Ima Kurniastuti
@unusa.ac.id
Information System
universitas nahdlatul ulama surabaya
RESEARCH INTERESTS
Image processing, information system
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Ima Kurniastuti, Ary Andini, and Paramitha Nerisafitra
AIP Publishing
Ima Kurniastuti, Hendik Eko Saputro, and Fajar Annas Susanto
AIP Publishing
Ubaidillah Zuhdi, Riyan Sisiawan Putra, Aditya Narendra Wardhana, Endah Tri Wahyuningtyas, Ima Kurniastuti, and Yauwan Tobing Lukiyono
DiscoverSys, Inc.
Background: Food is an essential thing in human activities. Therefore, it is said that agricultural sectors have a crucial role in human life. The purpose of this study is to analyze the role of the agricultural sector in the national economy of Indonesia. Method: The data used in this study are Indonesian input-output (IO) tables in 1990, 1995, and 2005. The analytical instrument of this research is IO analysis. This study uses more specific parts of the IO analysis such as simple household income multiplication, simple output multiplication, sensitivity distribution index, and power distribution index as analysis tools. The analysis of this research has a period of 1990-2005. In this study, the analyzed sectors are (1) paddy, (2) maize, (3) cassava, (4) other rootlcrops, including sweet potatoes, (5) groundnut, (6) soybeans, (7) other beans, (8) vegetables, (9) fruits, (10) cereals and other food crops, (11) rubber, (12) sugarcane, (13) coconut, (14) oil palm, (15) fibrelcrops, (16) tobacco, (17) coffee, (18) tea, (19) clove, (20) otherlestatelcrops, and (21) otherlagriculture. The first step of the methodology of this study is to describe the data, while the final step is to explain the study's conclusions and suggested further research. Results: The results show that, by using a simple output multiplier, the analyzed sectors did not include the top five Indonesian industries from 1990 through 2005. Conversely, one of the analyzed sectors, rubber, was admitted in the top five Indonesian industries in the period of the analysis from the point of view of another multiplier. Using both indices, almost all analyzed industries were consistent in the quadrant from 1990 through 2005. Conclusion: Indonesian government shall prioritize the rubber sector for the next economic development plans.
Muhammad Nazaaruddin, Ima Kurniastuti, Fajar Annas Susanto, Rizqi Putri Nourma Budiarti, Teguh Herlambang, Imam Wahyudi Farid, and Firman Yudianto
IEEE
In this study an evaluation of the website-based school library information system was done. The method is used in this study was Human Organization-Technology fit (Hot-Fit) method. The focus of this study was in terms of use, organization, technology and application benefits according to user needs. The stages of this research were problem identification, determining research respondents, creating questionnaires using hot-fit, distributing questionnaires, processing data, compiling results and analyzing them. The results show that there were 4 accepted hypotheses and 6 rejected hypotheses with details of t-statistics greater than 1.96, namely service quality affects system use with a t-statistic value of 2.808, system quality affects user satisfaction with a value t-statistic 1.975, system use has an effect on net benefits with a t-statistic value of 2.085, and organizational structure has an effect on net benefits with a t-statistic value of 3.317.
I Kurniastuti, E N I Yuliati, F Yudianto, and T D Wulan
IOP Publishing
Abstract The kidney is organ that plays an important role in the body’s metabolism, especially the process of filtration and reabsorption of food waste. Currently the determination of kidney parts through kidney histology is still done manually by experts based on experience and knowledge. Therefore, to make it easier to determine the parts of the kidney, a histological image segmentation of the kidney was carried out. In the segmentation process, it is necessary to extract the color features of the parts of the kidney, namely the glomerulus and proximal tubule. The color features used are Hue, saturation, value (HSV) color space. The hue means the representation of color type. The saturation defines the amount of white color is mixed with hue. The value in HSV color space denotes the intensity or lightness or brightness of the color. The method consists of three steps such as pre-processing step, extraction feature HSV and statistical analysis. The result of statistical analysis showed that the hue and value features, glomerulus and proximal tubule had different ranges of values. However, the features of saturation, glomerulus and proximal tubule is overlap.
Ima Kurniastuti, Tri Deviasari Wulan, and Difran Nobel Bistara
IEEE
Examination of blood chemistry, especially blood glucose, uric acid and cholesterol in the body is a test carried out in routine health checks or in the process of diagnosing a disease. The research aims to produce an android-based application that can determine and monitor the results of blood chemistry examinations that are user-friendly for the community. The research method is literature study, design flowchart, design user interface (UI), implement application, and testing application. The first stage is a literature study to collect data and information about blood chemistry followed by design application regarding the flowchart design and interface of the application. The next stage was implement application regarding the application implementation process based on the design application using android studio and testing application using black box testing, white box testing and user acceptance testing (UAT). Overall the application has been successfully designed and built according to the research method. The results of testing application show that the application runs well and there are no errors. This indicates that the application has been successful and can be used by the public as a supporting application in routine blood chemistry examinations.
Ima Kurniastuti, Ula Nur Rahmatin, Firman Yudianto, and Tri Deviasari Wulan
IEEE
Segmentation in digital pathology, especially kidney histology images, is still rarely done. The detection of parts of the kidney is done manually by an experienced laboratory which takes a long time. This paper proposed method of extracting color features in glomerulus and proximal tubule as the initial stage of segmentation. Data were kidney histology images. RGB color feature extraction is done by utilizing histogram. Histogram give information about highest frequency of intensity. Data analysis was statistically using grouped frequency distributions to obtain range number of RGB. The result was RGB in kidney histology image can be extracted and comparison of color components in RGB show that all component overlap in the glomerulus while in proximal tubule, blue component can be used as feature differentiator. The conclusion was RGB channel cannot be used as a distinguishing feature in the segmentation of parts of the kidney, especially the glomerulus and proximal tubule.
