Prediction of Decreasing Agricultural Land based on Geographic Information System Case Study: Denpasar City
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10.5120/ijca2017913364 |
Ni Nyoman Supuwiningsih and Muhammad Rusli. Prediction of Decreasing Agricultural Land based on Geographic Information System Case Study: Denpasar City. International Journal of Computer Applications 162(9):30-34, March 2017. BibTeX
@article{10.5120/ijca2017913364,
author = {Ni Nyoman Supuwiningsih and Muhammad Rusli},
title = {Prediction of Decreasing Agricultural Land based on Geographic Information System Case Study: Denpasar City},
journal = {International Journal of Computer Applications},
issue_date = {March 2017},
volume = {162},
number = {9},
month = {Mar},
year = {2017},
issn = {0975-8887},
pages = {30-34},
numpages = {5},
url = {http://www.ijcaonline.org/archives/volume162/number9/27273-2017913364},
doi = {10.5120/ijca2017913364},
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
Abstract
Agricultural land in Denpasar city from year to year is always decreasing. Based on data from the years 2011-2014, agricultural land decreased significantly with percentage 58.6%. The decline in agricultural land affects agricultural output. The decrease in agricultural land caused by factor, namely the increase in population so that agricultural land is used as a housing or another functions. Seeing this phenomenon due to a lack of information to the public on the impact of agricultural land conversion. The narrow agricultural land in Denpasar will affect the balance of nature, the air will be more crowded and there will be global warming. Based on this analysis then necessary statistical forecasting using method prediction semi trend average which is implemented using the Geographical Information System with ArcView 3.3 as software and digital maps as result. Prediction with this mapping is used to predict the area of agricultural land that would come if the condition is still the same (data used in 2011-2014) so that the government and the general public can know the impact of land conversion and can think of solutions to tackle the agricultural land conversion.
References
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Keywords
Geographical Information System, digital maps, prediction, agricultural land.