Pemodelan Faktor-faktor yang Mempengaruhi Balita Gizi Buruk di Provinsi Jawa Barat Tahun 2017 dengan Pendekatan Spatial Autoregressive Model (SAR)

Ambarwati, Retno; Hastono, Sutanto Priyo

doi:10.33221/jikm.v9i02.507

Cited by 3 publications

(3 citation statements)

References 2 publications

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“…Nutritional status is included in the important factor in assessing the growth and development rate of babies and toddlers [4]. Nutritional problems (Malnutrition), have adverse effects on the health conditions of infants, toddlers, and women of productive age, because they are caused by several factors including food availability, infectious diseases, lack of knowledge about parenting, difficulty in accessing environmental health, healthy living behaviors, the environment, and poverty [2].…”

Section: Introductionmentioning

confidence: 99%

Implementation of Naïve bayes Method for Predictor Prevalence Level for Malnutrition Toddlers in Magelang City

Arumi

Subrata

Rahmawati

2023

J. RESTI (Rekayasa Sist. Teknol. Inf.)

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Nutritional status is an important factor in assessing the growth and development rate of babies and toddlers. Cases of malnutrition are increasing, especially in magelang city. Because nutritional problems (Malnutrition) can affect the health of toddlers. Therefore, this study aims to predict the level of prevalence of malnutrition with the Naïve Bayes method. This research uses an observational design, a single center study at the Magelang City Office, using the Naïve bayes method which is used as an application of time series data, and is most widely used for prediction, especially in data sets that have many categorical or nominal type attributes. The Naïve bayes method is used to predict such cases of malnutrition. The results of this study show that the Naïve Bayes method succeeded in predicting the magnitude of cases of malnourished toddlers in Magelang City with an accuracy percentage of 75% due to the very minimal amount of training data, and the areas that have the most malnutrition are in three areas, namely Magersari, North Tidar and Panjang.

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Section: Introductionmentioning

confidence: 99%

Implementation of Naïve bayes Method for Predictor Prevalence Level for Malnutrition Toddlers in Magelang City

Arumi

Subrata

Rahmawati

2023

J. RESTI (Rekayasa Sist. Teknol. Inf.)

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“…Stunting is a condition where children fail to grow due to chronic malnutrition over an extended period, especially during the first 1.000 days of a child's life [1]. This condition is caused by various factors, including nutritional factors such as poor nutritional status in pregnant women and inadequate nutritional intake in children; environmental factors such as poor sanitation, lack of access to clean water, and limited health service accessibility; and social factors like the level of education and the low socioeconomic status of families [2,3].…”

Section: Introductionmentioning

confidence: 99%

Unlocking potential of data: A localized data-driven approach for stunting reduction in South Kalimantan Province

Rizkiah

2023

icdsos

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This study addresses the issue of stunting in South Kalimantan Province, where high stunting prevalence rates persist. Through a comprehensive analysis of factors influencing stunting prevalence, predictive modeling using machine learning, and clustering analysis of districts based on stunting rates, the research aims to support the provincial government in formulating effective and sustainable strategies. The findings highlight influential factors such as HDI, poverty rates, immunization coverage, breasfed babies, number of uninhabitable houses, and access to clean water. The study also utilise machine learning to build model that aids in predicting future stunting prevalence, while clustering analysis categorizes districts into distinct groups. These insights guide the government in prioritizing interventions, setting prevalence targets, and determining strategic areas for stunting reduction efforts.

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“…Based on Nutritional Status Monitoring (PSG) data organized by the Ministry of Health in 2017, West Java has a malnourished toddler rate of 2.9%. (Ambarwati & Hastono, 2020). Bogor Regency is one of the districts that is a priority for malnutrition interventions in West Java.…”

Section: Introductionmentioning

confidence: 99%

Health Education On Balanced Nutrition in Toddlers in Teluk Pinang Village

Yusnia

Putri

2022

Journal of Community Service

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Introduction: Knowledge of balanced nutrition in toddlers in Indonesia is still relatively low. Of the 37.2% of toddlers in Indonesia, only 13.0% experienced malnutrition status based on age and 2.5% who experienced thinness based on weight compared to height. This means that there are only 13.0% and 2.5% of children under five who have been malnourished from a long time until now, low balanced nutrition knowledge has resulted in Indonesia still facing nutritional problems in toddlers such as malnutrition. Purpose: To determine the effect of "balanced nutrition" education on maternal knowledge in fulfilling "balanced nutrition" in toddlers in Teluk Pinang Village. Method: The method carried out is the lecture method, in this community service, the speaker team provides understanding to 22 mothers who have toddlers. Results: The results of statistical test calculations obtained a t value of 6,953 and p = 0.000 (p<001), meaning that there is an influence of balanced nutrition education for toddlers. From the results obtained from the pre-test and post-test, it shows an increase in participants' understanding from an average pre-test value of 60 to an average post test value of 75. Conclusion: This "balanced nutrition" education can be influenced on mothers who have toddlers, especially for mothers who are poorly educated and relatively young to be able to increase knowledge in meeting the nutrition of toddlers in Teluk Pinang Village.

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Pemodelan Faktor-faktor yang Mempengaruhi Balita Gizi Buruk di Provinsi Jawa Barat Tahun 2017 dengan Pendekatan Spatial Autoregressive Model (SAR)

Cited by 3 publications

References 2 publications

Implementation of Naïve bayes Method for Predictor Prevalence Level for Malnutrition Toddlers in Magelang City

Implementation of Naïve bayes Method for Predictor Prevalence Level for Malnutrition Toddlers in Magelang City

Unlocking potential of data: A localized data-driven approach for stunting reduction in South Kalimantan Province

Health Education On Balanced Nutrition in Toddlers in Teluk Pinang Village

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