Digital mapping of relevant food insecurity information among post flood victim at Bera district, Pahang, Malaysia / Siti Salwani Musa

Flood is one of the natural phenomenon that have high potential to cause damage in terms of loss of lives, destruction to property and economic loss. This cross sectional study conducted by using convenience sampling method. The objective of this study is to demonstrate and illustrate the factors af...

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Main Author: Musa, Siti Salwani
Format: Thesis
Language:English
Published: 2016
Subjects:
Online Access:http://ir.uitm.edu.my/id/eprint/27918/
http://ir.uitm.edu.my/id/eprint/27918/1/TD_SITI%20SALWANI%20MUSA%20HS%2016_5.pdf
id uitm-27918
recordtype eprints
spelling uitm-279182020-01-30T03:12:31Z http://ir.uitm.edu.my/id/eprint/27918/ Digital mapping of relevant food insecurity information among post flood victim at Bera district, Pahang, Malaysia / Siti Salwani Musa Musa, Siti Salwani Computer applications to medicine. Medical informatics Neural Networks (Computer). Artificial intelligence Public health. Hygiene. Preventive Medicine Flood is one of the natural phenomenon that have high potential to cause damage in terms of loss of lives, destruction to property and economic loss. This cross sectional study conducted by using convenience sampling method. The objective of this study is to demonstrate and illustrate the factors affecting food insecurity among the flood victims at Bera, Malaysia on the digital mapping by using the Geographic Information System (GIS) as the study on the factors of food insecurity and the illustration of the factors through the digital mapping is limited. The combination of questionnaire from the Household Food Security Survey Model (HFSSM), Household Food Insecurity Access Field (HFIAS), and anthropometric assessment with some modification were used in this study. There were 210 of respondents out of 247 respondents were agree .to be interviewed. Chi square and logistic regression were utilized to know the factors that associated with household food insecurity. The results show that the percentage of the household with food insecure was 29.6% (n=73) according to HFSSM. Thirteen out of seventeen villages have been identified as food insecure in which the three highest food insecure were Kampung Padang Luas (50%), Kampung Kuala Triang (53.8%), and Kampung Bohor Bharu (53.3%). This paper highlight on the factors of food insecurity and on how the GIS application help to demonstrate and visualize the area of food insecurity at Bera, Malaysia. 2016-01 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/27918/1/TD_SITI%20SALWANI%20MUSA%20HS%2016_5.pdf Musa, Siti Salwani (2016) Digital mapping of relevant food insecurity information among post flood victim at Bera district, Pahang, Malaysia / Siti Salwani Musa. Degree thesis, Universiti Teknologi MARA.
repository_type Digital Repository
institution_category Local University
institution Universiti Teknologi MARA
building UiTM Institutional Repository
collection Online Access
language English
topic Computer applications to medicine. Medical informatics
Neural Networks (Computer). Artificial intelligence
Public health. Hygiene. Preventive Medicine
spellingShingle Computer applications to medicine. Medical informatics
Neural Networks (Computer). Artificial intelligence
Public health. Hygiene. Preventive Medicine
Musa, Siti Salwani
Digital mapping of relevant food insecurity information among post flood victim at Bera district, Pahang, Malaysia / Siti Salwani Musa
description Flood is one of the natural phenomenon that have high potential to cause damage in terms of loss of lives, destruction to property and economic loss. This cross sectional study conducted by using convenience sampling method. The objective of this study is to demonstrate and illustrate the factors affecting food insecurity among the flood victims at Bera, Malaysia on the digital mapping by using the Geographic Information System (GIS) as the study on the factors of food insecurity and the illustration of the factors through the digital mapping is limited. The combination of questionnaire from the Household Food Security Survey Model (HFSSM), Household Food Insecurity Access Field (HFIAS), and anthropometric assessment with some modification were used in this study. There were 210 of respondents out of 247 respondents were agree .to be interviewed. Chi square and logistic regression were utilized to know the factors that associated with household food insecurity. The results show that the percentage of the household with food insecure was 29.6% (n=73) according to HFSSM. Thirteen out of seventeen villages have been identified as food insecure in which the three highest food insecure were Kampung Padang Luas (50%), Kampung Kuala Triang (53.8%), and Kampung Bohor Bharu (53.3%). This paper highlight on the factors of food insecurity and on how the GIS application help to demonstrate and visualize the area of food insecurity at Bera, Malaysia.
format Thesis
author Musa, Siti Salwani
author_facet Musa, Siti Salwani
author_sort Musa, Siti Salwani
title Digital mapping of relevant food insecurity information among post flood victim at Bera district, Pahang, Malaysia / Siti Salwani Musa
title_short Digital mapping of relevant food insecurity information among post flood victim at Bera district, Pahang, Malaysia / Siti Salwani Musa
title_full Digital mapping of relevant food insecurity information among post flood victim at Bera district, Pahang, Malaysia / Siti Salwani Musa
title_fullStr Digital mapping of relevant food insecurity information among post flood victim at Bera district, Pahang, Malaysia / Siti Salwani Musa
title_full_unstemmed Digital mapping of relevant food insecurity information among post flood victim at Bera district, Pahang, Malaysia / Siti Salwani Musa
title_sort digital mapping of relevant food insecurity information among post flood victim at bera district, pahang, malaysia / siti salwani musa
publishDate 2016
url http://ir.uitm.edu.my/id/eprint/27918/
http://ir.uitm.edu.my/id/eprint/27918/1/TD_SITI%20SALWANI%20MUSA%20HS%2016_5.pdf
first_indexed 2023-09-18T23:19:15Z
last_indexed 2023-09-18T23:19:15Z
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