Shailla Rustiana | Bogor Agricultural University, Indonesia (original) (raw)

Papers by Shailla Rustiana

Curah hujan merupakan salah satu faktor yang paling berpengaruh dalam kehidupan. Dalam bidang per... more Curah hujan merupakan salah satu faktor yang paling berpengaruh dalam kehidupan. Dalam bidang pertanian, curah hujan kerap kali menjadi penyebab kegagalan panen karena kondisinya yang ekstrem, baik itu menyebabkan tanah sangat kering maupun banjir. Hal tersebut melatar belakangi penelitian ini mengingat prediksi akan curah hujan sangat penting, bukan hanya bagi petani, tapi juga bagi para pekerja di sektor sektor lainnya, seperti perikanan, pertambangan, industri, dan sebagainya. Dari berbagai prediksi curah hujan yang sering dilakukan, metode secara statistik diyakini memberikan hasil yang signifikan dalam melakukan prediksi, karena dapat memprediksi data deret waktu dalam jangka panjang. Beberapa metode statistik yang umum digunakan adalah SARIMA (musiman ARIMA) dan SSA. Pada penelitian ini, peramalan dilakukan terhadap curah hujan kota Bogor dengan tahun pengamatan 2007-2016. Peramalan dilakukan 1 tahun terakhir (2016) dengan menggunakan SARIMA dan SSA. Peramalan dengan SARIMA da...

Curah hujan dengan intensitas yang tinggi di Provinsi DKI Jakarta tak jarang menyebabkan bencana ... more Curah hujan dengan intensitas yang tinggi di Provinsi DKI Jakarta tak jarang menyebabkan bencana banjir. Hal tersebut meresahkan warga sekitar karena bencana banjir yang terjadi dapat menyebabkan kerugian material akibat terhambatnya dan terganggunya aktivitasÂ indutri di DKI Jakarta. Maka diperlukan suatu metodeÂ prediksiÂ curahÂ hujanÂ yangÂ diharapkanÂ jugaÂ dapatÂ menjadiÂ mitigasiÂ bencanaÂ banjirÂ olehÂ warga sekitar. Dari berbagai metode prediksi berbasis analisis statistik, dikenal sebuah metodeÂ multivariate time seriesÂ padaÂ beberapaÂ lokasiÂ yangÂ disebutÂ GeneralizedÂ SpaceÂ Time AutoregressiveÂ (GSTAR)Â dengan penyelesaian efek heteroskedastisitas autokorelasi (ARCH),Â bernama GSTAR-ARCH. Pada penelitian ini metodeÂ GSTAR-ARCHÂ diterapkanÂ padaÂ dataÂ curahÂ hujanÂ bulananÂ padaÂ musimÂ penghujan,Â DesemberJanuari-Februari (DJF) hasil ekstrak data reanalisis satelit dengan korelasi yang tinggi dari CHIRPS untuk wilayah Jakarta Pusat...

As one of the most important region located along the belt equator, the meteorological surface pa... more As one of the most important region located along the belt equator, the meteorological surface parameter over the Indonesia Maritime Continent (IMC) suspected effecting by the Monsoon system. This is caused IMC is located between two great continent (Asia and Australia) and two great ocean (Indian and Pacific). It indicates that the Sea Surface Temperature (SST) should become one of the most important parameter. Although, this region is effected by the Monsoon system, but another phenomena, called as the Indian Ocean Dipole (IOD) and El Nino suspected has a great effects also in determining the rainfall anomalies. By this reason, we investigated the IOD and El-Nino index, especially the SST Nino 3.4 index. By assuming the drought and wet extreme condition was mostly affected by both parameter, we analyzed the IOD and SST Nino 3.4 index for period of 1976 to 2000. For study case, we concentrated to analyse the monthly rainfall data over Java Island, especially when the strongest El N...

