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All Journal MAJALAH ILMIAH GLOBE The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Rudy Parluhutan Tambunan
Unknown Affiliation
Earth & Planetary Sciences Education

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PENGUKURAN VARIABILITAS INFORMASI COVID-19 DALAM WEB-GIS Studi Kasus Kota Bogor Wayan Gede Krisna Arimjaya; Mangapul Parlindungan Tambunan; Rudy Parluhutan Tambunan; Muhammad Dimyat
Majalah Ilmiah Globe Vol. 23 No. 2 (2021): GLOBE Vol 23 No 2 TAHUN 2021
Publisher : Badan Informasi Geospasial

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Abstract

Dalam perspektif geografis, COVID-19 dilihat sebagai data yang dapat diolah menjadi informasi dan dimodelkan secara spasial. Berdasarkan Peraturan Presiden Nomor 39 Tahun 2019 tentang Satu Data Indonesia, tata kelola data dan informasi yang baik dilaksanakan dengan menerapkan prinsip Satu Data Indonesia. Penerapan standar data, metadata, interoperabilitas data, dan kode referensi dan/atau data induk sangat penting untuk mewujudkan sinergi antar-pemangku kepentingan. Variasi data dan informasi COVID-19 antara portal Kota Bogor dengan portal Provinsi Jawa Barat mengindikasikan kebijakan satu data Indonesia belum berjalan dengan baik. Penelitian ini bertujuan untuk mengukur variabilitas data dan informasi COVID-19 Kota Bogor, mengukur implikasi dari adanya variasi data tersebut dan membangun WEB-GIS COVID-19 Kota Bogor dengan prinsip satu data dan satu peta. Penelitian ini menggunakan pendekatan kuantitatif deskriptif berdasarkan kuesioner, wawancara, dan observasi. Pertanyaan disusun menggunakan Skala Likert dengan 5 ukuran skala. WEB-GIS dibangun menggunakan frame work ArcGIS Online dan dievaluasi dengan Lighthouse pada Google Chrome. Hasil survei menunjukkan variasi data terjadi di sebagian besar kecamatan di Kota Bogor. Hanya Kecamatan Bogor Timur yang memiliki variasi terendah. Implikasi dari adanya variasi data dan informasi COVID-19 di Kota Bogor berada pada kategori cukup netral dengan skor 58,77. Pemerintah perlu lebih gencar mensosialisasikan data dan informasi COVID-19 Kota Bogor. WEB-GIS COVID-19 berhasil dibuat berupa web map application dengan nilai rata-rata hasil uji 87% pada perangkat mobile dan 85% pada perangkat desktop.
UTILIZING REMOTE SENSING AND MACHINE LEARNING FOR ECOSYSTEM SERVICES MAPPING AT GUNUNG MAS TEA PLANTATION Annisa Fitria; Masita Dwi Mandini Manessa; Rudy Parluhutan Tambunan
International Journal of Remote Sensing and Earth Sciences Vol. 20 No. 2 (2023)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2023.v20.a3880

Abstract

Land use and land cover changes are one of the main factors affecting ecosystems and the services they provide. Conversion from natural vegetation to agricultural and urban land can lead to the degradation of ecosystem services and loss of biodiversity. Puncak area, Bogor, which is a highland area, has become an area that is synonymous with tea plantations because it has an ecosystem that is suitable for being a tea plantation area. Gunung Mas tea plantation managed by PTPN VIII is one of the largest tea plantations and a contributor to foreign exchange in Indonesia. The tourism potential in the plantation and agricultural business sectors has a high selling value as a tourist object and attraction. The purpose of this study is to find out the distribution of ecosystem services for climate regulation, water flow and flood regulation, and ecotourism and cultural recreation services at Gunung Mas tea plantation which is displayed in the form of an Ecosystem Service Map. The land cover classification was extracted from the Sentinel 2A image, which was then scored based on expert judgment. The scoring results are then processed using the AHP Pairwise Comparison method. The results of the study show that the research area has very high climate regulation ecosystem services, very high water flow and flood regulation, and high cultural recreation and ecotourism ecosystem services.
Co-Authors Annisa Fitria Masita Dwi Mandini Manessa Muhammad Dimyat Tambunan, Mangapul Parlindungan Wayan Gede Krisna Arimjaya