The agribusiness sector is the largest economic sector and the most important part of the Indonesian national economy, but the agribusiness sector begins to experience threats in fulfilling human food. Fulfillment of food faced some challenges including an increase in population, which means rising food, urbanization resulting in a decrease in the number of farmers and dietary changes, limited resources (land and air), changes to facilitate and waste food. This corresponds to the data issued by the United Nations, which is the fulfillment of food from approximately 9.6 billion people in the world in 2050 [2]. Along with that, the agricultural land area also decreased due to the transfer of agricultural land function. Farmbot can increase agricultural production to solve human food because it can manage crops within 24 hours without stopping. Farmbot is liquid of agricultural robots that can plant seeds with regular, watering plants and monitoring plant growth. Farmbot can be controlled through an application interface that allows remote access from any location in easy Internet-connected devices. In this study, it will create an automation system that can plant seeds, watering agricultural crops by controlling air production, monitoring plant conditions, plant databases by using applications and designing algorithms to detect crops. Besides, other ways can measure the moisture of the soil to scheduling watering as a watering parameter. To implement this feature can work using a robotic hand with a CNC (Computer Numeric Control) gesture system that would be controlled by the Arduino and Raspberry PI. Following are the procedures for implementing agricultural automation with IoT applications (Internet of Things), seedlings with the help of seeders that stored in plant databases, watering and direct monitoring by users who use camera help.

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Indonesia ceramic tiles production is currently ranked between the fifth and sixth of the world, it shows that ceramic tiles is one of the largest commodities in Indonesia. So, ceramic quality becomes very important to be considered for it is used as one of the basic building materials. The existing ceramic testing system in Balai Besar Keramik is performed by the operator repeatedly. With the repetitive performances, they cause fatigue to operator that results in decreased work ability, so in the calibration and readings of measuring instruments an error occurs. To improve the accuracy level of quality control system to remain stable, it's necessary to create an intelligent device that can overcome errors that occur in the inspection process using human vision on the surfaces of defect detection of ceramic tiles that have a high level of system stability; therefore, it is required the automation system design of the image processing-based using Artificial Neural Network method with backpropagation algorithm. The process of system design is using automation design with 300 Lx light intensity, 50 cm of camera distance, based on Artificial Neural Network method with confusion matrix result obtaining accuracy rate of 96.9% for offline mode and 92.3% for realtime mode.

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