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Red onion plants using hydroponic method is a method performed by cultivating plants using water, nutrients, and oxygen with no soil required. Hydroponics method is an alternative solution to grow onions in limited soil. The changes in air temperature, bright light, plant temperature and humidity greatly affect hydroponic growth. Red onion plants using hydroponic planting medium is a method performed by cultivating plants using water, nutrients, and oxygen with no soil required. Hydroponics method is an alternative solution to grow onions in the limited land. The changes in air temperature, bright light, plant temperature and humidity greatly affect hydroponic growth. The difficulty of knowing the environmental conditions of hydroponic planting media, often makes the hydroponic farmers fail in the middle of the process of plant growth. This monitoring system uses water temperature sensor, air temperature sensor, Light Sensor, GSM SIM800L, LM2596Relay module and Arduino Uno as a microcontroller. The result of tests conducted for eight weeks on the onion environment monitoring by taking into account the water temperature, humidity, air temperature, and light intensity. The leaves amount and height acquired from the test is 12 leaves with 29 cm of height.

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Mangrove plants are one of the plants that really help aquatic ecosystems between the sea, coast, and land. Mangrove plants provide many ecological, social, and economic benefits. In Indonesia, mangrove plants have 202 species with the same anatomy as other plants in general, consisting of roots, fruits, stems and leaves. Nowadays, the location of mangrove plants in Indonesia has experienced the fastest damage in the world due to conversion to ponds, settlements, industry and plantations. One of the efforts to restore aesthetic value and restore the ecological function of mangrove forest areas is rehabilitation using mangrove fruit. In the rehabilitation process, farmers generally use the manual method with the naked eye to determine fruit ripeness on mangrove plants, so the resulting level of accuracy is not optimal. To overcome this problem, an application is needed that can facilitate farmers in determining fruit maturity in mangrove plants so that it can help determine the maturity level of mangrove fruit. The development of this application utilizes the Deep Learning method as well as the utilization of digital image processing techniques with Grayscaling, Adaptive Threshold, Sharpening and Smoothing techniques. The results of this study are an application that can detect the level of fruit maturity in mangrove plants with an accuracy of 99.11%. With this application, determining the maturity level of fruit on mangrove plants can be easily done.