Decision support system to determine hydroponic vegetable cultivation based on Internet of Things (IoT)

Abstract

Currently, hydroponic vegetables have become a trend because of its efficient construction requires a minimum resource management. Determining the correct type of hydroponic vegetable before planting would affect the yield of the vegetables produced. However, the experiments conducted in this research resulted in deadlocks to determine the exact type of vegetable cultivated at the farm where the type of hydroponic vegetable depends on several factors that affect the quality and quantity, size weights, the number of leaves and the weight of plants. A decision support system is applied as a solution to the problem and IoT is performed to gain criteria data input. AHP method is conducted to measure criteria such as raw water PH, PPM of a nutritional solution, air temperature and sunlight illumination intensity and to find alternatives determined namely, lettuce, Pakcoy, Mustard greens, Spinach, Kale, Celery, and Chinese Kale. Results showed that Pakcoy in the first rank with a value of 0.25% and the second is spinach with a value of 0.16%, the Decision support system has proven to determine the type of vegetable on hydroponic vegetables.