latipa, and F. Hafid, “STATUS GIZI BADUTA DAN GRAFIK PERTUMBUHAN ANAK USIA 0-23 BULAN DI WILAYAH KERJA PUSKESMAS PANTOLOAN: NUTRITION STATUS OF CHILDREN UNDER TWO YEARS OF AGE AND GROWTH GRAPH OF CHILDREN AGE 0-23 MONTHS IN THE WORKING AREA PANTOLOAN CENTRAL OF HEALTH COMMUNITY,” Poltekita J. Ilmu Kesehat., vol. 14, no. 2, pp. 104–110, 2020.

A. H. Al Rahmad, I. Iskandar, T. K. Fadjri, and A. Hadi, “UTILIZATION OF THE GROWTH CHART MODULE IN INCREASING MOTHER’S KNOWLEDGE TO MONITOR THE GROW UP OF TODDLERS,” Kesmas Indones., vol. 14, no. 1, pp. 110–120, 2022.

A. Y. Kartini and D. Wulandari, “PENERAPAN MULTIVARIATE ADAPTIVE REGRESSION SPLINES UNTUK ANALISIS FAKTOR YANG MEMPENGARUHI KELAYAKAN NASABAH YANG MENGAJUKAN PEMBIAYAAN,” J. Lebesgue J. Ilm. Pendidik. Mat. Mat. dan Stat., vol. 4, no. 3, pp. 1439–1451, 2023.

A. Y. Kartini and N. Cahyani, “HYBRID K MEANS-MULTIVARIATE ADAPTIVE REGRESSION SPLINES FOR DISTRIBUTION OF DENGUE FEVER RISK MAPPING IN BOJONEGORO DISTRICT,” BAREKENG J. Ilmu Mat. dan Terap., vol. 17, no. 1, pp. 313–322, 2023.

D. A. Widyastuti, A. A. R. Fernandes, and H. Pramoedyo, “SPLINE ESTIMATION METHOD IN NONPARAMETRIC REGRESSION USING TRUNCATED SPLINE APPROACH,” in Journal of Physics: Conference Series, IOP Publishing, 2021, p. 12027.

N. Murbarani, Y. Swastika, A. Dwi, B. Aris, and N. Chamidah, “MODELING OF THE PERCENTAGE OF AIDS SUFFERERS IN EAST JAVA PROVINCE WITH NONPARAMETRIC REGRESSION APPROACH BASED ON SPLINE TRUNCATED ESTIMATOR,” Indones. J. Stat. Its Appl., vol. 3, no. 2, pp. 139–147, 2019.

A. Y. Kartini and M. Ishlahuddin, “MULTIVARIATE ADAPTIVE GENERALIZED POISSON REGRESSION SPLINES UNTUK PENGEMBANGAN MODEL PREDIKSI PRODUKSI PADI DI KABUPATEN BOJONEGORO,” J. Math. Educ. Sci., vol. 5, no. 2, pp. 147–156, 2022.

A. Y. K. Kartini and L. N. Ummah, “PEMODELAN KEJADIAN BALITA STUNTING DI KABUPATEN BOJONEGORO DENGAN METODE GEOGRAPHICALLY WEIGHTED REGRESSION DAN MULTIVARIATE ADAPTIVE REGRESSION SPLINES,” J Stat. J. Ilm. Teor. dan Apl. Stat., vol. 15, no. 1, 2022.

B. Lestari and I. N. Budiantara, “SPLINE ESTIMATOR AND ITS ASYMPTOTIC PROPERTIES IN MULTIRESPONSE NONPARAMETRIC REGRESSION MODEL,” Songklanakarin J. Sci. Technol., vol. 42, no. 3, pp. 533–548, 2020.

A. A. R. Fernandes, I. N. Budiantara, and B. W. Otok, “SPLINE ESTIMATOR FOR BI-RESPONSES AND MULTI-PREDICTORS NONPARAMETRIC REGRESSION MODEL IN CASE OF LONGITUDINAL DATA,” J. Math. Stat., vol. 11, no. 2, pp. 61–69, 2015.

