@article {10.3844/jcssp.2020.518.531,
article_type = {journal},
title = {A Fuzzy Decision Support Model for Cropland Recommendation of Food Cropping in Indonesia},
author = {Utama, Ditdit Nugeraha and Taufan, Alvali Zaqi and Hartzani, Al Ghifari and Haidi, Hasfhi and Lubis, Yusuf Ramadhan and Sardjono, Wahyu},
volume = {16},
number = {4},
year = {2020},
month = {Apr},
pages = {518-531},
doi = {10.3844/jcssp.2020.518.531},
url = {https://thescipub.com/abstract/jcssp.2020.518.531},
abstract = {Indonesia has an incredibly wide area for agriculture. The agriculture area in Indonesia has specific characteristic for each area (e.g., water capacity, land porosity, land height, etc.,). Furthermore, food crop is the most plant planted in Indonesia; rice, corn, red bean, green bean are some important food crops. The study aims to create a Decision Support Model based on fuzzy logic (FDSM). The model is able to recommend the most suitable food crop to be rationally planted in a specified area. The recommendation is based on distance value between plant and area characteristic value. Two main methods are operated in this study, they are fuzzy logic and Euclidean distance measurement. The method fuzzy logic purposely avoids the ambiguity of parameter value and considers the human linguistic based parameter value. Afterward, the Euclidean distance adopted to calculate the fitness value as a fundamental value for decision recommendation. Here, seven geographic parameters (i.e., water availability, temperature, humidity, land height, land slope, rainfall and land porosity) matched to food crop’s biotic parameters in finding the fittest value. Finally, the model shows a simulation of recommendation for 514 administrative areas of 34 provinces’ district/municipality (in Indonesia) based on five types of food crops (i.e., rice, maize, soybeans, green beans and peanuts).},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}