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Kota adm. jakarta timur,
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INDONESIA
Spatial : Wahana Komunikasi dan Informasi Geografi
Published by Universitas Negeri Jakarta
ISSN : 16931408     EISSN : 25809830     DOI : -
Core Subject : Science,
Earth & Planetary Sciences
Jurnal SPATIAL Wahana Komunikasi dan Informasi terbit dua kali dalam setahun, bulan Maret dan September.
Arjuna Subject : -
Articles 192 Documents
 16   17   18   19   20 
A Pemilihan Model Pembelajaran Mitigasi Kebencanaan Menggunakan Metode AHP di SMAN Kecamatan Jatinegara: Pemilihan Model Pembelajaran Mitigasi Kebencanaan Menggunakan Metode AHP Di SMAN Kecamatan Jatinegara Ula Nurjanah
Jurnal Spatial Wahana Komunikasi dan Informasi Geografi Vol. 25 No. 2 (2025): SPATIAL: Wahana Komunikasi dan Informasi Geografi
Publisher : Department Geography Education Faculty of Social Science - Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/spatial.252.008

Abstract

This study was conducted to determine how the application of the Analytical Hierarchy Process (AHP) in deciding the learning model on disaster mitigation material at SMAN Jatinegara District. The selection of the right model will assist teachers in the learning process so that the learning objectives that have been set will be achieved. This study uses a descriptive quantitative approach with the analytical hierarchy process (AHP) method. In determining the sample, the researcher used purposive sampling. The data collection technique was carried out by filling out a questionnaire and interviewing experts. Data analysis was carried out using the superdecission application by filling out a comparison matrix to obtain preference weights, consistency tests, and then obtaining the decision results from calculating the combination of respondents' opinions using the superdecission application. The final alternative results show that the highest disaster mitigation material learning model is outdoor learning with a weighted value of 0.2780, the PBL model 0.2090, the Earthcomm model 0.2011, the PjBL model 0.1905, and the Inquiry Learning model 0.1214. Then the highest criteria in selecting a learning model are learning objectives with a weight of 0.4070, Student Characteristics 0.2406, Teaching Media 0.1945 and Supporting Facilities 0.1577. Based on the results of the study, it can be concluded that the outdoor learning model with a high weight is the most recommended model for disaster mitigation material.
Evaluasi Akurasi Deteksi Kelapa Sawit TBM Menggunakan Object-Based Image Analysis pada Citra UAV Alhafiz Ibnu Azmi; Dedy Fitriawan; Eva Purnamasari; Muhammad Ismail
Jurnal Spatial Wahana Komunikasi dan Informasi Geografi Vol. 25 No. 2 (2025): SPATIAL: Wahana Komunikasi dan Informasi Geografi
Publisher : Department Geography Education Faculty of Social Science - Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/spatial.252.001

Abstract

Rapid and accurate identification of oil palm health status is crucial for supporting plantation replanting decisions. This study aimed to compare the sensitivity of the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Red Edge (NDRE) in detecting senescence in oil palms using multispectral Unmanned Aerial Vehicle (UAV) imagery. A comparative quantitative approach was employed across two smallholder oil palm plantation blocks in Kamang Baru District, Sijunjung Regency, West Sumatra. Data were obtained through multispectral UAV image acquisition, followed by orthomosaic generation, manual digitization for ground truth, calculation of NDVI and NDRE indices, descriptive statistical analysis, accuracy evaluation using a confusion matrix (Overall Accuracy and Kappa Coefficient), and spatial pattern analysis using Nearest Neighbor Analysis. The results identified 320 individual trees, comprising 195 healthy plants and 125 plants exhibiting senescence. NDVI yielded clearer value separation between classes compared to NDRE and demonstrated higher classification accuracy, with an Overall Accuracy of 81.25% and a Kappa Coefficient of 0.604, whereas NDRE achieved an Overall Accuracy of 69.06% and a Kappa Coefficient of 0.357. Spatial analysis revealed that the senescent plants exhibited a clustered pattern. The novelty of this study lies in the empirical evidence demonstrating that NDVI is more sensitive than NDRE for detecting senescence at the study site, indicating that the effectiveness of vegetation indices is influenced by plant physiological characteristics, environmental conditions, and spectral responses at the observation location. These findings provide a scientific basis for selecting the most appropriate vegetation index to support health monitoring and replanting planning for oil palms using multispectral UAV technology.

Page 20 of 20 | Total Record : 192

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