Rahardita Widyatra
Politeknik Elektronika Negeri Surabaya

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Smart Agriculture untuk Mewujudkan Ketahanan Pangan Berbasis Lora di Desa Kalipadang-Benjeng Gresik Norma Ningsih; Ida Anisah; I Gede Puja Astawa; Mochammad Zen Samsono Hadi; Prima Kristalina; Mike Yuliana; Aries Pratiarso; Haryadi Amran; Rahardita Widyatra; Amang Sudarsono; Mohamad Ridwan; Rini Satiti; Afifah Dwi Ramadhani
Jurnal Pengabdian Nasional (JPN) Indonesia Vol. 5 No. 1 (2024): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jpni.v5i1.648

Abstract

Increasing agricultural production is a top priority in agricultural development. There are many agricultural problems to be managed. One way to increase rice production is to pay attention to irrigation conditions. In addition to irrigation, rising temperatures also affect the process of flowering and grain filling. At high temperatures, grain because of rice agricultural production will calcify, resulting in a decrease in grain quantity and grain mass. Temperature spikes can also reduce the viability and size of the seeds when they reach the ripe stage. Apart from water and air, farmers also need to pay attention to soil pH and humidity. Many farmers do not yet have accurate indicators to determine soil quality, most farmers only use estimates, the application of the estimation method causes the quality of the soil in paddy fields to be infertile. To overcome this problem, a tool is made to predict the condition of agricultural land by taking data on temperature, humidity, air pressure, soil pH, soil moisture, and water flow rate. The data is then sent to a database to be displayed on a web server, so that farmers can monitor land conditions. It is expected that the parameter results obtained can be used as a preventive measure for farmers when conditions occur that can reduce rice productivity. That way, the condition of the land can be maintained so that crop failure can be minimized. This tool will be implemented in one of the rice fields of the residents of Kalipadang-Benjeng-Gresik Village. Based on data taken using an NPK sensor, wet soil has an average NPK content of 29.3 (Nitrogen); 41 (Phosphorus); 82 (Potassium). Moist soil has an NPK level of 28 (Nitrogen); 40 (Phosphorus); 82 (Potassium), and dry soil has an NPK level of 27.5 (Nitrogen); 39.7 (Phosphorus); 79.1 (Potassium). It can be said that soil moisture is directly proportional to NPK levels.