PenerapanÂ metodeÂ ordinaryÂ kriggingÂ dalamÂ memprediksiÂ dataÂ padaÂ lokasiÂ takÂ ter... more PenerapanÂ metodeÂ ordinaryÂ kriggingÂ dalamÂ memprediksiÂ dataÂ padaÂ lokasiÂ takÂ tersampelÂ berdasarkan observasiÂ padaÂ lokasiÂ yangÂ tersampelÂ yangÂ beradaÂ diÂ sekitarnyaÂ mensyaratkanÂ semivariogramÂ dalam menentukanÂ besarÂ bobotÂ krigingnya.Â HalÂ terpentingÂ dalamÂ semivariogramÂ adalahÂ pemilihanÂ model semivariogramÂ teoretisÂ yangÂ sesuaiÂ yangÂ mensyaratkanÂ jumlahÂ pasanganÂ dataÂ yangÂ cukupÂ besarÂ yang disusun berdasarkan jarak antar lokasi. Hal tersebut menjadi kendala ketika dilakukan prediksi data inflasi padaÂ lokasiÂ takÂ tersampelÂ dimanaÂ hanyaÂ adaÂ sedikitÂ lokasiÂ tersampelÂ diÂ setiapÂ provinsi.Â MakalahÂ ini menerapkanÂ metodeÂ OrdinaryÂ KrigingÂ untukÂ memprediksiÂ dataÂ inflasiÂ diÂ beberapaÂ kabupaten/Â kotaÂ di Sumatera Utara dengan semivariogram linear pada dua lokasi tersampel. Hasil penerapan metode tersebut mengahasilkan taksiran nilai di titik tidak tersampel dengan variansi...

Difteri merupakan penyakit menular yang menyerang saluran pernafasan bagian atas dan terlihat sel... more Difteri merupakan penyakit menular yang menyerang saluran pernafasan bagian atas dan terlihat selaput putih kotor yang semakin lama akan membesar yang akan mempersempit saluran pernafasan. Penyakit difteri merupakan kejadian luar biasa (KLB), yaitu penyakit yang sebelumnya memiliki jumlah kasus yang sedikit tetapi mengalami peningkatan pesat.Jumlah kasus difteri merupakan data count yang mengikuti distribusi poisson sehingga untuk mengetahui faktor-faktor yang berpengaruh terhadap kasus difteri menggunakan analisis regresi Poisson. Regresi Poisson mensyaratkan kondisi dimana nilai mean dan variansi dari variabel respon bernilai sama. Namun, adakalanya terjadi fenomena overdispersi dalam data yang dimodelkan dengan distribusi Poisson. Pada penelitian ini dilakukan analisis dengan memperhatikan excess zero dan overdispersi menggunakan regresi Zero Inflated Negative Binomial (ZINB) dan model regresi Hurdle Negative Binomial (HNB) pada kasus difteri di Indonesia. Hasil penelitian menunj...

Tingginya intensitas curah hujan (CH) yang terjadi di Indonesia belakangan ini tak lepas dengan t... more Tingginya intensitas curah hujan (CH) yang terjadi di Indonesia belakangan ini tak lepas dengan terjadinya bencana banjir bahkan beberapa daerah juga terjadi bencana longsor, hingga menyebabkan korban meninggal. CH dengan intensitas yang tinggi diketahui tidak hanya menyebabkan bencana banjir dan longsor, tetapi juga menyebabkan bencana hidrometeorologi lainnya. Di awal tahun 2017 ini, bencana akibat CH ekstrem terjadi di Kintamani-Bali dan DKI Jakarta. Untuk menganalisis kejadian bencana tersebut diperlukan data satelit dengan resolusi tinggi yang dapat mendukung pengamatan data insitu, guna dilakukannya proses prediksi CH untuk mitigasi bencana banjir dan longsor terjadi kembali. Pada penelitian ini dilakukan analisis data CH re-analisis dari Climate Hazard Group InfraRed Precipitation with Station (CHIRPS) daily-improve (pengamatan harian) dengan resolusi tinggi (0,05° x 0,05° ~ 5km) terhadap kejadian bencana banjir dan longsor di pulau Jawa dan Bali. Analisis dilakukan dengan me...

This study is mainly concerned an application of SST NiA±o 3.4, IOD and Monsoon index in determin... more This study is mainly concerned an application of SST NiA±o 3.4, IOD and Monsoon index in determining the upcoming of the extreme rainfall over the Indonesian Maritime Continent (IMC). As one of the most important region located along the belt equator, the meteorological surface parameter over the IMC suspected is effecting mostly by the Monsoon system. This is a unique country, since located between two great continent (Asia and Australia) and two great ocean (Indian and Pacific). It indicates that the Sea Surface Temperature (SST) should become one of the most important parameter. Although, this region is affected by the Monsoon system, but another event called as the Indian Ocean Dipole (IOD) and El NiA±o suspected has a great effects also in determining the rainfall anomalies, especially for the extreme conditions. By this reason, we investigated the IOD and El-NiA±o index signal, especially the SST NiA±o 3.4 index. By assuming the drought and wet extreme condition is mostly affe...

