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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Teknologi Jurnal IPTEK-KOM (Jurnal Ilmu Pengetahuan dan Teknologi Komunikasi) Communications in Science and Technology IJID (International Journal on Informatics for Development) IJITEE (International Journal of Information Technology and Electrical Engineering) Psikobuletin: Jurnal Ilmiah Psikologi Jurnal Nasional Teknik Elektro dan Teknologi Informasi Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya
Sunu Wibirama
Universitas Gadjah Mada
Religion Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Physics Social Sciences

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Journal : Communications in Science and Technology

 1 
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

Abstract

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%.
Automated localisation of optic disc in retinal colour fundus image for assisting in the diagnosis of glaucoma Latifah Listyalina; Hanung Adi Nugroho; Sunu Wibirama; Widhia KZ Oktoeberza
Communications in Science and Technology Vol 2 No 1 (2017)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.2.1.2017.43

Abstract

Optic disc (OD), especially its diameter together with optic cup diameter can be used as a feature to diagnose glaucoma. This study contains two main steps for optic disc localisation, i.e. OD centre point detection and OD diameter determination.  Centre point of OD is obtained by finding brightness pixel value based on average filtering.  After that, OD diameter is measured from the detected optic disc boundary.  The proposed scheme is validated on 30 healthy and glaucoma retinal fundus images from HRF database.  The results are compared to the ground truth images.  The proposed scheme obtains evaluation result (E) for healthy and glaucoma images is 0.23 and 0.21, respectively.  These results indicate successful implementation of automated OD localisation by detecting OD centre point and determining OD diameter.
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (211.443 KB) | DOI: 10.21924/cst.3.1.2018.75

Abstract

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.
Wart treatment method selection using AdaBoost with random forests as a weak learner M. Azka Putra; Noor Akhmad Setiawan; Sunu Wibirama
Communications in Science and Technology Vol 3 No 2 (2018)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (272.523 KB) | DOI: 10.21924/cst.3.2.2018.96

Abstract

Selection of wart treatment method using machine learning is being a concern to researchers. Machine learning is expected to select the treatment of warts such as cryotherapy and immunotherapy to patients appropriately. In this study, the data used were cryotherapy and immunotherapy datasets. This study aims to improve the accuracy of wart treatment selection with machine learning. Previously, there are several algorithms have been proposed which were able to provide good accuracy in this case. However, the existing results still need improvement to achieve better level of accuracy so that treatment selection can satisfy the patients. The purpose of this study is to increase the accuracy by improving the performance of weak learner algorithm of ensemble machine learning. AdaBoost is used in this study as a strong learner and Random Forest (RF) is used as a weak learner. Furthermore, stratified 10-fold cross validation is used to evaluate the proposed algorithm. The experimental results show accuracy of 96.6% and 91.1% in cryotherapy and immunotherapy respectively.
Spontaneous gaze interaction based on smooth pursuit eye movement using difference gaze pattern method Suatmi Murnani; Noor Akhmad Setiawan; Sunu Wibirama
Communications in Science and Technology Vol 7 No 1 (2022)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.7.1.2022.739

Abstract

Human gaze is a promising input modality for being able to be used as natural user interface in touchless technology during Covid-19 pandemic. Spontaneous gaze interaction is required to allow participants to directly interact with an application without any prior eye tracking calibration. Smooth pursuit eye movement is commonly used in this kind of spontaneous gaze-based interaction. Many studies have been focused on various object selection techniques in smooth pursuit-based gaze interaction; however, challenges in spatial accuracy and implementation complexity have not been resolved yet. To address these problems, we then proposed an approach using difference patterns between gaze and dynamic objects' trajectories for object selection named Difference Gaze Pattern method (DGP). Based on the experimental results, our proposed method yielded the best object selection accuracy of and success time of ms. The experimental results also showed the robustness of object selection using difference patterns to spatial accuracy and it was relatively simpler to be implemented. The results also suggested that our proposed method can contribute to spontaneous gaze interaction.
Co-Authors AG Pradnya Sidhawara Ahmad Nasikun Aninditya Anggari Nuryono Bagas Y. Wijonarko Budi Windarta Cepi Ramdani Dwi Fithriyaningrum Dwi Fithriyaningrum Dwi Joko Suroso Faza Maula Azif Hanung Adi Nugroho Hasnely Hasnely Igi Ardiyanto Indah Soesanti Lina Choridah Listyalina, Latifah Lisya Chairani Luthfi Ardi M. Azka Putra Noor Akhmad Setiawan Persada, Anugerah Galang Rachmawati Rachmawati Rachmawati Raja Bagus Arief Rahman Risanuri Hidayat Rudy Hartanto Sri Suning Kusumawardani Suatmi Murnani Subandi Subandi Supra Wimbarti Tio Eko Prabowo Widhia KZ Oktoeberza