SISTEM INFORMASI GEOGRAFIS PENENTUAN DAERAH POTENSI RAWAN PANGAN (STUDI KASUS: KABUPATEN PONTIANAK)

Authors

  • Yunitia Sari Universitas Tanjungpura

Keywords:

food, food insecurity, mapping, PCA, clustering, priorities.

Abstract

Food is a basic need for humans. The  more advanced a nation, the greater demands for  quality of the food they consume will be increase.  Nevertheless there are still many places where the  unmet  food evenly. Food insecurity could cause to  hunger, malnutrition and health problems, and worst  is death. Food insecurity can be seen in terms of  production, consumption and distribution.  Geographical mapping activities should be planned  and conducted to assist in determining priority areas  that potentially have food insecurity. This research  aims to map the areas of potential food insecurity in  the district of Pontianak and analyze the indicators  that have been defined, specifically the access roads,  the number of grocery stores, the amount of maternal  mortality, malnutrition, electricity, health facilities  and poor families. The analysis of composite  prioritization is done by using Principal Component  Analysis (PCA) and analysis of clusters (clustering).  Principal Component Analysis (PCA) is a method  used to construct a new variable which is a linear  combination of the original variables. To give the  accurate results, the variable will be reduced to create  a new variable called principal component.  Observation Cluster analysis is also used to perform  the analysis of existing patterns, classifying objects  into groups that have similar and classifying the  pattern.  This system can  help us to manage the  tabular data of indicator and displayed as maps and  generate reports in tabular form of potentially food-insecure areas.  The conclution of this research  represent the priority areas of food insecurity are  Wajo Hulu, Jungkat, Sei Nipah, Parit Bugis, Galang,  Peniraman, Sei Pinyuh, Sei Bakau Besar Laut, Pasir  Wan Salim, Penibung, Terusan and Sei Limau. Based  on the  questionnaire  testing,  the result  shows the  average respondent gives 50% percentage point of  the importance of this application.

References

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Published

2014-10-27

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Section

Articles