Journal of Physics: Conference Series, Oct 1, 2017

This study is mainly concerned in development one of the most important equatorial atmospheric ph... more This study is mainly concerned in development one of the most important equatorial atmospheric phenomena that we call as the Madden Julian Oscillation (MJO) which having strong impacts to the extreme rainfall anomalies over the Indonesian Maritime Continent (IMC). In this study, we focused to the big floods over Jakarta and surrounded area that suspecting caused by the impacts of MJO. We concentrated to develop the MJO index using the statistical model that we call as Box-Jenkis (ARIMA) ini 1996, 2002, and 2007, respectively. They are the RMM (Real Multivariate MJO) index as represented by RMM1 and RMM2, respectively. There are some steps to develop that model, starting from identification of data, estimated, determined model, before finally we applied that model for investigation some big floods that occurred at Jakarta in 1996, 2002, and 2007 respectively. We found the best of estimated model for the RMM1 and RMM2 prediction is ARIMA (2,1,2). Detailed steps how that model can be extracted and applying to predict the rainfall anomalies over Jakarta for 3 to 6 months later is discussed at this paper.

IOP Conference Series: Earth and Environmental Science

Climate phenomena that significantly affect Indonesian rainfall to be lower (positive) and higher... more Climate phenomena that significantly affect Indonesian rainfall to be lower (positive) and higher (negative) than normal conditions are ENSO and IOD. The other phenomenon with different time scale with ENSO and IOD is MCC that rainfall until causing storms. This study was conducted to determine the influence of ENSO and IOD during MCC to rainfall in Indonesia. The data used are monthly data of rainfall, Nino3.4-IOD index, and hourly MCC data derived from T bb data of Himawari Satellite, year 2001-2015 observation. The study focused on 4 occurrence phenomena: Nino3.4 (+) IOD (+), Nino3.4 (-) IOD (-), Nino3.4 (+) IOD (-), and Nino3.4 (-) IOD (+) with the distribution of 3 longitude regions (90-105E, 106-125E, and 126-140E). The results showed that the distribution of rainfall during MCC were higher when the events of negative IOD compared to other events, especially in the western maritime of Sumatra until Kalimantan. While, in the Nusa Tenggara region there is no rainfall when positi...

Journal of Physics: Conference Series

Rainfall prediction in Indonesia is very influential on various development sectors, such as agri... more Rainfall prediction in Indonesia is very influential on various development sectors, such as agriculture, fisheries, water resources, industry, and other sectors. The inaccurate predictions can lead to negative effects. Cimanuk watershed is one of the main pillar of water resources in West Java. This watersheds divided into three parts, which is a headwater of Cimanuk sub-watershed, Middle of Cimanuk sub-watershed and downstream of Cimanuk subwatershed. The flow of this watershed will flow through the Jatigede reservoir and will supply water to the north-coast area in the next few years. So, the reliable model of rainfall prediction is very needed in this watershed. Rainfall prediction conducted with Canonical Correlation Analysis (CCA) method using Climate Predictability Tool (CPT) software. The prediction is every 3months on 2016 (after January) based on Climate Hazards group Infrared Precipitation with Stations (CHIRPS) data over West Java. Predictors used in CPT were the monthly data index of Nino3.4, Dipole Mode (DMI), and Monsoon Index (AUSMI-ISMI-WNPMI-WYMI) with initial condition January. The initial condition is chosen by the last data update. While, the predictant were monthly rainfall data CHIRPS region of West Java. The results of prediction rainfall showed by skill map from Pearson Correlation. High correlation of skill map are on MAM (Mar-Apr-May), AMJ (Apr-May-Jun), and JJA (Jun-Jul-Aug) which means the model is reliable to forecast rainfall distribution over Cimanuk watersheds region (over West Java) on those seasons. CCA score over those season prediction mostly over 0.7. The accuracy of the model CPT also indicated by the Relative Operating Characteristic (ROC) curve of the results of Pearson correlation 3 representative point of sub-watershed (Sumedang, Majalengka, and Cirebon), were mostly located in the top line of non-skill, and evidenced by the same of rainfall patterns between observation and forecast. So, the model of CPT with CCA method is reliable to use.

