Swarga, Maharaja Agung (2025) Rancang Bangun Sistem Monitoring dan Kontrol Kelembapan, Suhu dan Kadar NPK (Nitrogen, Fosfor, Kalium) Pada Tanah Menggunakan ANFIS Terintegrasi Internet of Things. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Pertanian merupakan sektor penting dalam mendukung ketahanan pangan dunia. Namun, pengelolaan tanah yang tidak optimal sering menjadi kendala dalam meningkatkan hasil panen. Penelitian ini mengembangkan sistem monitoring dan kontrol tanah berbasis Internet of Things (IoT) yang terintegrasi dengan Adaptive Neuro-Fuzzy Inference System (ANFIS). Sistem ini dirancang untuk memantau kelembapan, suhu, dan kadar unsur hara tanah (nitrogen, fosfor, kalium/NPK) secara real-time serta mengendalikan irigasi dan pemupukan secara otomatis. Hasil pengujian menunjukkan bahwa sensor kelembapan mencatat presisi sebesar 97,69% dan akurasi 97,78%, sedangkan sensor suhu memiliki presisi 99,95% dan akurasi 98,69%. Sensor NPK mencapai presisi dan akurasi masing-masing lebih dari 97%. Nilai Root Mean Square Error (RMSE) untuk kelembapan dan suhu adalah 0,0001 dengan 1000 epochs, sementara RMSE untuk NPK adalah 0,006 dengan jumlah iterasi yang sama. Sistem kontrol berbasis ANFIS bekerja dengan sangat baik, menghasilkan respon yang stabil dengan waktu respons, waktu penyesuaian, dan tingkat kesalahan minimal. Teknologi ini menawarkan solusi inovatif untuk meningkatkan efisiensi pengelolaan sumber daya, mendukung pertanian presisi yang berkelanjutan, serta membantu petani meningkatkan produktivitas secara signifikan.
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Agriculture is a crucial sector in supporting global food security. However, suboptimal soil management often becomes an obstacle to improving crop yields. This research developed a soil monitoring and control system based on the Internet of Things (IoT) integrated with an Adaptive Neuro-Fuzzy Inference System (ANFIS). The system is designed to monitor soil moisture, temperature, and nutrient content (nitrogen, phosphorus, potassium/NPK) in real- time and to automatically control irrigation and fertilization. Test results showed that the moisture sensor recorded a precision of 97.69% and an accuracy of 97.78%, while the temperature sensor achieved a precision of 99.95% and an accuracy of 98.69%. The NPK sensor reached a precision and accuracy of more than 97% for nitrogen, phosphorus, and potassium. The Root Mean Square Error (RMSE) values for moisture and temperature were 0.0001 over 1000 epochs, while the RMSE for NPK was 0.006 with the same number of iterations. The ANFIS-based control system performed excellently, producing a stable response with minimal response time, adjustment time, and error rate. This technology offers an innovative solution to improve resource management efficiency, support sustainable precision agriculture, and significantly help farmers increase productivity.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Internet of Things (IoT), Adaptive Neuro – Fuzzy Inference System (ANFIS), Monitoring tanah, Sensor NPK, Kelembapan tanah |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) > TA1573 Detectors. Sensors T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1007 Electric power systems control |
| Divisions: | Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis |
| Depositing User: | Maharaja Agung Swarga |
| Date Deposited: | 01 Feb 2025 16:01 |
| Last Modified: | 01 Feb 2025 16:01 |
| URI: | http://repository.its.ac.id/id/eprint/117478 |
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