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MODEL FOR LOCATION DEVELOPMENT OF ATM BANKING SERVICE IN URBAN AREA

Indonesian Journal of Geography Vol 41, No 2 (2009): Indonesian Journal of Geography
Publisher : Faculty of Geography, Universitas Gadjah Mada

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Abstract

The research aims to (iesign a determination modelfor the locations of ICTbased economic service particularly the ATM (Automatic Teller Machine) service.The initial step of this research was to compile a database of the ATM service useby respondents in JjJekasiCity. The data base covered the locations of the ATMsthe respondents visited and their reasons for choosing those locations. The nextstep was to perform the network and spatial analysis by using Arc View GIS 3.x todetermine the optimal service locations. The research result shows that: 1) Thelocations of ATM placement were mostly found in areas of trade and service,industry and regular residence, 2) The orientation of ATM location developmentrequired by the people was on regular and irregular residence considering theshort distance, 3) In determining optimal ATM locations attention must be paid tothe parameter of distance between the location and trade and service areas as wellas the regular residence. The use of network analysis is indeed helpful indeveloping model of the service location in the determination of optimal servicearea.

Perbandingan Akurasi Klasifikasi Penutup Lahan Hasil Penggabungan Citra ALOS AVNIR-2 dan ALOS PALSAR pada Polarisasi Berbeda dengan Transformasi Wavelet

Jurnal Bumi Indonesia Volume 1, Nomor 2, Tahun 2012
Publisher : Fakultas Geografi UGM

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Abstract

Penggabungan citra merupakan salah satu alternatif dari penggunaan citra penginderaan jauh yang konvensional atau secara individu. Penelitian ini mengkaji peningkatan akurasi klasifikasi citra ALOS PALSAR yang digabungkan dengan citra ALOS AVNIR-2.Transformasi wavelet digunakan dalam proses penggabungan citra, mengacu pada kemampuannya mempertahankan kualitas spektral citra. Akurasi total dan indeks kappa pada citra ALOS AVNIR-2 85.26% dan 78.90%, pada citra gabungan I (Citra ALOS AVNIR-2, ALOS PALSAR polarisasi HH) 76.84%  dan 67.06%, pada citra gabungan II (Citra ALOS AVNIR-2, ALOS PALSAR polarisasi HV) 71.58% dan 58.64%. Ditinjau dari hasil tersebut citra gabungan mempunyai akurasi yang lebih rendah daripada citra ALOS AVNIR, namun dibanding pada hasil klasifikasi citra ALOS PALSAR polarisasi HH (59.38% dan 45.97%) dan citra ALOS PALSAR polarisasi HV (64.06% dan 49.55%) proses penggabungan citra yang dilakukan menunjukkan peningkatan akurasi.Kata kunci: Penggabungan citra, Wavelet, Akurasi, Wang bovic, Maximum likelihood

PEMROGRAMAN ’VIRTUAL STEREOPLOTTER’ SEBAGAI PROGRAM SPASIAL PENGHASIL DIGITAL SURFACE MODEL DARI FOTO UDARA STEREO DIGITAL

Jurnal Bumi Indonesia Volume 1, Nomor 2, Tahun 2012
Publisher : Fakultas Geografi UGM

