Widhiwoso, Satrio Kamil (2024) Prototipe Sistem Irigasi Cerdas Berdasarkan Crop Water Stress Index dan Weather Forecasting Berbasis Internet of Things. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Pertanian merupakan salah satu sektor utama di negeri ini, dan salah satu faktor penting yang mempengaruhi suksesnya pertanian adalah irigasi. Penelitian ini bertujuan untuk mengembangkan sistem irigasi tanaman cerdas berbasis Internet of Things (IoT) dengan memanfaatkan crop water stress index (CWSI) dan kelembapan tanah. Metode ini dirancang untuk meningkatkan efisiensi penggunaan sumber daya manusia dan air dalam pertanian. Penelitian ini menggunakan sensor kelembapan udara, kelembapan tanah, termometer inframerah, dan suhu udara sebagai input untuk menghitung CWSI, yang merupakan indikator kritis tingkat kekeringan tanaman. Untuk menghindari kelebihan air pada tanaman yang disebabkan oleh hujan, ditambahkan satu indikator penentu dalam sistem irigasi ini yaitu weather forecasting. Penggunaan weather forecasting memungkinkan sistem untuk memproyeksikan kebutuhan air tanaman dalam jangka waktu tertentu. Ketika nilai CWSI melampaui batas yang ditentukan, sistem secara otomatis memicu pengiriman air irigasi ke area yang membutuhkan. Penelitian ini juga membandingkan efektifitas irigasi otomatis berdasarkan CWSI, kelembapan tanah, dan weather forecasting dengan irigasi secara manual yang dilakukan dengan interval tetap pada tanaman selada. Hasil penelitian menunjukkan bahwa irigasi otomatis 68% lebih efektif dalam menjaga kelembapan tanah optimal pada tanaman selada yang memiliki kelembapan tanah optimal 65% - 75%. Selain itu, irigasi otomatis juga berhasil mengungguili irigasi manual dalam penjagaan CWSI di batas rendah sebanyak 33%. Dari data tersebut, dapat disimpulkan bahwa irigasi tanaman otomatis berdasarkan CWSI, kelembapan tanah, dan weather forecasting lebih baik dalam menjaga kelembapan tanah dan CWSI optimal jika dibandingkan dengan irigasi manual.
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Agriculture is one of the main sectors in Indonesia, and one of the critical determining factors of agriculture is irrigation. This research aims to develop a smart plant irrigation system based on the Internet of Things (IoT) utilizing the Crop Water Stress Index (CWSI) and soil moisture. This method is designed to increase the efficiency of human and water resource use in agriculture. This study utilizes air humidity sensors, soil moisture sensors, infrared thermometers, and air temperature as inputs to calculate CWSI, which is a critical indicator of plant drought levels. To avoid overwatering plants due to rain, weather forecasting is included as a determining indicator in this irrigation system. The use of weather forecasting allows the system to project plant water needs over a specific period. When the CWSI value exceeds the determined threshold, the system automatically triggers the delivery of irrigation water to the needed area. This research also compares the effectiveness of automatic irrigation based on CWSI, soil moisture, and weather forecasting with manual irrigation performed at fixed intervals on lettuce plants. The results show that automatic irrigation is 68% more effective in maintaining optimal soil moisture in lettuce plants, which have an optimal soil moisture range of 65% - 75%. Additionally, automatic irrigation also outperformed manual irrigation in maintaining CWSI at the lower limit by 33%. From this data, it can be concluded that automatic plant irrigation based on CWSI, soil moisture, and weather forecasting is better at maintaining optimal soil moisture and CWSI compared to manual irrigation.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Crop Water Stress Index (CWSI), Internet of Things (IoT), Irigasi, Weather Forecasting |
| Subjects: | S Agriculture > S Agriculture (General) T Technology > T Technology (General) > T174 Technological forecasting T Technology > T Technology (General) > T385 Visualization--Technique T Technology > TD Environmental technology. Sanitary engineering > TD433 Water treatment plants T Technology > TD Environmental technology. Sanitary engineering > TD481 Water distribution systems T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3070 Automatic control |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information Technology > 59201-(S1) Undergraduate Thesis |
| Depositing User: | Satrio Kamil Widhiwoso |
| Date Deposited: | 25 Jul 2024 05:25 |
| Last Modified: | 25 Jul 2024 05:25 |
| URI: | http://repository.its.ac.id/id/eprint/108849 |
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