IMPLEMENTASI METODE K-MEANS UNTUK KLASTERISASI LAHAN PERTANIAN STRAWBERRY DI DAERAH SUBANG BERBASIS IoT(INTERNET OF THINGS)



Abstract
The level of acidity, humidity, and air temperature on the soil has a major effect on the growth of strawberry plants, therefore a tool is needed to see the level of acidity, soil moisture plus air temperature and a clustering system for agricultural land suitable for strawberry plants so that it can be used as a reference in any area. Which is suitable for planting strawberries on agricultural land of farmers in the Subang area.
The data placed by the system is obtained from direct research into the field and soil sampling to each area point determined by the author with various considerations ranging from the type of land, temperature, and level of soil dryness, the data obtained is the result of sensors implanted into the microcontroller. and connected via a hotspot network from a smartphone which then uses the k-means clustering algorithm so that it can be inputted into the database using the node-red platform. The data that has been entered into the database can be directly / calculated using the k-means method that the author has embedded in the system, and the final result of this system is that we can see the clustering results of the data that has been placed by the system into 3 clusters and the author uses 2 boards microcontroller and 3 sensors, for the microcontroller board the author uses Arduino UNO and Node MCU ESP8266, for the sensor the author uses a soil moisture sensor (soil moisture) from China, a pH probe/soil pH sensor, and a local product temperature sensor (DHT11) from Indonesia.
The system built produces a cluster of agricultural areas suitable for the cultivation of strawberry plants.
Keywords: Internet of Things (IoT), K-Means Clustering, Node-RedCITATIONS
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