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Abstract

Tujuan dari penelitian ini adalah untuk menciptakan Virtual Stereoplotter sebagai program spasial pengolah foto udara stereo digital untuk menghasilkan Digital Surface Model (DSM). Virtual Stereoplotter dibangun menggunakan software Visual Basic 2010 Express dengan mengintegrasikan berbagai component dan library open source antara lain DotSpatial 1.2, GeoStatisticalTool, MathNet.Numerics dan ZedGraph. Virtual Stereoplotter mampu melakukan proses Interior Orientation, Cross Correlation, Single Model Bundle Adjustment, Inverse Distance Weighted dan Median Filtering hingga diperoleh DSM dalam format raster yang sudah bereferensi spasial. Dua pasang stereopair FUFK dan hasil pengukuran lapangan dengan GPS digunakan sebagai bahan untuk menguji akurasi DSM yang dihasilkan melalui program Virtual Stereoplotter. Stereopair pertama mampu menghasilkan DSM sebagian daerah Parangendog dengan akurasi vertikal sebesar 7.965 meter pada tingkat kepercayaan 90%. Stereopair kedua mampu menghasilkan DSM sebagian daerah Depok dengan akurasi vertikal sebesar 5.108 meter pada tingkat kepercayaan 90%. Kualitas dan akurasi DSM dipengaruhi oleh kualitas FUFK, kualitas GCP, dan kualitas Tie Point.Kata kunci : Fotogrametri Digital, Model Permukaan Digital

Fuzzy Neural Network Capability Studies in Land Cover Perpiksel Based Classification Using Landsat7 ETM+

Jurnal Bumi Indonesia Volume 2, Nomor 1, Tahun 2013
Publisher : Fakultas Geografi UGM

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Abstract

Variasi kondisi penutup lahan di permukaan bumi menyebabkan sistem klasifikasi dengan pendekatan parametrik (maximum likelihood) cenderung kurang baik dalam mengklasifikasikan penutup lahan pada subkelas yang lebih detil jika dibandingkan dengan pendekatan non-parametrik. Sementara, pendekatan non-parametrik dengan sistem hard classifier secara teori juga tidak mampu memberikan hasil yang lebih baik pada batas samar tiap piksel kelas penutup lahan jika dibandingkan dengan sistem soft classifier. Peneltian ini bertujuan untuk mengetahui akurasi hasil klasifikasi perpiksel penutup lahan menggunakan metode Fuzzy neural network (FNN). Penelitian ini menggunakan citra Landsat 7 ETM+. Citra ini diklasifikasikan dengan menggunakan 3 sistem klasifikasi yakni maximum likelihood, artificial neural network (non parametrik), dan FNN (fuzzy logic - non parametrik). Hasil penelitian menunjukkan FNN mampu memberikan akurasi yang jauh lebih baik dibandingkan dengan 2 sistem klasifikasi lainnya. FNN dengan dan tanpa data gabungan masing-masing memberikan akurasi sebesar 78.87% dan 80.41%. Sementara itu, sistem klasifikasi lainnya memberikan akurasi dibawah 65%.Kata Kunci; pendekatan parametrik, artificial neural network, fuzzy neural network, penutup lahan, akurasi

Remote Sensing and GIS for Surface Water Resources in Rawa Biru – Torasi Merauke Papua

Forum Geografi Vol 20, No 1 (2006): July 2006
Publisher : Universitas Muhammadiyah Surakarta

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Abstract

The research describe about surface water ecosystem study in Merauke Papua by using multisource and multistage remote sensing data which was splitted into two parts based on the study areas. First, it is for micro scale spatial analysis focusing on the Rawa Biru – Torasi watershed, while the second is for macro scale spatial analysis for Transfly ecoregionin the floodplain areas of Merauke. Multispectral approach was adopted for Landsat image analysis, followed by field survey on the selected areas. Auxilary data used are maps, secondary documents in order to improve understanding of the areas. Interview and discussion with related institutions (Wasur National Sanctuary, Potable Water Services, Internal Affairs Government, Forestry Service) accordingly were carried out. The research result showed that remote sensing imagery are usefull for surface water resources study. Physical condition of the Rawa Biru – Torasi watershed, vegetation analysis by using multitemporal data, wetland type, hydrological process in the floodplain were presented. Rawa Biru watershed as a resource for drinking water supply environmentaly decreased considerably due to the species invasion, with successively dominated by hydrophilla, tebu rawa, rumput pisau, dan Mellaleuca and sedimentation took place in the main body of swamp. Upper part of the watershed is actually included in the Papua New Guinea, in long water resources development scheme, it need administratively belong to one recharge areas for the watershed.

