Rokhana Dwi Bekti

MANOVA Statistical Analysis of Inorganic Compounds in Groundwater Indonesia

The present study was carried out to determine levels of inorganic compounds contained in the ground water and Reverse Osmosis (RO) water filtration result. The data in groundwater samples was collected from Bekasi, Tangerang and Jakarta in Indonesia. A total of 30 samples were collected and analyzed for the determine Cadmium (Cd), Chromium (Cr), Manganese (Mn), Cyanide (CN) and Lead (Pb). The results of the study revealed that in groundwater, the average of Cd 0.0058 mg / l, Mn 1.5233 mg / l, Cr 0.0127 mg/l, Pb 0.0060 mg / l, and CN 0.0040 mg / l. The level of RO result were: Cd 0.0027 mg / l, Mn 0.1767 mg / l, Cr 0.0024 mg / l, Pb 0.0021 mg / l, and CN 0.0023 mg / l . This means that Cd and Mn in ground water were higher than the values recommended by PAK-EPA and WHO or the standard of Indonesian Ministry of Health. But after filtration Reverse Osmosis (RO) Mn and Cd levels decreased to levels below the standardized value. By comparing of mean in MANOVA and nonparametric MANOVA in α=5%, there are differ...

Spatial pattern of diarrhea based on regional economic and environment by spatial autoregressive model

The diarrhea case pattern information, especially for toddler, is very important. It is used to show the distribution of diarrhea in every region, relationship among that locations, and regional economic characteristic or environmental behavior. So, this research uses spatial pattern to perform them. This method includes: Morans I, Spatial Autoregressive Models (SAR), and Local Indicator of Spatial Autocorrelation (LISA). It uses sample from 23 sub districts of Bekasi Regency, West Java, Indonesia. Diarrhea case, regional economic, and environmental behavior of households have a spatial relationship among sub district. SAR shows that the percentage of Regional Gross Domestic Product is significantly effect on diarrhea at α = 10%. Therefore illiteracy and health center facilities are significant at α = 5%. With LISA test, sub districts in southern Bekasi have high dependencies with Cikarang Selatan, Serang Baru, and Setu. This research also builds development application that is based on java and R to sup...

Ordinary Kriging and Spatial Autocorrelation Identification to Predict Peak Ground Acceleration in Banda Aceh City, Indonesia

Peak ground acceleration (PGA) is a measure of earthquake acceleration in the ground. The prediction information about PGA is important to minimize the effect of earthquake. The method for prediction is Ordinary Kriging. It is geostatistic method used to predict data in certain locations which have autocorrelation. The sample data used in this research are PGA in Meuraxa, Banda Aceh 2006. The steps of research methodology consist of autocorrelations identify by Moran’s I and LISA, build semivariograms, and prediction by Ordinary Kriging. The results is Ordinary Kriging can be applied to predict PGA. It was shown by evaluate of mean and MSE value. According to mean value of three prediction, all models (Gaussian, Spherical, and Exponential) have mean 0,3534; 0,3584; and 0,3555 which approaches the actual PGA mean 0.34. According to MSE value, it can be seen that all models have small MSE or relatively closed to zero.

Earthquake Ground Motion Attenuation Modeling Using Levenberg-Marquardt and Brute-Force Method

In this paper, we discuss the results of research on the optimization modeling of ground motion attenuation in the subduction zone of the model Youngs et al. [1] using two methods: the Levenberg-Marquard and Bruce-Force method. This modeling is particularly important in the case of seismicity. Given that it takes a good model for predicting the strength of earthquakes in order to reduce the risk of the impact of natural disasters. Two major contributions of this study are ground motion attenuation model specific to the subduction zone that has been optimized with the Levenberg-Marquard method and Bruce-Force uses a model Youngs et al. [1] and a proof that the Levenberg-Marquard method for optimization model is better than Bruce-Force method. The Levenberg-Marquardt method has been proven to provide more accurate results on the modeling of ground motion attenuation which is indicated by a very small deviation between the values of PGA predictable results with the PGA actual values.

Computer-Based Ground Motion Attenuation Modeling Using Levenberg-Marquardt Method

In this paper, we present the results of research on the optimization modeling of ground motion attenuation of the two establish models by Youngs et al. [25] and the model of Lin and Lee [13] using the Levenberg-Marquardt method. This modeling is particularly important in the case of ground motion given that it takes a good model for predicting the strength of earthquakes in order to reduce the risk of the impact of the natural disaster. There are two main contributions of this research is the optimization of ground motion attenuation models with Levenberg-Marquardt method on two models that have been extensively used and the development of computer applications to help accelerate modeling, especially on large data with an area of extensive research. Levenberg-Marquardt method proved to give a good contribution to the modeling of ground motion attenuation that is indicated by the very small deviations between the predicted values with the actual value.

Spatial Autocorrelation of Inorganic Compound in Groundwater

The water quality at a location is influenced other locations. Characteristics of groundwater quality in some locations were spatially auto correlated. Such as in Jakarta, Indonesia, if the water source in one location is polluted so can lead to polluted water sources at a different location which close together. This research was analyzing the content of inorganic compounds in Jakarta, Indonesia. The analysis was performed using spatial methods to obtain the relationship among locations of ground water quality. The samples were ten locations in East, West, Central, North, and South Jakarta. Spatial methods conclude that there were spatial autocorrelation in inorganic compounds of groundwater in Jakarta, specifically in Cadmium (Cd). Moran’s I test shows that there are dependencies of Cd among 10 samples at α = 10%. Meanwhile, Mn, CN, Cr, and Pb haven’t dependencies. By LISA test, there were the first sample in West Jakarta and seventh sample in East Jakarta which significant affects with other location at α = 5%. P value in area west, north, and east of Jakarta were lower than others. So, the samples in these areas have dependencies than in south area.