Proceeding ofInternational Symposium on the 15th Anniversary of the Equatorial Atmosphere Radar (EAR), 2016

Indonesia's rainfall can't be separated from the influence of global climate phenomena, including... more Indonesia's rainfall can't be separated from the influence of global climate phenomena, including Madden-Julian Oscillation (MJO). Based on previous research, the active phase of MJO has a correlation with the high intensity of rainfall. MJO caused the high intensity of rainfall with saturated water vapor submissions from the Indian Ocean. This study aims to determine the effect of MJO activity when the occurrence of extreme rainfall events that caused flooding and landslides in the Western Region of Indonesia on June 2016. The data used are daily data Real Time Multivariate MJO (RMM1 and RMM2), Pentad MJO index, and hourly precipitation data from Global satellite Mapping (GSMaP), while the software used are GrADS (spatial analysis), Matlab (temporal analysis), and Microsoft Office. The resultsshowed that rainfall intensityof flood events in Padang (00.93S & 100.33E) that occurred on June 16, is high enough since 4-23 WIB, in the range 10-21 mm/hr. Meanwhile flood events and landslides in Purworejo (07.70S & 110.00E) on June 18, also showed high rainfall intensity from 4-22 WIB, in the range 12-21 mm/hr. The intensity of rainfall is included in the category of heavy to very heavy which causing floods. But, the value of RMM1 and RMM2 were in phase 2 and 3 (Indian Ocean), It have not yet entered thewestern part of Indonesian Maritime Continent (phase 4). The pentad MJO index values also classified in the category of weak in phase 4 (0.36), so the MJO has no significant effect on the flood events in the western region of Indonesia.

Climate predictions are very important for the people in various development sectors, such as agr... more Climate predictions are very important for the people in various development sectors, such as agriculture, forestry, fisheries, and industry. Java Island has the biggest population in Indonesia, causing almost all sectors of development centered on the island. The impact of extreme climate like dry season and rainy season that is longer than normal conditions, due to the phenomenon of ENSO and IOD greatly affect various sectors of life in Java Island. Therefore, climate predictions in Java Island is very interesting to study, consider this will be very useful for the community. This study was conducted in 1995-2014 observations using software Climate Predictability Tool (CPT) with Canonical Correlation Analysis (CCA) methods. Predictors used was the monthly data index of Niño3.4 + Dipole Mode (DMI), one month prior to the observation season (November for rainy season Desember-January-February (DJF) and May for dry season June-July-August (JJA)) while predictant was the rainfall data Climate Hazards InfraRed Precipitation Group with Station (CHIRPS) region of the Java island. The results of rainfall prediction CPT years 2013-2014 were compared with the results of spatial analysis using GrADS, which both have the same spatial distribution of the rainfall values average of 250-550 mm/month (DJF) and average of 0-300 mm/month (JJA). The accuracy of the model CPT was also indicated by the Relative Operating Characteristic (ROC) curve of the results of Pearson correlation of 5 representative points of observation (Jakarta, Bandung, Semarang, Yogyakarta and Surabaya), which were mostly located in the top line of non-skill, so that a reliable model of the CPT to use. Rainfall prediction of Java Island on rainy season DJF 2014/2015 shows rainfall value ranges from 200-600 mm/month with the highest peak rainfall in February while forecast on dry season JJA 2015 was in the range of 0-250 mm/month with the lowest rainfall peaks in August.

Keywords: CCA; CHIRPS; CPT; rainfall; ROC curve

Floods in the western part of Java Island area, including the Jakarta City, Bandung, Sumedang and... more Floods in the western part of Java Island area, including the Jakarta City, Bandung, Sumedang and Garut Regency is the most extreme incident like the incident in 2007. In 2016, flood occurred in March that caused the Citarum river overflowed. The overflowed of the Citarum river resulted in 15 regions in Bandung Regency were flooded (BNPB) and as many as 5,900 heads of households consisting of 24,000 inhabitants affected by the floods and more than 3,000 people displaced (BPBD Bandung). With this background, further analysis related to floods, especially from remote sensing is needed. This study was conducted to analyze the incidence of flooding in the western part of Java Island on March 12-13, 2016 with atmospheric parameters. The data used is the MODIS Near Real Time (NRT) Global Flood Mapping data with a resolution of 250m and daily rainfallsatellite data with GSMaP and reanalysis data from CHIRPS for the analysis of rainfall intensity during a flood. While the software used areQGIS, Google Earth, and GrADS. Observations flood MODIS image folder averaging 2 days (March, 12-13 2016) shows the floods are marked with red color found in Jakarta, Bandung, and partly in the area of Garut, Subang, Sumedang and Cirebon. MODIS image analysis in accordance with the spatial distribution of rainfall intensity averaging 2 days of GSMaP, which shows rainfall in these areas ranged from 20-80 mm/day were classified in the category of moderate to heavy rainfall by BMKG. Thus, the results of this study show that MODIS NRT imagery is good enough to analyze the flooding event in the western part of Java Island on March 2016.