Metode CTA dengan Teknik Data Mining Citra Landsat-8 untuk Klasifikasi Penggunaan Lahan

Majalah Geografi Indonesia Vol 29, No 2 (2015): September 2015
Publisher : Fakultas Geografi, Universitas Gadjah Mada

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Abstract

ABSTRAK Kajian mengenai metode non-parametrik Classification Tree Analysis (CTA) menggunakan teknik data mining untuk aplikasi penginderaan jauh masih belum banyak dilakukan. Sehingga diperlukan penelitian mengenai kemampuan CTA dalam menangani data yang cukup banyak, dengan memanfaatkan kelebihan CTA untuk aplikasi penginderaan jauh. Kombinasi parameter CTA dan data masukan, serta penerapannya pada dua skema klasifikasi yang berbeda tingkat kerinciannya, memerlukan pengujian terkait dengan tingkat akurasi yang dihasilkan. Penelitian ini bertujuan melakukan simulasi dari beberapa kombinasi parameter untuk mengetahui tingkat akurasi hasil klasifikasi, dan memperoleh pohon keputusan dari hasil KDD. Serta menganalisis akurasi metode non-parametrik CTA dengan teknik data mining untuk klasifikasi penggunaan lahan menggunakan citra Landsat-8 OLI,dan menerapkan hasil KDD pada daerah lain. Klasifikasi diperoleh dengan melakukan simulasi beberapa parameter CTA dan data masukan. Parameter aturan pemisah (splitting rules) dalam CTA, yaitu Ratio, Entropy, dan Gini. Parameter pemangkas (pruning), yaitu 0%, 1%, 5%, dan 10%.Beberapamasukan data klasifikasi, antara lain adalah citraLandsat-8 tujuhsaluran, transformasi citra (NDVI, NDWI, BI, NDBI, dan PCA), serta filter tekstur variance danmean(jendela bergerak 3x3 dan 5x5). Data non-spektral, yaitu data ketinggian dan data kemiringan lereng. Dua tingkat skema klasifikasi penggunaan lahan, yaitu Level I (5 kelas) dan Level II (8 kelas). Pohon keputusan yang diperoleh dari hasil pembelajaran dengan akurasi terbaik kemudian diterapkan pada daerah lain yang memiliki karakteristik mirip. Hasil penelitian menunjukkan bahwa kombinasi parameter terbaik adalah atribut pemisah Gini,pruning 1%, filter tekstur dengan jendela bergerak 5x5, dan skema Level I yaitu dengan akurasi keseluruhan 96,71%, kappa 0,9504, dan waktu proses 3,388 detik. Penerapannya pada daerah lain, menghasilkan akurasi keseluruhan 93,27% dengan kappa 0,8923. Tingkat akurasi terbaik yang diperoleh pada daerah penelitian maupun penerapannya pada daerah lain, lebih besar dari 90%.Sehinggadiharapkanmetode ini dapat menjadi alternatif metode untuk terapan kebijakan penggunaan lahan, dan klasifikasi penggunaan lahan berbasis penutup lahan setara dengan skala 1:100.000. ABSTRACT The study of non-parametric methods Classification Tree Analysis (CTA) using data mining techniques for remote sensing applications is still much to do, so it require studies on the CTAs ability to handle quite a lot of data, by utilizing CTA advantages for remote sensing applications. The combination of parameter CTA and data input, as well as its application on two different detail levels of land use classification scheme, require testing related to the level of accuracy that is generated. This studies aimed to simulate multiple combinations of parameters to determine the level of accuracy of the classification results, and obtain a decision tree from KDD results. And to analyze the accuracy of non-parametric methods CTA with data mining techniques for land use classification using Landsat-8 OLI, and apply the results of KDD on another area. The classification is obtained by performing simulations on several parameters CTA and data input. There are three splitting rules parameter in CTA, i.e. Ratio, Entropy, and Gini. Pruning parameter, i.e. 0%, 1%, 5%, and 10%. There are several inputs of the classification data, namely seven bands of Landsat-8 OLI imagery, image transformation (NDVI, NDWI, BI, NDBI, and PCA), as well as texture filter variance and texture filter mean (moving window 3x3 and 5x5). Non-spectral data, i.e.elevation data and slope data. And two-level land use classification scheme, i.e. Level I (5 classes) and Level II (8 classes). The decision tree that obtained from the best accuracy of the learning outcomes then applied to another area with similar characteristics. The results showed that the best parameter combination are a splitting attribute Gini, pruning 1%, texture filter with 5x5 moving window,and Level I scheme, with an accuracy of 96.71%, kappa 0.9504, and processing time 3.388 sec. Its aplication on another area, resulting an overall accuracy 93.27% with kappa 0.8923.The best accuracy rate obtained in this study and its application on another area was greater than 90%. Therefore this method is expected could be an alternative method for land use policy application, and land use classification based on land cover commensurate to a scale of 1:100,000.

