Rahman, Yusril (2026) Pengembangan Model Adopsi Drone untuk Smart Farming pada Petani Padi: Studi Kualitatif Berbasis Decomposed Theory of Planned Behavior (DTPB) dengan Dukungan EEG Neurofeedback. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Teknologi drone atau Unmanned Aerial Vehicle (UAV) memiliki potensi untuk mendukung penerapan smart farming melalui kegiatan penyemprotan, pemupukan, pemantauan lahan, serta peningkatan efektivitas dan efisiensi pekerjaan pertanian. Namun, penerapan teknologi tersebut pada petani padi tidak hanya bergantung pada manfaat teknis, tetapi juga berkaitan dengan pertimbangan personal, sosial, kelembagaan, ekonomi, dan operasional. Penelitian ini bertujuan mengidentifikasi faktor-faktor yang menjadi pertimbangan petani padi serta mengembangkan model adopsi drone berdasarkan kerangka Decomposed Theory of Planned Behavior (DTPB). Penelitian menggunakan pendekatan kualitatif eksploratif dengan studi kasus pada petani padi di Kabupaten Lombok Barat. Data utama diperoleh melalui wawancara mendalam berbasis kelompok dan observasi lapangan, serta dilengkapi informasi dari penyuluh pertanian, perwakilan perusahaan pertanian, dan dinas pertanian. EEG Neurofeedback digunakan secara terbatas sebagai data pendukung untuk memperkaya interpretasi respons personal dan kognitif petani selama fase take-off, hover, dan landing. Data dianalisis secara tematik melalui tahapan open coding, axial coding, dan selective coding, kemudian diperdalam melalui triangulasi data dan evaluasi proposisi.
Hasil penelitian menghasilkan tiga faktor utama dalam model akhir, yaitu faktor personal dan kognitif, faktor sosial dan kelembagaan, serta faktor kontekstual dan operasional. Ketiga faktor tersebut dipetakan dalam perspektif DTPB, yaitu Attitude, Subjective Norm, dan Perceived Behavioral Control. Data EEG tidak digunakan untuk mengukur sikap, niat, kesiapan adopsi, maupun penggunaan aktual secara langsung, tetapi hanya sebagai informasi pendukung dalam interpretasi temuan kualitatif. Model akhir menunjukkan bahwa adopsi drone oleh petani padi berlangsung secara bertahap, kolektif, kontekstual, dan berbasis layanan. Niat menggunakan drone belum selalu berkembang menjadi penggunaan aktual tanpa pelatihan dan pendampingan, dukungan penyuluh, biaya yang terjangkau, ketersediaan operator, infrastruktur, serta layanan teknis. Bentuk adopsi yang paling realistis saat ini adalah melalui layanan sewa, bantuan operator atau pilot drone, dan penggunaan kolektif melalui kelompok tani.
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Drone technology or Unmanned Aerial Vehicles (UAVs) holds the potential to support the implementation of smart farming by facilitating tasks such as spraying, fertilizing, and land monitoring, while enhancing the effectiveness and efficiency of agricultural operations. However, the adoption of this technology by rice farmers depends not only on technical benefits but also on personal, social, institutional, economic, and operational considerations. This study aims to identify the factors influencing rice farmers' decisions and to develop a drone adoption model based on the Decomposed Theory of Planned Behavior (DTPB) framework. An exploratory qualitative approach was employed, utilizing a case study of rice farmers in West Lombok Regency. Primary data were gathered through group-based in-depth interviews and field observations, supplemented by information from agricultural extension workers, representatives of agricultural companies, and the agriculture agency. EEG Neurofeedback was used to a limited extent as supporting data to enrich the interpretation of farmers' personal and cognitive responses during take-off, hovering, and landing phases. Data were analyzed thematically through open, axial, and selective coding stages, followed by further refinement via data triangulation and proposition evaluation.
The study identified three main factors in the final model: personal and cognitive factors, social and institutional factors, and contextual and operational factors. These factors were mapped against the DTPB constructs of Attitude, Subjective Norm, and Perceived Behavioral Control. The EEG data were not used to directly measure attitude, intention, adoption readiness, or actual usage, but rather served as supporting information for interpreting qualitative findings. The final model reveals that drone adoption among rice farmers occurs in a manner that is gradual, collective, contextual, and service-oriented. Intention to use drones does not automatically translate into actual usage without training and mentoring, extension support, affordable costs, the availability of operators and infrastructure, and technical services. Currently, the most realistic forms of adoption involve rental services, assistance from drone operators or pilots, and collective usage through farmer groups.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Adopsi Teknologi, Drone Pertanian, DTPB, EEG, Smart Farming, Technology Adoption, Agricultural Drones, DTPB, EEG, Smart Farming. |
| Subjects: | R Medicine > RC Internal medicine > RC386.5 Electroencephalography. S Agriculture > SB Plant culture > SB191.R5 Rice farming T Technology > T Technology (General) > T59.7 Human-machine systems. T Technology > TJ Mechanical engineering and machinery > TJ1480 Agricultural machinery. Farm machinery T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL152.8 Vehicles, Remotely piloted. Autonomous vehicles. |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information System > 59101-(S2) Master Thesis |
| Depositing User: | Yusril Rahman |
| Date Deposited: | 31 Jul 2026 07:53 |
| Last Modified: | 31 Jul 2026 07:53 |
| URI: | http://repository.its.ac.id/id/eprint/140920 |
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