ANALISIS MODEL GEOSTATISTIK KRIGING ORDINARY UNTUK PREDIKSI TREND KENAIKAN NILAI LAHAN DI WILAYAH SEKITAR EXIT TOLL SOROJA

• Main Author: Nindi Risna Dewi, - (Author)
• Format: Book
• Published: 2019-03-11.
• Subjects: Thesis; NonPeerReviewed
• Online Access: Link Metadata
• Notes: http://repository.upi.edu/48365/1/S_GEO_1405415_Abstract.pdf; http://repository.upi.edu/48365/2/S_GEO_1405415_Title.pdf; http://repository.upi.edu/48365/3/S_GEO_1405415_Table_of_content.pdf; http://repository.upi.edu/48365/4/S_GEO_1405415_Chapter%201.pdf; http://repository.upi.edu/48365/5/S_GEO_1405415_Chapter%202.pdf; http://repository.upi.edu/48365/6/S_GEO_1405415_Chapter%203.pdf; http://repository.upi.edu/48365/7/S_GEO_1405415_Chapter%204.pdf; http://repository.upi.edu/48365/8/S_GEO_1405415_Chapter%205.pdf; http://repository.upi.edu/48365/9/S_GEO_1405415_Bibliography.pdf; http://repository.upi.edu/48365/10/S_GEO_1405415_Appendix.pdf
• Keywords: G Geography (General); L Education (General)

Pembangunan Jalan Tol Soroja mempengaruhi perkembangan wilayah disekitarnya. Laju pertumbuhan penduduk, pertumbuhan perekonomian, perubahan tata guna lahan, serta pembangunan infrastuktur dengan cepat berkembang di wilayah sekitar exit toll. Kondisi wilayah yang menguntungkan meningkatkan permintaan lahan, sehingga terjadi kenaikan nilai lahan di wilayah sekitar exit toll. Mengingat fungsinya yang banyak maka, informasi berupa Peta Zona Nilai Lahan penting diperbaharui dan disesuaikan dengan perkembangan nilai lahan yang terjadi di wilayah tersebut. Penelitian ini bertujuan untuk memprediksi trend kenaikan nilai lahan untuk dimodelkan dalam Geostatistik Kriging Ordinary dan menganalisis perubahan karakteristik spasial (peri-urbanisasi) sebagai dampak pembangunan jalan tol. Metode yang digunakan adalah kuantitatif deskriptif dengan analisis spasial dan pendekatan Sistem Informasi Geografis (SIG).. Hasil analisis Geostatistik terhadap root mean squere standardized, mean standardized, average standard error dan root mean squere pada 11 model semivariogram menunjukkan, model K-Bessel dengan type sector 1dan neighborhood type smooth paling memenuhi standar penilaian sehingga, tepat digunakan dalam pemetaan Zona Nilai Lahan. Tingkat keakuratan peta dihitung melalui besar deviasi hasil cross validation data peta pemodelan dengan data ground check.. Diketahui besar deviasi predicted data ground check sampel nilai lahan sebesar Rp.679.684 dan predicted data hasil pemodelan sebesar Rp.606.020. Hal tersebut membuktikan bahwa Peta Zona Nilai Lahan hasil pemodelan memiliki keakuratan yang lebih baik. Dalam penerapannya, proses pemilihan data sampel nilai lahan perlu diperhatikan kerapatan serta persebarannya untuk menyempurnakan hasil pemodelan. Construction of Soroja Toll Road affected to the development of surrounding area. Population growth rate, economics, land use changes, and infrastructure development are rapidly in around the toll exit area. Favorable regional condition causing to increase land demand, the impact give influence to improve land value in around area toll exit. Cause it has so many functions, information land value zone map important to have update and adjusted to development land value which happen that area. This study aims to have prediction about land value adjusted trend for modeling Kriging Ordinary Geostatistical and for analysis spatial characteristic changes (peri-urbanitation) which as impact of road toll building. The method used is quantitive descriptive with spatial analysis and Geopraphic Information System (GIS) approach. Spatial development plans and inflation are indicators for predicting trend of increasing land values. Geostatistical analysis give result of standardized root mean squares, mean standardized, average standard error and root mean squere in 11 semivariogram models show is k-Bessel model with type 1 and neighborhood type smooth its best have assessment standard for use to mapping Land Value Zone. Grade accuracy of map is calculated through deviation magnitude result cross validation modeling map data with ground check data. The result known deviation magnitude of predicted ground check data is Rp.679,684 and predicted modeling data is Rp.606,020.This proves that the Land Value Zone Map modeling result have better accuracy. In its application, the process of selecting sample data for land values need to be considered by density and distribution to improve the modeling result