DECISION SUPPORT SYSTEM FOR SUGARCANE SEED SELECTION – A CASE STUDY: KAMPHAENGPHET

Abstract

At the present day, the production of sugar industry in Thailand becomes more advanced than the past. However, it is not without its problems. The high cost of cultivation and low growth and yields are two major problems confronting this important rural industry. Hence, the cultivation of sugarcane should be considered as a significant matter in order to reduce the cost. Sugarcane variety selection should be a process that may help in reducing the cultivation cost and increase yields. Matching the right sugarcane varieties for the right area can reduce costs of fertilizer, insect and pest control, and weeds. The purpose of this research was selecting the appropriate Multi-Criteria Decision Making (MCDM) technique for selecting  sugarcane varieties and implementing the decision support system of sugarcane variety selection via Web GIS (Geographic Information System). The study area is Kamphaengphet. According to the consideration of the spatial data and data of sugarcane, there are five criterias: suitability of plantation area, suitability of water resources, weight per rai, Commercial Cane Sugar (CCS) and the rotation of the sugarcane crop.  Based on these criterias, spatial data of Kamphaengphet and data of sugarcane seed were analysed by using three MCDM techniques: Analysis Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Simple Additive Weighting (SAW). Result showed that AHP is the most appropriate technique for sugarcane variety selection. The consistency ratio (CR) of all criterias were less than 10%. It means all criterias is acceptable. Then a web application for sugarcane varieties selection was developed based on AHP. There were 2 parts of user: general and specialist. General user can search sugarcane variety that suitable for particular area. Specialist can add, edit and delete information to the system. The decision support system for sugarcane varieties selection can recommend sugarcane varieties that suitable for growing areas to general user accurately.