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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Reconfigurable and Embedded Systems (IJRES) TELKOMNIKA (Telecommunication Computing Electronics and Control) Telematika Jurnal Ilmiah Dinamika Rekayasa (DINAREK) Jurnal Teknik Elektro dan Komputer TRIAC Indonesian Journal of Electrical Engineering and Computer Science Jurnal Teknik Informatika (JUTIF) JURNAL ABDIKARYASAKTI RENATA Jurnal Pengabdian Masyarakat Kita Semua Molekul: Jurnal Ilmiah Kimia

Retno Supriyanti

Jenderal Soedirman University

Author-ID : 394043

Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Other

Published : 22 Documents Claim Missing Document

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Articles

Title

Computer Aided Diagnosis for Screening the Shape and Size of Leukocyte Cell Nucleus based on Morphological Image Retno Supriyanti; Alfin Chrisanty; Yogi Ramadhani; Wahyu Siswandari
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 1: February 2018
Publisher : Institute of Advanced Engineering and Science

Hematology tests are examinations that aim to know the state of blood and its components, one of which is leukocytes. Hematologic examinations such as the number and morphology of blood generally still done manually, especially by a specialist pathologist. Despite the fact that today there is equipment that can identify morphological automatically, but for developing countries like Indonesia, it can only be done in the capital city. Low accuracy due to the differences identified either by doctors or laboratory staff, makes a great reason to use computer assistance, especially with the rapid technological developments at this time. In this paper, we will emphasize our experiment to screen leucocyte cell nucleus by identifying the contours of the cell nucleus, diameter, circumference and area of these cells based on digital image processing techniques, especially using the morphological image. The results obtained are promising for further development in the development of computer-aided diagnosis for identification of leukocytes based on a simple and inexpensive equipment.

Preliminary process in blast cell morphology identification based on image segmentation methods Retno Supriyanti; Pangestu F. Wibowo; Fibra R. Firmanda; Yogi Ramadhani; Wahyu Siswandari
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 6: December 2020
Publisher : Institute of Advanced Engineering and Science

The diagnosis of blood disorders in developing countries usually uses the diagnostic procedure Complete Blood Count (CBC). This is due to the limitations of existing health facilities so that examinations use standard microscopes as required in CBC examinations. However, the CBC process still poses a problem, namely that the procedure for manually counting blood cells with a microscope requires a lot of energy and time, and is expensive. This paper will discuss alternative uses of image processing technology in blast cell identification by using microscope images. In this paper, we will discuss in detail the morphological measurements which include the diameter, circumference and area of blast cell cells based on watershed segmentation methods and active contour. As a basis for further development, we compare the performance between the uses of both methods. The results show that the active contour method has an error percentage of 5.15% while the watershed method has an error percentage of 8.25%.

Point Processing Method for Improving Dental Radiology Image Quality Retno Supriyanti; Ariep Soelaiman Setiadi; Yogi Ramadhani; Haris Budi Widodo
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 4: August 2016
Publisher : Institute of Advanced Engineering and Science

Radiology field is very important in today's world, especially in the field of medicine including dentistry. Radiology equipment that is popular in dentistry is the panoramic machine. A panoramic image facilitate the dentist in making a diagnosis of the abnormality in the mouth and teeth. But unfortunately, for developing countries like Indonesia, panoramic machine available are low resolution which have an effect on the resulting image also has low quality. This research aims to improve the quality of the panoramic image to have a better quality. We use point processing method with emphasis on contrast stretching method. We chose this method because it is quite simple but has a high performance. Based on the second opinion from the hospital, the performance is 83.9%, therefore this method is promising to be implemented on the improvement of dental radiology images.

Calculating the area of white spots on the lungs of patients with COVID-19 using the Sauvola thresholding method Retno Supriyanti; Muhammad Rifqi Kurniawan; Yogi Ramadhani; Haris Budi Widodo
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp315-324

COVID-19 is a pandemic that has occurred in the world since 2019. Researchers have carried out various ways in dealing with this disease, starting from the screening stage to the stage of treatment and therapy for COVID-19 patients. As the gateway to the COVID-19 problem, screening has an essential role in a diagnosis that leads to appropriate treatment. In this paper, we will focus on the screening stage using digital image processing techniques, namely in calculating the area of white spots in the lungs of COVID-19 patients. The white patches are an early indication of how badly COVID-19 is attacking the patient. We use X-Ray Thorax image objects as research data in this paper. Although the current experimental results show that this method has a successful performance of 71.11%, it is pretty promising for further development due to its simplicity.

Support vector machine method for classifying severity of Alzheimer's based on hippocampus object using magnetic resonance imaging modalities Supriyanti, Retno; Riyanto, Arif Pujo; Ramadhani, Yogi; Aliim, Muhammad Syaiful; Akbar, Muhammad Irham; Widodo, Haris Budi; Alqaaf, Muhammad
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6322-6331

Alzheimer's disease is a degenerative brain condition that causes progressive decline in several aspects. Starting from memory, cognitive or thinking abilities, speaking abilities, and behavior. Currently, Alzheimer's diagnosis uses some methods, such as blood tests, scanning with computerized tomography scan (CT scan), or magnetic resonance imaging (MRI). As a reference for determining the level of severity, doctors usually use clinical dementia rating (CDR). CDR is a numerical scale used to measure the severity of dementia symptoms. The doctor will manually compare the patient's condition with those stated on the CDR. This condition will take quite a long time, and sometimes human error will occur. As technology and science develop, doctors can assist in manually detecting Alzheimer's using classification algorithms. Many methods can be used to classify, including the CDR support vector machine (SVM) method. Unfortunately, this method is usually only used to classify two classes. This technology allows the classification process to be carried out automatically and quickly. On the other hand, when using CDR to classify Alzheimer's severity, there are several scales, not just two classes. So, in this research, we modified the use of SVM to classify three levels of severity, namely scale 0 for normal, scale 1 for mild conditions, and scale 2 for moderate conditions. The experiments we carried out provided an accuracy of 90.9%.

Co-Authors Ahmad Fariz Akbar, Mohammad Irham Akbar, Muhammad Irham Alfin Chrisanty Aliim, M. Syaiful Alqaaf, Muhammad Anugerah Kevin Marchel Ardi Wicaksono, Madya Ari Fadli Ariep Soelaiman Setiadi Aryanto, Andreas S. Candra Kurniawan Dina Rahmawati Dita Dayu AW Dwi Susanto, Putra Eko Murdyantoro Elvin Pranata Eman Sutrisna Erfan Handoko Fadlola, M. Gus Solhan Fibra R. Firmanda Ghoshal, Sib Krishna Hari Siswantoro, Hari Haris B. Widodo Haris Budi Widodo Haris Budi Widodo Haris Budi Widodo Icuk Rangga Bawono, Icuk Rangga Jatmika, Jumaeda Lazuardi Umar Mudrik Alaydrus Muhammad Alqaaf Muhammad Alqaaf Muhammad Rifqi Kurniawan Muhammad Syaiful Aliim Mukhtar Effendi Pangestu F. Wibowo Rais Akhdan, Syafrudin Rifda Naufalin Riyanto, Arif Pujo Rumpoko Wicaksono Subkhi Adhi Priyono Suroso Suroso Suwitno Suwitno Syadzwina Luke Dzihniza Tamtowi, Tomy Teddy Septiana Trishardian, Rachmat Tutik Ida Rosanti Wahyu Siswandari Wahyu Widanarto, Wahyu Winasis Winasis Yogi Ramadhani Yogi Ramadhani Yogi Ramadhani

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