Keywords: Floods, CHIRPS, GSMaP, MODIS

This study emphasized the importance of data analysis of El-Niño Modoki on the determination of t... more This study emphasized the importance of data analysis of El-Niño Modoki on the determination of the dry season in some areas in Riau Province. This is important because forest fires in Riau Province often occur almost every year, especially during the dry season. On this basis, it is necessary to do the analysis of the data of El-Niño Modoki Index (EMI). In addition, rainfall data were also analyzed in five observation points, Indragiri Hilir, Bengkalis, Pekanbaru, Kuantan Singingi, and Rokan Hilir respectively. Those data are extracted from the Tropical Rainfall Measurement Mission (TRMM) and the Climate Research Unit (CRU). The results showed that both anomalous rainfall data in five areas above were inversely proportional to the data of EMI. Here we can see the role of a strong El-Niño Modoki on dry season in Riau Province, as happened in the years 2002-2003, 2004-2005 and 2009-2010, respectively. The results of the analysis of spatial composite precipitation anomalies in the years above showed the decrease in the intensity of rainfall in the province of Riau, especially during the June-July-August (JJA) with a peak in August. The results of the spatial analysis of data turned out to be proportional to the EMI which is expressed in the correlation coefficient (R) of -0.66, particularly in Rokan Hilir, Riau.

Keywords: CRU; El Niño Modoki; Forest Fire; GrADS; TRMM

ENSO phenomenon is one of global climate change have an impact on various sectors including the a... more ENSO phenomenon is one of global climate change have an impact on various sectors
including the agricultural sector in Indonesia. Some of the province which is one of the
national food production centers West Sumatera are wet tropical climate and West Nusa
Tenggara are tropical climate, vulnerable to climate change. Therefore it is necessary to
analyze the impact of ENSO on rainfall variability in both provinces for 31 years (1982-
2012). Results composite anomalies of rainfall, SST and horizontal wind speed at an altitude
of 850 hPa in years condition of El Nino and La Nina spatially with software GrADS, showed
a decrease and increase rainfall than normal conditions in both provinces in the
SON(September-October-November) season. Seasonal rainfall prediction model using
software CPT with Principal Component Regression (PCR) analyze, results coefficient
principal component with variable estimation Nino3.4 in three region of the province of West
Sumatra highest in ASO(August-September-October) season which means the condition of El
Nino and La Nina affect precipitation in that season with highest impact in the Padang (0.53),
while the coefficient principal component in three region of the West Nusa Tenggara Province
highest in OND(October-November-December) season with the highest impact in Sumbawa
(0.69).

Keywords: CPT, El Nino, GrADS, La Nina, PCR, Rainfall

This study examines the differences of varians rainfall in Indramayu district, West Java about t... more This study examines the differences of varians rainfall in Indramayu district, West Java about the incidence of El Niño Modoki with EMI and El Niño with Niño3.4. The data rainfall used is the observation data and satelite data from Climate Research Unit (CRU). Based on the region of rainfall pattern, Indramayu patterned is monsoonal region wich occured 6 months rain season and 6 months dry season with rainfall peak December to January. Wavelet analysis of the SST anomaly Niño3.4 and EMI period 1979 – 2013 resulted differences temporal characteristics and determine the years of El Niño Modoki and El Niño conditions. The results strengthened with spatial analysis used GrADS which displays the distribution of rainfall on the Java island in period 1979-2012 as well as composite SST anomalies and 850 hPa wind speed data in period of El Niño Modoki and El Niño. The result of spatial analysis showed a decrease rainfall in Java Island is SON season. The decrease rainfall in El Niño Modoki and El Niño conditions then linked to the productivity of rice in Indramayu district, considering that Indramayu is one of the highest rice producing areas in Indonesia.

Keywords: El Niño Modoki, El Niño , Rainfall, GrADS, Productivity of Rice