Insight and Foresight: Mortality Trends Due to Malnutrition

Malnutrition remains a significant global health problem, linked to a substantial proportion of child deaths worldwide. According to the United Nations, malnutrition is responsible for 45% of deaths in children under five. The World Food Programme estimates that over 820 million people globally suffer from hunger, with malnutrition playing a crucial role in this crisis. This study uses Python for data analysis and visualization, integrating time-series analysis and deep learning to forecast global malnutrition trends. The system processes data from 1970 to 2022, normalizes it, and trains a model comprising Conv1D and LSTM layers. The predictions are visualized using Plotly and displayed in a Flask web application, offering interactive features for exploring the data. The results highlight a notable decline in malnutrition-related deaths in both developing and developed nations, reflecting the success of previous interventions. However, developing countries continue to report a higher number of diseases and conditions associated with malnutrition, underscoring the need for further targeted interventions.

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Publication Details

Journal
Jurnal Aplikasi dan Teori Ilmu Komputer
Published
2024-12-24
DOI
https://doi.org/10.17509/jatikom.v7i2.72389
Primary Topic
Nutrition and Health in Aging
Type
article
Field-Weighted Citation Impact
0.00
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article

Insight and Foresight: Mortality Trends Due to Malnutrition

Muslimah Yusof, M Haq, Ihsan Ghozi Zulfikar, Rhisma Syahrul Putra et al.
Jurnal Aplikasi dan Teori Ilmu Komputer
Nutrition and Health in Aging
article

Insight and Foresight: Mortality Trends Due to Malnutrition

Muslimah Yusof, M Haq, Ihsan Ghozi Zulfikar, Rhisma Syahrul Putra, Arianti Apriani Sagita, Della Rachmatika Noer Intanty
article en

Abstract

Malnutrition remains a significant global health problem, linked to a substantial proportion of child deaths worldwide. According to the United Nations, malnutrition is responsible for 45% of deaths in children under five. The World Food Programme estimates that over 820 million people globally suffer from hunger, with malnutrition playing a crucial role in this crisis. This study uses Python for data analysis and visualization, integrating time-series analysis and deep learning to forecast global malnutrition trends. The system processes data from 1970 to 2022, normalizes it, and trains a model comprising Conv1D and LSTM layers. The predictions are visualized using Plotly and displayed in a Flask web application, offering interactive features for exploring the data. The results highlight a notable decline in malnutrition-related deaths in both developing and developed nations, reflecting the success of previous interventions. However, developing countries continue to report a higher number of diseases and conditions associated with malnutrition, underscoring the need for further targeted interventions.

Jurnal Aplikasi dan Teori Ilmu KomputerVol. 7(2)
Indonesia University of Education (ID), Universiti Teknologi MARA (MY)
Openalex Percentile: Top 64%
Nutrition and Health in Aging
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