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Moch. Rio Pambudi
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Jl. Prof. Dr. Ing. B. J. Habibie, Moutong, Tilongkabila, Kabupaten Bone Bolango 96119, Gorontalo, Indonesia. Tel. +62-852-5674-4737 , +62-821-5166-4800 (Call/SMS/WA) E-mail: geosfera@ung.ac.id
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Geosfera: Jurnal Penelitian Geografi
Published by Universitas Negeri Gorontalo
ISSN : 29625424     EISSN : 29625416     DOI : https://doi.org/10.34312/geojpg.v1i1
Core Subject : Science, Education, Social,
Earth & Planetary Sciences Education Environmental Science Social Sciences
Geosfera : Jurnal Penelitian Geografi (GeoJPG, P-ISSN: 2962-5424, E-ISSN: 2962-5416) is a peer-reviewed journal published by Department of Earth Science and Technology, Universitas Negeri Gorontalo. GeoJPG provides open access to the principle that research published in this journal is freely available to the public to support the exchange of knowledge globally. GeoJPG published two-issue articles per year namely June and December. GeoJPG provides a place for academics, researchers, and practitioners to publish scientific articles. Each text sent to GeoJPG editor is reviewed by peer review. Starting from Vol. 1 No. 1 (June 2022), all manuscripts sent to the GeoJPG editor are accepted in Bahasa Indonesia. The scope of the articles listed in this journal relates to various topics, including (1) Geography Education, (2) Physical Geography, (3) Human Geography, (4) Geographic Information System (GIS), (5) Remote Sensing, (6) Environmental Science, (7) Disaster Risk Reduction and other relevant geosciences. This journal is available in print and online and highly respects the ethics of publication and avoids all types of plagiarism.
Arjuna Subject : Ilmu Sosial - Geografi, Perencanaan dan Pengembangan
Articles 123 Documents
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Perancangan Zona Layanan dan Rute Bus Sekolah Kota Payakumbuh Menggunakan Graph Neural Network (GNN) Rizky Ferdiansyah Habibi NST; Arie Yulfa
Geosfera: Jurnal Penelitian Geografi Vol 4, No 2 (2025): Geosfera : Jurnal Penelitian Geografi
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/geojpg.v4i2.37729

Abstract

Payakumbuh City is one of the cities located in West Sumatra Province, with a population of 149,077 people. Public transportation is needed for daily mobility, especially for students, because public transportation in this city only consists of 21 units and only serves one route. This study aims to establish service zones, routes, stops or bus stops, and bus transportation modes that are suitable for the geographical conditions of Payakumbuh City. The method used in this study is Graph Neural Network (GNN) with the variables analyzed being the distribution of schools, traffic congestion points, points of interest, and road networks. The results of the study show that service zones can be determined based on the existing land use in Payakumbuh City, dividing the service zones into 4 zones with a total route length of 93.54 kilometers, 209 bus stops, and a suitable mode of transportation, namely microbuses with two types of buses, with an estimated number of 211 units. Payakumbuh City can implement public transportation, particularly school buses, but special attention must be given to the existing road conditions, as the road width in the area is 4-7 meters. Therefore, in its implementation, three service zones can use microbuses with a capacity of 30 passengers, and one service zone can use microbuses with a capacity of 20 passengers.
Pengaruh Faktor Oseanografi Terhadap Hasil Tangkapan Masyarakat Nelayan Di Kelurahan Namosain Kecamatan Alak Kota Kupang Dian Kusuma Dewi; Hamza H Wulakada; Arfita Rahmawati
Geosfera: Jurnal Penelitian Geografi Vol 4, No 2 (2025): Geosfera : Jurnal Penelitian Geografi
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/geojpg.v4i2.37681

Abstract

Fishing communities are coastal communities that are highly dependent on marine conditions in carrying out fishing activities. The dynamics of oceanographic conditions, such as ocean currents and tidal fluctuations, play an important role in determining fish distribution, fishing safety, and the success of fishing activities. This study aims to examine the effect of oceanographic factors on the catch of fishing communities in Namosain Village, Alak District, Kupang City. This research employed a quantitative approach using a survey method. The research population consisted of fishermen in Namosain Village, with the sample determined using the Slovin formula. The results showed that partially, ocean currents had a significant effect on fishermen’s catch, while tidal fluctuations did not have a significant effect on fishermen’s catch. However, simultaneously, oceanographic factors had a significant effect on the catch of fishing communities in Namosain Village. These findings indicate that oceanographic conditions play an important role in determining the success of fishing activities; therefore, adaptation efforts and increased fishermen’s understanding of marine dynamics are needed to support the sustainability of capture fisheries and improve the welfare of coastal fishing communities.
Pemetaan Bahaya Banjir Berbasis Geomorphic Flood Index (GFI) Di Sub-Das Batang Tebo Provinsi Jambi Ias Okta Kurniawan; Dipo Caesario
Geosfera: Jurnal Penelitian Geografi Vol 4, No 2 (2025): Geosfera : Jurnal Penelitian Geografi
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/geojpg.v4i2.37991

Abstract

Banjir merupakan bencana hidrometeorologi yang paling sering terjadi di Indonesia, termasuk di Sub-DAS Batang Tebo yang mencatat 30 kejadian banjir selama periode 2019–2024. Penelitian ini bertujuan memetakan bahaya banjir di Sub-DAS Batang Tebo menggunakan metode Geomorphic Flood Index (GFI) berbasis data Digital Elevation Model (DEM), serta menguji akurasi model terhadap data genangan aktual dari citra Sentinel-1 yang diolah melalui Google Earth Engine (GEE). GFI dihitung secara sistematis menggunakan dua parameter utama, yaitu Height Above Nearest Drainage (H) dan Hydraulic Radius Proxy (hr). Hasil pemodelan menunjukkan bahwa kelas bahaya rendah mendominasi wilayah seluas 279.080,56 ha (65,4%), diikuti kelas sedang 90.913,56 ha (21,3%), tinggi 31.186,86 ha (7,3%), dan sangat tinggi 25.561,28 ha (6,0%). Lima kecamatan termasuk kelas bahaya sangat tinggi: Kecamatan Tebo Tengah, Kecamatan Batin II Babeko, Kecamatan Bungo Dani, Kecamatan Pasar Muaro Bungo, dan Kecamatan Bathin III. Uji akurasi menggunakan True Positive Rate (TPR) menghasilkan nilai 0,64 pada base case (GFI 2,3), sedangkan Frequency Ratio (FR) meningkat konsisten dari 0,11 pada kelas rendah hingga 7,23 pada kelas sangat tinggi. Hasil ini menunjukkan bahwa metode GFI layak digunakan sebagai pendekatan awal pemetaan bahaya banjir berbasis geomorfologi.

Page 13 of 13 | Total Record : 123

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