<![CDATA[Abstrak. Dua variabel digunakan untuk memaparkan variabilitas spasial hujan harian di Jawa Timur, yaitu: (1) Hujan-24jam-maksimal dan (2) Hari-Hujan. Data hujan diperoleh dari 946 lokasi stasiun hujan yang tersebar merata di seluruh wilayah Provinsi. Analisis spasial dilakukan menggunakan ESDA (Exploratory Spatial Data Analysis) yang ada pada ArcGIS Geostatistical Analyst. Tool yang digunakan mencakup: Histogram dan QQ-Plot. Selanjutnya, peta distribusi spasial (hujan-24jam-maksimal dan hari-hujan) di seluruh wilayah Jawa Timur dibuat dengan menggunakan metode Interpolasi Inverse Distance Weigthing (IDW). Hasil analisa menunjukkan Histogram dan Normal QQ-Plot untuk hari-hujan mendekati distribusi normal, sedangkan untuk hujan-24jam-maksimal lebih condong ke kanan. Statistik nilai hujan-24jam-maksimal yang diperoleh adalah: minimal = 32 mm, rerata = 137 mm, maximum = 332 mm, and median = 130 mm/hari. Nilai ringkasan distribusi statistik lainnya adalah:Â standar deviasai = 50,37; koefisien kemencengan = 0,99; dan koefisien kurtosis = 4,3. Statistik untuk variabel hari-hujan, menunjukkan nilai minimal = 4 hari/tahun dan maksimal = 184 hari/tahun. Sedangkan, nilai rerata = 81 hari/tahun dan nilai median = 80 hari/tahun. Histogram juga menampilkan nilai standar deviasi = 23,74; koefisien skewness = 0,28; dan koefisien curtosis = (3,6). Penelitian menunjukkan kemampuan dan manfaat ESDA untuk menggambarkan variabilitas spasial hujan harian dengan lebih detail.Abstract. Two variabel (maximum-24hour-rainfall and number of rainfall-day) were used to describe the spatial variabiity of Daily Rainfall phenomena in East Java regions. Daily rainfall data were collected from 946 pluviometres spread around the regions. Spatial analyst were exploited by means of Exploratory Spatial Data Analysis (ESDA) available at ArcGIS Geostatistical Analyst. Histogram and QQ-Plot were used for the analysist. Furthermore, thematic map visualized the spatial variability of daily rainfall data over the region was produced using Inverse Distance Weighting (IDW) interpolation method. Results shows that both Histogram and Normal QQ-Plot for number-ofrainffal-day are close to normal distribution, however spatial distribution of 24-hour rainfall data is quitely distorsed to standard normal distribution. Statistical resume obtained from 24hour-rainfall data are : minimum = 32 mm/day, average = 137 mm/day, maximum = 332 mm/day, median = 130 mm/day, standard deviation = 50,37, coefficient of skewness = 0,99, and Coefficient of Curtosis = 4,3. Other statistical value resumed from number of rainy-day are : minimum = 4 day/year, average = 81 day/year, maximum = 184 day/year, and median = 80 day/year, standard deviation = 23,74, coefficient of skewness = 0,28, and Coefficient of curtosis = 3,6. The research demonstrate the capability and benefit of those statistical tool to describe spatial variability of daily rainffal phenomenon in East Java Regions.]]>
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