A. Islamiyati and N. Chamidah, “PENALIZED SPLINE ESTIMATOR WITH MULTI SMOOTHING PARAMETERS IN BI-RESPONSE MULTI-PREDICTOR NONPARAMETRIC REGRESSION MODEL FOR LONGITUDINAL DATA.,” Songklanakarin J. Sci. Technol., vol. 42, no. 4, 2020.

W. Chen, M. Wan, J. Xu, J. Zhong, Y. Xia, and M. Zhang, “PENALIZED SPLINE ESTIMATION FOR NONPARAMETRIC MULTIPLICATIVE REGRESSION MODELS,” Open Access Libr. J., vol. 11, no. 4, pp. 1–16, 2024.

L. N. Berry and N. E. Helwig, “CROSS-VALIDATION, INFORMATION THEORY, OR MAXIMUM LIKELIHOOD? A COMPARISON OF TUNING METHODS FOR PENALIZED SPLINES,” Stats, vol. 4, no. 3, pp. 701–724, 2021.

N. Chamidah, B. Zaman, L. Muniroh, and B. Lestari, “DESIGNING LOCAL STANDARD GROWTH CHARTS OF CHILDREN IN EAST JAVA PROVINCE USING A LOCAL LINEAR ESTIMATOR,” Int. J. Innov. Creat. Chang., vol. 13, no. 1, pp. 45–67, 2020.

Y. Matdoan, “PEMODELAN MULTIVARIATE ADAPTIVE REGRESSION SPLINE (MARS) PADA FAKTOR-FAKTOR YANG MEMPENGARUHI KEMISKINAN DI PROVINSI MALUKU DAN MALUKU UTARA,” J Stat. J. Ilm. Teor. Dan Apl. Stat., vol. 13, no. 1, pp. 8–14, 2020.

R. Asriyanti, I. Yahya, B. Abapihi, G. N. A. Wibawa, and L. Laome, “PENERAPAN REGRESI NONPARAMETRIK SPLINE DALAM MEMODELKAN FAKTOR-FAKTOR YANG MEMPENGARUHI JUMLAH KASUS TUBERKULOSIS DI SULAWESI TENGGARA,” in Seminar Nasional Sains dan Terapan VI, 2022, pp. 100–109.

F. Y. Rumlawang, S. N. Aulele, and N. Kasim, “PENENTUAN MODEL REGRESI NONPARAMETRIK SPLINE PADA DATA PERTUMBUHAN BALITA DI DESA NANIA PROVINSI MALUKU TAHUN 2013-2014,” Barekeng J. Ilmu Mat. dan Terap., vol. 12, no. 1, pp. 27–32, 2018.

Y. Pertiwi, D. Permana, N. Amalita, and A. Salma, “MODELING HUMAN DEVELOPMENT INDEX IN PAPUA AND WEST SUMATERA WITH MULTIVARIATE ADAPTIVE REGRESSION SPLINE,” UNP J. Stat. Data Sci., vol. 1, no. 3, pp. 188–195, 2023.

R. M. Adnan, Z. Liang, S. Heddam, M. Zounemat-Kermani, O. Kisi, and B. Li, “LEAST SQUARE SUPPORT VECTOR MACHINE AND MULTIVARIATE ADAPTIVE REGRESSION SPLINES FOR STREAMFLOW PREDICTION IN MOUNTAINOUS BASIN USING HYDRO-METEOROLOGICAL DATA AS INPUTS,” J. Hydrol., vol. 586, p. 124371, 2020, doi: https://doi.org/10.1016/j.jhydrol.2019.124371.

Published
2025-04-01
How to Cite
[1]
A. Y. Kartini, J. R. Budiani, and M. Arifat, “THE DESIGN OF STANDARD GRAPH FOR TODDLER GROWTH USES NONPARAMETRIC PENALIZED SPLINE REGRESSION”, BAREKENG: J. Math. & App., vol. 19, no. 2, pp. 917-926, Apr. 2025.