English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The issue of food security is closely linked to the self-sufficiency program proclaimed. Government has conducted food security and vulnerability mapping detailing up to the kelurahan and kecamatan. The food security atlas classifies districts based on food security priorities. The priority of food security becomes information to support the decision-making process. Classification process can also be done with one method of data mining i.e. Artificial Neural Network (ANN). ANN is one of the classification methods that enable the network to learn from training dataset. In this research ANN use to classify district priorities on food security so can be known which districts are experiencing food vulnerability before turning into food-insecure districts. The dataset used is the resistance and vulnerability of West Papua Province. Output classification of ANN compared with real data with result Spearman correlation value  0.9375 which shows that the ANN method can classify the priority of food security and food vulnerability by using 10 indicators.

KLASIFIKASI PRIORITAS DISTRIK TERHADAP KETAHANAN PANGAN MENGGUNAKAN METODE JARINGAN SYARAF TIRUAN