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All Journal Spatial : Wahana Komunikasi dan Informasi Geografi Geodika: Jurnal Kajian Ilmu dan Pendidikan Geografi The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Kuncoro Adi Pradono
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Humanities Earth & Planetary Sciences Education Environmental Science Social Sciences

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Prediksi Pertumbuhan Penduduk dengan Google Earth Pro Studi Kasus Kelurahan Madyopuro Kota Malang Kuncoro Adi Pradono; Wibowo, Adi
Jurnal Spatial Wahana Komunikasi dan Informasi Geografi Vol. 24 No. 2 (2024): 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.242.004

Abstract

The construction of the Trans Java toll road has brought development to the areas it passes through. As happened in Madyopuro Village, Malang City, which was transformed into a satellite city due to the construction of the toll exit, some unoccupied land in this area began to be looked at by developers to build settlements known from the 2019 image. In addition, supporting facilities in the form of arterial roads were widened so that access to the eastern region of the village became easy. This settlement development factor is an indicator of population growth. The purpose of this research is to analyze changes in the number of settlements with Google Earth Data. The method used is snapshoot analysis through Google Earth Pro image data which is available in full and easily accessible in a multi-spatial and multi-temporal manner. The results are used to predict the amount of population growth. Images from Google Earth are rectified then the amount of built-up land in the form of settlements is calculated through the appearance of the roof. Furthermore, the number of each building is correlated with the population of each building based on SNI-03-1733-2004. The results of this calculation were compared with population data for that year using data from the Central Statistics Agency (BPS). The results of this research show that the population based on predictions in 2015 amounted to 18,604 people, in BPS data 19,566 people. For 2019, predictions with this method show a number of 20,020 people and BPS data shows 20,067 people. The prediction in 2023 is 21,544 people. Through image data from Google Earth Pro, the population predicted by this method is close to data from BPS in 2015 and 2019 with a difference. The conclusion is that data on changes in house buildings from Google Earth can be used to predict the number of people affected by toll road construction.
Analisis Distribusi Fasilitas Sekolah Menengah Pertama melalui Pemodelan Spasial Studi Kasus di Kota Malang Kuncoro Adi Pradono; Manurung, Parluhutan; Wibowo, Adi
Geodika: Jurnal Kajian Ilmu dan Pendidikan Geografi Vol 8 No 2 (2024): September 2024
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/geodika.v8i2.25692

Abstract

Dalam upaya membangun bangsa melalui pemerataan wajib belajar sembilan tahun merupakan bagian amanat UUD 1945 dan menjadi prioritas program pemerintah. Penelitian ini bertujuan untuk menganalisis distribusi fasilitas sekolah SMP di Kota Malang. Metode pemodelan spasial yang digunakan metode krigging dan regresi machine learning untuk prediksi perkembangan fasilitas sekolah SMP. Pemodelan spasial akan menilai sejauh mana pola spasial fasilitas sekolah terdistribusi dan analisis regresi yang akan melakukan prediksi fasilitas sekolah SMP dengan variabel peserta didik, guru, pegawai dan rombongan belajar. Hasil pemodelan spasial dengan teknik krigging menunjukan distribusi variogram antar fasilitas sekolah berjarak 3-4 km dan merata. Adapun regresi dengan model terbaik secara berurutan REML, RF, OLS, GB, INLA dan PLS. Dengan model terbaik didapatkan akurasi 0,98 dan RMSE sebesar 0.79. Melalui hasil dari penelitian ini didapatkan gambaran bahwa sebaran distribusi fasilitas sekolah tingkat SMP di era zonasi saat ini masih terpusat di wilayah tengah Kota Malang sehingga terdapat peluang untuk pembangunan dan pengembangan fasilitas sekolah SMP di daerah pinggiran. Analisis pemodelan spasial dapat memberikan sudut pandang dan pertimbangan bagaimana fasilitas sekolah di perbaikan sesuai untuk pemerataan pendidikan.
EFFECT OF ATMOSPHERIC CORRECTION ALGORITHM ON LANDSAT-8 AND SENTINEL-2 CLASSIFICATION ACCURACY IN PADDY FIELD AREA Fadila Muchsin; Kuncoro Adi Pradono; Indah Prasasti; Dianovita; Kurnia Ulfa; Kiki Winda Veronica; Dandy Aditya Novresiandi; Andi Ibrahim
International Journal of Remote Sensing and Earth Sciences Vol. 20 No. 1 (2023)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2023.v20.a3845

Abstract

Landsat-8 and Sentinel-2 satellite imageries are widely used for various remote sensing applications because they are easy to access and free to download. A precise atmospheric correction is necessary to be applied to the optical satellite imageries so that the derived information becomes more accurate and reliable. In this study, the performance of atmospheric correction algorithms (i.e., 6S, FLAASH, DOS, LaSRC, and Sen2Cor) was evaluated by comparing the object's spectral response, vegetation index, and classification accuracy in the paddy field area before and after the implementation of atmospheric correction. Overall, the results show that each algorithm has varying accuracy. Nevertheless, all atmospheric correction algorithms can improve the classification accuracy, whereby those derived by the 6S and FLAASH yielded the highest accuracy.
Co-Authors Adi Wibowo Andi Ibrahim Dandy Aditya Novresiandi Dianovita Fadila Muchsin Indah Prasasti Kiki Winda Veronica Kurnia Ulfa Parluhutan Manurung