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Proses Perhitungan Otomatis Menggunakan Oil Palm Application (OPA)
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Abstrak. Kelapa sawit merupakan komoditas utama dalam produksi minyak nabati di Indonesia dan menyumbang pendapatan devisa terbesar bagi negara. Dengan perkebunan kelapa sawit yang luas, pengelolaan jumlah pohon kelapa sawit menjadi krusial dalam perencanaan dan pemeliharaan. Sayangnya, perhitungan manual sering kali tidak efektif dan berisiko terjadi kesalahan perhitungan. Oleh karena itu, penelitian ini mengusulkan penggunaan teknologi penginderaan jauh, khususnya Oil Palm Application (OPA) dari Trimble eCognition, untuk menghitung jumlah pohon kelapa sawit secara otomatis melalui citra satelit beresolusi tinggi. Studi ini bertujuan untuk menjelaskan proses perhitungan otomatis kelapa sawit menggunakan OPA dan mengevaluasi potensi serta tingkat akurasi teknologi ini. Hasilnya diharapkan dapat memberikan kontribusi positif dalam pengelolaan perkebunan kelapa sawit yang lebih efisien. OPA diharapkan mampu memberikan informasi cepat dan akurat tentang jumlah pohon kelapa sawit, membantu pengelola perkebunan dalam perencanaan, pemeliharaan, dan pemupukan yang lebih efektif. Studi ini menjadi relevan mengingat pertumbuhan pesat perkebunan kelapa sawit setiap tahunnya dan meningkatnya permintaan minyak sawit di pasar domestik dan internasional.Automatic Calculation Process Using Oil Palm Application (OPA)Abstrac. Palm oil is a primary commodity in the vegetable oil production in Indonesia and contributes significantly to the country's foreign exchange earnings. Given the vast expanses of oil palm plantations, the management of the palm tree count becomes crucial in planning and maintenance. Unfortunately, manual counting often proves ineffective and prone to calculation errors. Therefore, this research proposes the utilization of remote sensing technology, specifically the Oil Palm Application (OPA) by Trimble eCognition, to automatically count the number of oil palm trees through high-resolution satellite imagery.This study aims to elucidate the automated oil palm tree counting process using OPA and evaluate the potential and accuracy of this technology. The results are expected to make a positive contribution to more efficient oil palm plantation management. OPA is anticipated to provide quick and accurate information about the number of oil palm trees, assisting plantation managers in better planning, maintenance, and fertilization. This study is relevant considering the rapid growth of oil palm plantations each year and the increasing demand for palm oil in both domestic and international markets.
LPPM Universitas Syiah Kuala
Title: Proses Perhitungan Otomatis Menggunakan Oil Palm Application (OPA)
Description:
Abstrak.
Kelapa sawit merupakan komoditas utama dalam produksi minyak nabati di Indonesia dan menyumbang pendapatan devisa terbesar bagi negara.
Dengan perkebunan kelapa sawit yang luas, pengelolaan jumlah pohon kelapa sawit menjadi krusial dalam perencanaan dan pemeliharaan.
Sayangnya, perhitungan manual sering kali tidak efektif dan berisiko terjadi kesalahan perhitungan.
Oleh karena itu, penelitian ini mengusulkan penggunaan teknologi penginderaan jauh, khususnya Oil Palm Application (OPA) dari Trimble eCognition, untuk menghitung jumlah pohon kelapa sawit secara otomatis melalui citra satelit beresolusi tinggi.
Studi ini bertujuan untuk menjelaskan proses perhitungan otomatis kelapa sawit menggunakan OPA dan mengevaluasi potensi serta tingkat akurasi teknologi ini.
Hasilnya diharapkan dapat memberikan kontribusi positif dalam pengelolaan perkebunan kelapa sawit yang lebih efisien.
OPA diharapkan mampu memberikan informasi cepat dan akurat tentang jumlah pohon kelapa sawit, membantu pengelola perkebunan dalam perencanaan, pemeliharaan, dan pemupukan yang lebih efektif.
Studi ini menjadi relevan mengingat pertumbuhan pesat perkebunan kelapa sawit setiap tahunnya dan meningkatnya permintaan minyak sawit di pasar domestik dan internasional.
Automatic Calculation Process Using Oil Palm Application (OPA)Abstrac.
Palm oil is a primary commodity in the vegetable oil production in Indonesia and contributes significantly to the country's foreign exchange earnings.
Given the vast expanses of oil palm plantations, the management of the palm tree count becomes crucial in planning and maintenance.
Unfortunately, manual counting often proves ineffective and prone to calculation errors.
Therefore, this research proposes the utilization of remote sensing technology, specifically the Oil Palm Application (OPA) by Trimble eCognition, to automatically count the number of oil palm trees through high-resolution satellite imagery.
This study aims to elucidate the automated oil palm tree counting process using OPA and evaluate the potential and accuracy of this technology.
The results are expected to make a positive contribution to more efficient oil palm plantation management.
OPA is anticipated to provide quick and accurate information about the number of oil palm trees, assisting plantation managers in better planning, maintenance, and fertilization.
This study is relevant considering the rapid growth of oil palm plantations each year and the increasing demand for palm oil in both domestic and international markets.
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