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Literature study of stunting supplementation in Indonesian utilizing text mining approach by Digdo Sudigyo; Alam Ahmad Hidayat; Rudi Nirwantono; Reza Rahutomo; Joko Pebrianto Trinugroho; Bens Pardamean is a Computer Science article available to read on EtoBox.

What is Literature study of stunting supplementation in Indonesian utilizing text mining approach about?

Numerous research on stunting supplementation interventions in Indonesia have been published. The information can be extracted through data mining, especially from academic research databases. In this paper, we presented a text mining-based literature review strategy to create a pipeline that researchers can use to accelerate the development of stunting supplementation intervention research in Indonesia. Utilizing various NLP (Natural Language Processing) techniques, data were crawled, processed, and visualized using Python. The crawling dataset used a module from the Pubmed API (Application Programming Interface) to collect literature papers. The NLTK (Natural Language Toolkit) module and itertools were used to process text data. The n-grams model was applied to process tokens into bigrams and trigrams. Text information was visualized using Matplotlib and Word cloud packages. There is an increasing number of publication in stunting supplementation intervention according to our result, which was observed from 2015 to 2021. West Java was the province where most of the stunting research has been conducted, as determined by research abstracts. Top occurrences obtained from the bigram

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Author

Digdo Sudigyo; Alam Ahmad Hidayat; Rudi Nirwantono; Reza Rahutomo; Joko Pebrianto Trinugroho; Bens Pardamean

Publisher

Elsevier BV

Published

2023

Language

EN

Field

Computer Science (Physical Sciences)