Effectiveness of Decision Support System for Hydroponic Plant Nutrient Selection Using Apriori Algorithm Method

Abstract

Hydroponics is an agricultural system that uses water as its growing medium by adding nutrients to plants without using soil. In hydroponic cultivation, the thing that needs to be considered is the provision of an optimal dose of nutrient solution as a food source for plants. The provision of nutrients that are not in accordance with the needs of plants results in plants stopping growing, so that plants do not take care of each other. The type of nutrition commonly used in hydroponic plants is AB mix. However, the use of AB mix as a hydroponic nutrient also has disadvantages, namely synthetics and the price of AB mix nutrients are quite expensive. Therefore, alternative nutrients are needed that have the potential to be used as hydroponic nutrients. By analyzing hydroponic plant assessment data so that the rules of linkage between combinations of goods are found and form a pattern of itemset combinations with apriori algorithm. The association technique aims to find matching links in the database. From the results of data mining calculations using apriori algorithms, nutrient assessment data on hydroponic plants with the minimum support 20% and the minimum confidence 70%, formed five rules on hydroponic plant nutrition. One of the best rules is that AB mix nutrition is used on cucumber, spinach, celery, and kailan plants, so with 100% probability that POC nutrients will be good to also use on cucumber, spinach, celery, and kailan plants.