Pengembangan Solusi Deteksi Area Stres Tanaman Padi Menggunakan Drone Dan Sistem Pendukung Keputusan Berbasis Kecerdasan Buatan

Mukminin, Muhammad Amirul (2026) Pengembangan Solusi Deteksi Area Stres Tanaman Padi Menggunakan Drone Dan Sistem Pendukung Keputusan Berbasis Kecerdasan Buatan. Masters thesis, Institute Technology Sepuluh November.

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Abstract

Pemantauan stres tanaman padi berperan penting dalam mendukung pengelolaan lahan pertanian berbasis area, namun pada praktiknya masih banyak bergantung pada metode manual. Metode manual memiliki keterbatasan dari sisi cakupan area, efisiensi waktu. Seiring berkembangnya teknologi pertanian digital, diperlukan solusi teknologi yang mampu mendukung pemantauan area stres tanaman padi secara lebih efisien, efektif, mudah digunakan, dan layak dioperasionalkan dibandingkan metode manual. Penelitian ini bertujuan untuk menjawab solusi teknologi apa yang dapat menjawab kebutuhan tersebut dalam konteks pertanian padi di Indonesia. Untuk mencapai tujuan tersebut, penelitian ini menggunakan pendekatan Design Science Research (DSR) dengan mengembangkan dan mengevaluasi solusi pemantauan berbasis Unmanned Aerial Vehicle (UAV) yang memanfaatkan data citra sensor RGB dan thermal, serta sistem pendukung keputusan (Decision Support System) berbasis kecerdasan buatan. Evaluasi solusi dilakukan berdasarkan aspek usability, efektivitas, efisiensi, dan kelayakan operasional. Hasil evaluasi menunjukkan bahwa solusi yang dikembangkan memperoleh skor System Usability Scale (SUS) sebesar 79 yang berada pada kategori Good, serta nilai efektivitas rata-rata sebesar 4,73 pada skala 1–5. Dari sisi efisiensi, solusi ini mampu mengurangi ketergantungan pada inspeksi manual dan meningkatkan efisiensi waktu serta tenaga dalam pemantauan lapangan. Sementara itu, hasil analisis cost–benefit menunjukkan bahwa solusi dinilai layak diterapkan pada skema penggunaan tertentu, khususnya secara kolektif, dibandingkan penerapan pada skala individu dengan luasan lahan kecil.
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Rice crop stress monitoring plays an important role in supporting area-based agricultural land management, however in practice, it still largely relies on manual methods. Manual monitoring has limitations in terms of area coverage and time efficiency. With the advancement of digital agricultural technologies, there is a need for technological solutions that can support rice crop stress area monitoring in a more efficient, effective, user-friendly, and operationally feasible manner compared to conventional manual methods. This study aims to address the question of which technological solution can meet these needs within the context of rice farming in Indonesia. To achieve this objective, this research adopts a Design Science Research (DSR) approach by developing and evaluating a UAV-based monitoring solution that utilizes RGB and thermal imagery data, integrated with an artificial intelligence–based Decision Support System (DSS). The solution is evaluated based on usability, effectiveness, efficiency, and operational feasibility. The evaluation results indicate that the developed solution achieved a System Usability Scale (SUS) score of 79, classified as Good, and an average effectiveness score of 4.73 on a 1–5 scale. In terms of efficiency, the solution reduces reliance on manual field inspections and improves time and labor efficiency in field monitoring activities. Furthermore, the cost–benefit analysis shows that the solution is feasible

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Sistem Pendukung Keputusan, Drone, Pemantauan Stres Tanaman Padi, UAV, Design Science Research, Desain Solusi,Decision Support System, Drone, Rice Crop Stress Monitoring, UAV, Design Science Research, Design Solution.
Subjects:	T Technology > T Technology (General) > T58.62 Decision support systems
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information System > 59101-(S2) Master Thesis
Depositing User:	Muhammad Amirul Mukminin
Date Deposited:	30 Jan 2026 07:07
Last Modified:	30 Jan 2026 07:08
URI:	http://repository.its.ac.id/id/eprint/131262

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