Tri Deviasari Wulan, Ima Kurniastuti, and Paramitha Nerisafitra
IEEE
Most hospitals and clinics use x-ray for diagnosis lung disease because the price is relatively cheaper than other lung diagnostic tools. In this research, the chest x-ray image is used as input to the program that consist of two categories such as lung cancer and healthy lung. Categorization images are done by a doctor. The research aimed to classify the X-ray image of the lungs between lung cancer and healthy lung. There are two main stages in this research, namely image processing and classification using a probabilistic neural network. The first step of image processing is preprocessing such as cropping, resizing, thresholding, and median filter. The next step is feature extraction using Haar wavelet transform. The feature of energy and coefficients of each subband produced by Haar wavelet transform is used as input in the classification process. The classification process used a Probabilistic Neural Network (PNN) method to distinguish between lung cancer and healthy lung. The training data used PNN show that all x-ray images could be correctly classified between lung cancer and healthy lung. While test results from PNN using new data obtained at 80 % accuracy rate in detecting abnormalities of the X-ray image of the lungs.
Ima Kurniastuti, Tri Deviasari Wulan, and Ary Andini
IEEE
Fingernail image color could be used for health diagnosis, such as detecting pancreatic condition as an indicator presence of diabetes mellitus risk. This paper focused on fingernail images as an early detection risk of diabetes mellitus. Therefore. the study aimed to analyze color features of fingernail images based on HSV (Hue, Saturation, Value) color space. The research data used fingernail images which were divided into three categories including normal, prediabetes, and diabetes data that according to blood glucose level. The data was cropped and extracted to each component of HSV color space. Analysis data was applied by grouping frequency distribution. The results revealed that among components of HSV, hue and value were overlapped between prediabetes and diabetes data. Component saturation had different range numbers in normal, prediabetes, and diabetes data. Therefore, it could be concluded that the HSV channel was considered as early detection of Diabetes Mellitus risk with fingernails image color as an object assay.
Ima Kurniastuti and Tri Deviasari Wulan
IEEE
This research has aim to segmentation of finger nails image using image processing methods and k-means region growing. Finger nails image could be used as early detection of diabetes mellitus. The steps in research are preprocessing step and segmentation step. Preprocessing step consist of image grayscale conversion, median filter, edge detection sobel operator and dilation. The aim of preprocessing step is to enhancement image before segmentation process is applied in image. Therefore, segmentation step using k-means region growing approach. The result show that accuracy rate of methods is 54.67%. In the next research, segmentation of finger nails image could use other methods that show better result.
Ima Kurniastuti and Ary Andini
IEEE
The aim of this research was to determine of component color RGB on fingernails as early detection of diabetes mellitus. Methods of the study consisted of material preparation and implementation procedures that carried out in three step i.e (1) data retrieval, (2) data processing and (3) data analysis. Firstly, random blood glucose levels were take with Autocheck GCU rapid test then fingernail images data were taken by digital camera and classified into into three categories namely diabetes, prediabetes and normal. Images data were segmented and transformed manually into R (red), G (green), and B (blue) histogram. RGB histogram was analyzed and grouped by frequency distribution to obtain RGB range number of each category. The results showed that range number of Red in diabetes, prediabetes and normal were 160–181, 170–185, and 165–183. Range number of Green were 100–119, 103–123, 107–129 for diabetes, prediabetes and normal. Also range number of Blue were 93–113, 90–110 and 97–117 for diabetes, prediabetes and normal. As conclusion, there was overlapping range number of RGB in all categories. Therefore, fingernail image as early detection of Diabetes Mellitus need to improve by added some feature such as texture image.
Ima Kurniastuti and Tri Deviasari Wulan
IEEE
This paper presented a method to make an application for determination of blood chemistry. Blood chemistry consists of blood glucose, uric acid and cholesterol. The method consists of four steps. The steps were a literature study step, design application step, implement application step and testing application step. Literature study step aimed to get information about the theory of the determination of blood glucose, uric acid, and cholesterol. Design application step consists of design flowchart and interface. Implement application step was converting design flowchart and interface into application in Macromedia Flash. Method in testing application was white-box testing. White-box testing method is used for logical and analytic test in unit test level and can helps spot hidden errors in the code. It is shown that cyclomatic complexity of glucose determination is six, cyclomatic complexity of uric acid determination is four and cyclomatic complexity of cholesterol determination is three. In future work, the application could be implemented into the web-based application and mobile application.
Ima Kurniastuti
IEEE
In this paper we proposed a method to create application of baby's nutrition status using Macromedia Flash. The anthropometry is used as input of application. The anthropometry like age, gender, weight, height and head circumference. The proposed method consists of stage of literature study as a preparation stage, stage of making application as a crucial stage in this research, data retrieval stage to get data as input in application, and stage of application testing as a stage in which application was tested using data from data retrieval stage. Output of the application was normal, below normal or above normal. It can be said normal if input is in around standard of nutrition status, it can be said below normal if input is below standard of nutrition status and it can be said above normal if input is above standard of nutrition status. The accuracy of program was 100% based on similarity between output of application and standard of nutrition status from ministry of health.
I Ketut Eddy Purnama, Ima Kurniastuti, Margareta Rinastiti, and Mauridhi Hery Purnomo
IEEE
In this paper we propose a new approach to determine the length of root canal in dental X-ray image semi-automatically. The approach consists of a sequence of the following procedures: preprocessing procedure using contrast stretching method, segmentation procedure using active shape model to find the area of root canal and thinning procedure to find centerline of the root canal area. The length of the extracted centerline to be the length of root canal. Active shape model able to find root canal area in the image, and the length of root canal can be determined. Hence, semi-automatic determination of root canal length in dental X-ray image is feasible.