AUTOMATIC PALM COUNTING DENGAN METODE TEMPLATE MATCHING (STUDI KASUS DI UNIVERSITAS SAMUDRA)

The oil palm land donated to Universitas Samudra is planned for the development of the campus area, including the construction of a number of buildings and supporting facilities. However, the process of identifying and mapping oil palm plants has been done manually, which is time-consuming, ineffici...

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Main Authors: Agusman, Iswahyudi, Iwan saputra
Format: Article
Language:English
Published: Universitas Brawijaya 2025-01-01
Series:JTSL (Jurnal Tanah dan Sumberdaya Lahan)
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Online Access:https://jtsl.ub.ac.id/index.php/jtsl/article/view/1098
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author Agusman
Iswahyudi
Iwan saputra
author_facet Agusman
Iswahyudi
Iwan saputra
author_sort Agusman
collection DOAJ
description The oil palm land donated to Universitas Samudra is planned for the development of the campus area, including the construction of a number of buildings and supporting facilities. However, the process of identifying and mapping oil palm plants has been done manually, which is time-consuming, inefficient, and prone to errors. This problem underscores the need for faster and more accurate methods to support spatial data-based planning. This study aimed to calculate the number of oil palm plants in 2022 and 2023 at the University of Samudra using the template matching method with eCognition Developer software, as well as evaluate the accuracy of automatic detection results based on aerial images obtained using drones. The research was carried out using survey methods and descriptive analysis, involving primary data in the form of aerial imagery and field validation, as well as secondary data from the map of the oil palm plantation area of Samudra University. The results of the study show that the number of oil palm plants in 2022 based on automatic calculations was 2,060 trees, while the results of manual validation showed the actual number of 2,169 trees with a difference of 109 trees. In 2023, the automatic calculation detected 1,932 trees, while the actual number was 2,030 trees, with a difference of 98 trees. The accuracy level of automatic calculations in 2022 had an average accuracy of 98.56%, recall of 94.05%, and F1-score of 95.63%, higher than in 2023 with precision of 97.41%, recall of 92.73%, and F1-score of 94.98%. Then the template matching method is effectively used for oil palm tree detection and can support the planning of campus area development efficiently. The use of this technology is expected to be a model that can be implemented in various other educational institutions.
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spelling doaj-art-90f3b1ae50b44d208cd2a3ff02e826c72025-08-20T02:40:02ZengUniversitas BrawijayaJTSL (Jurnal Tanah dan Sumberdaya Lahan)2549-97932025-01-0112118319610.21776/ub.jtsl.2025.012.1.18915AUTOMATIC PALM COUNTING DENGAN METODE TEMPLATE MATCHING (STUDI KASUS DI UNIVERSITAS SAMUDRA)Agusman0Iswahyudi1https://orcid.org/0000-0001-8551-3128Iwan saputra2Program Studi Agroteknologi, Fakultas Pertanian, Universitas SamudraProgram Studi Agroteknologi, Fakultas Pertanian, Universitas SamudraProgram Studi Agroteknologi, Fakultas Pertanian, Universitas SamudraThe oil palm land donated to Universitas Samudra is planned for the development of the campus area, including the construction of a number of buildings and supporting facilities. However, the process of identifying and mapping oil palm plants has been done manually, which is time-consuming, inefficient, and prone to errors. This problem underscores the need for faster and more accurate methods to support spatial data-based planning. This study aimed to calculate the number of oil palm plants in 2022 and 2023 at the University of Samudra using the template matching method with eCognition Developer software, as well as evaluate the accuracy of automatic detection results based on aerial images obtained using drones. The research was carried out using survey methods and descriptive analysis, involving primary data in the form of aerial imagery and field validation, as well as secondary data from the map of the oil palm plantation area of Samudra University. The results of the study show that the number of oil palm plants in 2022 based on automatic calculations was 2,060 trees, while the results of manual validation showed the actual number of 2,169 trees with a difference of 109 trees. In 2023, the automatic calculation detected 1,932 trees, while the actual number was 2,030 trees, with a difference of 98 trees. The accuracy level of automatic calculations in 2022 had an average accuracy of 98.56%, recall of 94.05%, and F1-score of 95.63%, higher than in 2023 with precision of 97.41%, recall of 92.73%, and F1-score of 94.98%. Then the template matching method is effectively used for oil palm tree detection and can support the planning of campus area development efficiently. The use of this technology is expected to be a model that can be implemented in various other educational institutions.https://jtsl.ub.ac.id/index.php/jtsl/article/view/1098citra dronekelapa sawittemplate matchingpemetaan otomatis
spellingShingle Agusman
Iswahyudi
Iwan saputra
AUTOMATIC PALM COUNTING DENGAN METODE TEMPLATE MATCHING (STUDI KASUS DI UNIVERSITAS SAMUDRA)
JTSL (Jurnal Tanah dan Sumberdaya Lahan)
citra drone
kelapa sawit
template matching
pemetaan otomatis
title AUTOMATIC PALM COUNTING DENGAN METODE TEMPLATE MATCHING (STUDI KASUS DI UNIVERSITAS SAMUDRA)
title_full AUTOMATIC PALM COUNTING DENGAN METODE TEMPLATE MATCHING (STUDI KASUS DI UNIVERSITAS SAMUDRA)
title_fullStr AUTOMATIC PALM COUNTING DENGAN METODE TEMPLATE MATCHING (STUDI KASUS DI UNIVERSITAS SAMUDRA)
title_full_unstemmed AUTOMATIC PALM COUNTING DENGAN METODE TEMPLATE MATCHING (STUDI KASUS DI UNIVERSITAS SAMUDRA)
title_short AUTOMATIC PALM COUNTING DENGAN METODE TEMPLATE MATCHING (STUDI KASUS DI UNIVERSITAS SAMUDRA)
title_sort automatic palm counting dengan metode template matching studi kasus di universitas samudra
topic citra drone
kelapa sawit
template matching
pemetaan otomatis
url https://jtsl.ub.ac.id/index.php/jtsl/article/view/1098
work_keys_str_mv AT agusman automaticpalmcountingdenganmetodetemplatematchingstudikasusdiuniversitassamudra
AT iswahyudi automaticpalmcountingdenganmetodetemplatematchingstudikasusdiuniversitassamudra
AT iwansaputra automaticpalmcountingdenganmetodetemplatematchingstudikasusdiuniversitassamudra