Remote Sensing and GIS for Surface Water Resources in Rawa Biru – Torasi Merauke Papua

Forum Geografi Vol 20, No 1 (2006): July 2006
Publisher : Universitas Muhammadiyah Surakarta

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Abstract

The research describe about surface water ecosystem study in Merauke Papua by using multisource and multistage remote sensing data which was splitted into two parts based on the study areas. First, it is for micro scale spatial analysis focusing on the Rawa Biru – Torasi watershed, while the second is for macro scale spatial analysis for Transfly ecoregionin the floodplain areas of Merauke. Multispectral approach was adopted for Landsat image analysis, followed by field survey on the selected areas. Auxilary data used are maps, secondary documents in order to improve understanding of the areas. Interview and discussion with related institutions (Wasur National Sanctuary, Potable Water Services, Internal Affairs Government, Forestry Service) accordingly were carried out. The research result showed that remote sensing imagery are usefull for surface water resources study. Physical condition of the Rawa Biru – Torasi watershed, vegetation analysis by using multitemporal data, wetland type, hydrological process in the floodplain were presented. Rawa Biru watershed as a resource for drinking water supply environmentaly decreased considerably due to the species invasion, with successively dominated by hydrophilla, tebu rawa, rumput pisau, dan Mellaleuca and sedimentation took place in the main body of swamp. Upper part of the watershed is actually included in the Papua New Guinea, in long water resources development scheme, it need administratively belong to one recharge areas for the watershed.

Tidal Correction Effects Analysis on Shoreline Mapping in Jepara Regency

Journal of Applied Geospatial Information Vol 2 No 2 (2018): Journal of Applied Geospatial Information (JAGI)
Publisher : Politeknik Negeri Batam

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Abstract

The existence of high-spatial resolution imagery that are now available free by Planet Labs opens up opportunities in detailed scale mapping research, both as basic data and as reference data for geometry accuracy assessment. However, the use of several satellite sensors types with different recording times is the biggest obstacle in the use of high spatial resolution imagery as reference data because the shoreline instantaneous imaging at the data acquisition time does not consider the spatial and temporal variability of the shoreline boundaries. The purpose of this study was to analyze the effect of tidal correction on shoreline mapping in Jepara Regency using Landsat 8 OLI imagery in 2018.The effect of tidal correction analysis is done by comparing the position of the shoreline corrected by tides with the shoreline that is not corrected for tides. The influence of tidal correction is marked by differences in the position of the two shorelines. Shoreline shift calculation when there is a difference in tidal conditions between the test shoreline and the reference shoreline is carried out using the theory of right triangle (also called as one-line shift method).Based on the analysis of tidal correction effects, it is known that the shift in shoreline position after tidal correction varies from 0.21 m to 1.8 m, the value does not exceed one pixel of the PlanetScope image (3 m) so that tidal correction does not needs to be done because the effect is insignificant and undetectable on PlanetScope imagery. Keywords: tidal correction, shoreline, Planetscope, Landsat 8 OLI, Jepara