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All Journal Jurnal Pekommas Jurnal Teknologi Informasi dan Komunikasi Communications in Science and Technology Conference SENATIK STT Adisutjipto Yogyakarta Water Circulation Monitoring System in The Vanname Shrimp Cultivation based on Internet of Thing

Hanung Adi Nugroho

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Author-ID : 3086441

Aerospace Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Social Sciences

Published : 11 Documents Claim Missing Document

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Segmentation of retinal blood vessels for detection of diabetic retinopathy: A review Rezty Amalia Aras; Tri Lestari; Hanung Adi Nugroho; Igi Ardiyanto
Communications in Science and Technology Vol 1 No 1 (2016)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.1.1.2016.13

Diabetic detinopathy (DR) is effect of diabetes mellitus to the human vision that is the major cause of blindness. Early diagnosis of DR is an important requirement in diabetes treatment. Retinal fundus image is commonly used to observe the diabetic retinopathy symptoms. It can present retinal features such as blood vessel and also capture the pathologies which may lead to DR. Blood vessel is one of retinal features which can show the retina pathologies. It can be extracted from retinal image by image processing with following stages: pre-processing, segmentation, and post-processing. This paper contains a review of public retinal image dataset and several methods from various conducted researches. All discussed methods are applicable to each researcher cases. There is no further analysis to conclude the best method which can be used for general cases. However, we suggest morphological and multiscale method that gives the best accuracy in segmentation.

Texture feature extraction for the lung lesion density classification on computed tomography scan image Hasnely Hasnely; Hanung Adi Nugroho; Sunu Wibirama; Budi Windarta; Lina Choridah
Communications in Science and Technology Vol 1 No 1 (2016)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.1.1.2016.14

The radiology examination by computed tomography (CT) scan is an early detection of lung cancer to minimize the mortality rate. However, the assessment and diagnosis by an expert are subjective depending on the competence and experience of a radiologist. Hence, a digital image processing of CT scan is necessary as a tool to diagnose the lung cancer. This research proposes a morphological characteristics method for detecting lung cancer lesion density by using the histogram and GLCM (Gray Level Co-occurrence Matrices). The most well-known artificial neural network (ANN) architecture that is the multilayers perceptron (MLP), is used in classifying lung cancer lesion density of heterogeneous and homogeneous. Fifty CT scan images of lungs obtained from the Department of Radiology of RSUP Dr. Sardjito Hospital, Yogyakarta are used as the database. The results show that the proposed method achieved the accuracy of 98%, sensitivity of 96%, and specificity of 96%.

Internal content classification of ultrasound thyroid nodules based on textural features Anan Nugroho; Hanung Adi Nugroho; Noor Akhmad Setiawan; Lina Choridah
Communications in Science and Technology Vol 1 No 2 (2016)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.1.2.2016.25

Ultrasound (US) is one of the best imaging modalities on thyroid identification. The suspicious thyroid is indicated in the existence of palpable nodules whose solid or cystic composition. Solid nodules have high possibility to be malignant than cystic. An effort to detect and classify the internal content of thyroid nodule has become challenge problem in radiology area. Operator dependence of ultrasound imaging makes it complicated due to missing interpretation among radiologists. Objective Computer Aided Diagnosis (CAD) was designed to solve it which works on texture analysis of histogram statistic, gray level co-occurrence matrice (GLCM) and gray level run length matrices (GLRLM). The fine-needle aspiration cytology (FNAC) is not needed because the textural pattern is significantly different between solid and cystic nodules.Â Multi-layer perceptron (MLP) was adopted to do classification process for 72 US thyroid images yield an accuracy of 90.28%, the sensitivity of 87.80%, specificity of 93.55% and precision of 94.74%.

Detection of malaria parasites in thick blood smear: A review Faza Maula Azif; Hanung Adi Nugroho; Sunu Wibirama
Communications in Science and Technology Vol 3 No 1 (2018)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Based on data from World Health Organization, in 2015, there are 90% of deaths caused by malaria disease in Africa, Southeast Asia and countries of eastern Mediterranean. It makes the malaria become one of the most dangerous diseases that often leads to death. To support the diagnosis of malaria, early detection of plasmodium parasite is needed. Recently, malaria diagnosis process can be done with the help of computer, or often referred to as Computer Aided Diagnosis (CAD). By utilizing the digital image from the blood staining process, digital image processing can be performed to detect the presence of malaria parasite. There are 2 types of blood smear images that can be used in the malaria diagnosis process, namely, thin blood smear images and thick blood smear images. This paper provides a review of the techniques and methods used in the diagnosis of computer-assisted malaria using thick blood smear images as a diagnostic material.

Optimasi Deteksi Kebocoran dengan Menggunakan Phase Stretch Transform pada Retina Fluorescein Angiography Images untuk Penyakit Malaria Febry Putra Rochim; Hanung Adi Nugroho; Noor Akhmad Setiawan
Communications in Science and Technology Vol 3 No 2 (2018)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Malarial Retinopathy (MR) is indicated by retina alteration such as white dots occurrence which is caused by malaria. Leak detection is a key factor of MR’s early diagnosis. Inconsistent size and shape of the leakages with the colour contrast that relatively similar with the background. Leak detection’s algorithm is one of the most complex algorithms on the fundus image analysis field. Therefore, improving performance in the leakage detection is essential. This study focuses on automated leakage detection on fluorescein angiography (FA) images. The methods used in this study are vessel segmentation, saliency detection, phase stretch transform (PST), optic disk removal and leak detection to extract some features which then classified to correctly validate the leak. From 20 patient data large focal leak images with 31 leak points, 28 of them have been correctly detected. So, the experiment produced the accuracy and specificity of 0.98 and 0.9, respectively. With the proposed method of this study, there is a potential to enhance the knowledge on MR field in the future.

Co-Authors Anan Nugroho Arif Masthori Budi Windarta Faza Maula Azif Febry Putra Rochim Hasnely Hasnely Igi Ardiyanto Lina Choridah Margaretha Kusuma Prihantiwi Noor Akhmad Setiawan Rezty Amalia Aras Riri Ferdiana Robert Silas Kabanga Sudaryanto . Sunu Wibirama Teguh Bharata Adji Tri Lestari

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