Erat hubungan antara iklim dan tanaman kopi membutuhkan langkah yang tepat dalam perencanaan dan pengembangan tanaman kopi. Sulawesi Selatan merupakan salah satu wilayah penghasil tanaman kopi arabika dan sedang direncanakan pengembangannya. Penelitian ini bertujuan mengetahui sebaran wilayah kesesuaian tanaman kopi Arabika di masa depan berdasarkan hasil proyeksi skenario RCP8.5 periode tahun 2021- 2050 dan 2051-2080 di Sulawesi Selatan, yang digunakan sebagai rekomendasi dalam investasi pengembangan tanaman kopi Arabika di Provinsi Sulawesi Selatan. Data yang digunakan adalah data observasi rata-rata bulanan curah hujan dan suhu udara periode 1989-2018. Data proyeksi yang digunakan merupakan data dari ensemble CORDEX-SEA yaitu model CSIRO dengan resolusi 25x25 km skenario RCP8.5 periode 2021-2080. Periode proyeksi dibagi menjadi dua periode untuk setiap scenario. Kesesuaian agroklimat untuk tanaman kopi Arabika dibuat berdasarkan dari jumlah bobot parameter yang digunakan. Hasil penelitian menunjukkan penurunan kualitas kesesuaian agroklimat pada periode proyeksi untuk tanaman kopi Arabika di Sulawesi Selatan. Hal ini, terlihat dari menyusutnya luas lahan klasifikasi sangat sesuai (S1) pada periode proyeksi dibandingkan dengan periode baseline. Persentase luas lahan untuk klasifikasi S1 untuk periode baseline sebesar 44% lalu mengalami penyusutan pada proyeksi skenario RCP8.5 periode 2021-2050 menjadi 27%. Hasil proyeksi skenario RCP8.5 periode 2051-2080 mengalami penyusutan persentase luas lahan klasifikasi yang signifikan dibandingkan dengan periode baseline yaitu menjadi 5%.
The weather data that can be obtained through government institutions is very limited, whereas in order to increase the accuracy of weather predictions a homogeneous and dense distribution of data is needed. Therfore it is necessary to increase the data and the purpose of this research is to create a simple and effective way to encourage the number of weather observations in Indonesia through the STMKG Weather Care program. Forms that are made as easy as for respondents to understand, simple, and don't take the time. Developed using Google Form and distributed via the most popular social media today, namely WhatsApp. The test results showed that social media has the potential to be used to support voluntary weather data. The form made is sufficient so that the respondents make relatively few mistakes in terms of the main content of the form. Moreover, the mistakes that are often made by respondents include filling in ID, and typing sub-districts that require manual correction. Based on the results of voluntary observations spread in almost all provinces of Indonesia with the most incoming data coming from the provinces of Central Java and East Java. Based on the evaluation results of 4 months of testing, weather variations and their predictions can be identified with an accurate distribution, with an average accuracy of 0.79. Differences in methods used in verification may affect accuracy.
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