Pemanfaatan Data Automatic Weather Station (AWS) dan BMKG dalam Penentuan Waktu Tanam bagi Petani di Kawasan Transmigrasi Pulau Morotai

Abstract

Pemanfaatan data cuaca berbasis Automatic Weather Station (AWS) dan BMKG diperlukan untuk membantu petani menentukan waktu tanam yang lebih tepat pada kondisi iklim dan cuaca yang semakin tidak menentu. Penelitian ini bertujuan menganalisis persepsi dan penilaian petani terhadap pemanfaatan data AWS, pola data cuaca yang terekam seperti (curah hujan, suhu, dan lama penyinaran), pendapat petani terhadap kendala pemanfaatan AWS, kesesuain cuaca lokal, dan keefektivitasan pemanfaatan data AWS, serta korelasi antara persepsi petani tentang pemanfaatan data AWS terhadap tindakan petani dalam pemanfaatan data AWS, penilaian petani terhadap data cuaca AWS dengan kesesuaian cuaca lokal, dan kendala pemanfaatan data AWS oleh petani terhadap efektivitas pemanfaatan data AWS oleh petani. Penelitian dilaksanakan di SP I dan SP III Desa Morodadi, Kecamatan Morotai Selatan, Kabupaten Pulau Morotai. Metode penelitian menggunakan pendekatan kuantitatif dan kualitatif dengan 32 responden petani. Data dikumpulkan melalui kuesioner, wawancara, observasi, dan data (AWS dan BMKG) berupa curah hujan, suhu udara, serta lama penyinaran. Hasil penelitian menunjukkan persepsi petani terhadap AWS berada pada kategori tinggi sebesar 68,8%. Curah hujan berkisar 103–762 mm, suhu udara 26,78–27,69°C, dan lama penyinaran 3,52–6,26 jam per hari. Waktu tanam cabai lebih sesuai diarahkan pada Juli dan Maret. Kendala pemanfaatan meliputi jaringan internet, penggunaan perangkat digital, dan pemahaman data teknis. Terdapat korelasi pada setiap variable penelitian.

The utilization of weather data from Automatic Weather Stations (AWS) and the Indonesian Agency for Meteorology, Climatology, and Geophysics (BMKG) is necessary to assist farmers in determining more appropriate planting times under increasingly uncertain climate and weather conditions. This study aimed to analyze farmers’ perceptions and assessments of AWS data utilization, recorded weather patterns such as rainfall, air temperature, and sunshine duration, farmers’ views regarding constraints in using AWS, the suitability of AWS data with local weather conditions, and the effectiveness of AWS data utilization. The study also examined the correlations between farmers’ perceptions of AWS utilization and their actions in using AWS data, farmers’ assessments of AWS weather data and its suitability with local weather conditions, as well as constraints in AWS utilization and the effectiveness of AWS data use by farmers. The study was conducted in Settlement Units I and III (SP I and SP III), Morodadi Village, South Morotai District, Morotai Island Regency. The research employed quantitative and qualitative approaches involving 32 farmer respondents. Data were collected through questionnaires, interviews, observations, and weather records from AWS and BMKG, including rainfall, air temperature, and sunshine duration. The results showed that farmers’ perceptions of AWS were predominantly in the high category, accounting for 68.8%. Rainfall ranged from 103 to 762 mm, air temperature ranged from 26.78 to 27.69°C, and sunshine duration ranged from 3.52 to 6.26 hours per day. The most suitable periods for chili planting were identified as July and March. The main constraints included internet connectivity, the use of digital devices, and limited understanding of technical weather data. Significant correlations were found among all variables examined in this study.