Electronic Theses and Dissertation

Kesuburan tanah merupakan faktor penting bagi keberhasilan budidaya bawang merah, namun sebagian besar petani di Kabupaten Pidie masih menentukan dosis pupuk berdasarkan pengalaman pribadi dan pengamatan visual tanpa data kuantitatif kondisi tanah, sehingga teknologi soil sensor berpotensi besar dimanfaatkan, meskipun tingkat adopsinya di lapangan masih rendah. Penelitian ini bertujuan menganalisis pengaruh karakteristik demografi dan pertanian terhadap hambatan, persepsi manfaat, dan kesediaan petani bawang merah dalam mengadopsi teknologi soil sensor di Kecamatan Simpang Tiga, Kabupaten Pidie. Sampel penelitian berjumlah 75 petani, dianalisis menggunakan regresi logistik ordinal. Hasil penelitian menunjukkan bahwa karakteristik demografi dan pertanian berpengaruh signifikan terhadap ketiga variabel tersebut. Hambatan adopsi tergolong sedang dengan nilai mean 2,33–2,91, sementara persepsi manfaat dan kesediaan adopsi tergolong tinggi dengan nilai mean masing-masing 3,59–4,03 dan 3,51–4,21. Tingkat pendidikan menjadi faktor yang paling konsisten berpengaruh, di mana semakin rendah pendidikan petani maka semakin besar hambatan yang dirasakan dan semakin rendah persepsi manfaat yang dimiliki, sedangkan pendidikan yang lebih tinggi justru meningkatkan kesediaan adopsi. Temuan ini menjadi dasar perlunya program penyuluhan dan dukungan pembiayaan.

Soil fertility is a crucial factor for the successful cultivation of shallots; however, most farmers in Pidie Regency still determine fertilizer dosages based on personal experience and visual observation rather than quantitative soil data. Consequently, soil sensor technology holds significant potential for application, even though adoption rates in the field remain low. This study aimed to analyze the influence of demographic and agricultural characteristics on the barriers, perceived benefits, and willingness of shallot farmers to adopt soil sensor technology in Simpang Tiga District, Pidie Regency. A sample of 75 farmers was analyzed using ordinal logistic regression. The results indicate that demographic and agricultural characteristics significantly influence all three variables. Adoption barriers were classified as moderate (mean values ​​of 2.33–2.91), whereas perceived benefits and willingness to adopt were classified as high (mean values ​​of 3.59–4.03 and 3.51–4.21, respectively). Education level emerged as the most consistently influential factor; lower education levels were associated with greater perceived barriers and lower perceived benefits, while higher education levels increased the willingness to adopt the technology. These findings highlight the need for extension programs and financial support.