Bagus Adhi Kusuma

Bio: Bagus Adhi Kusuma is an academic researcher from Gadjah Mada University. The author has contributed to research in topics: Cobb angle & Curve fitting. The author has an hindex of 3, co-authored 11 publications receiving 30 citations.

Determination of spinal curvature from scoliosis X-ray images using K-means and curve fitting for early detection of scoliosis disease

Abstract: One of the disease that require X-ray diagnosis is scoliosis Early detection of scoliosis is important to do for anyone From the early detection information, the doctor may take the firts step to further treatment quickly Determination of spinal curvature is a first step method that used to measure how severe the degree of scoliosis The severity degree of scoliosis can be assess by using Cobb angle Therefore, by approximate the spinal curvature, we can approximate the cobb angle too From previous work that interobserver measurement value may reach 118° and intraobserver measurement error is 6° So, as far as the cobb angle measuring, the subjectivity aspect is the natural thing and can be tolerated until now This research propose an algorithm how to define spinal curvature with the aid of a computer in digital X-ray image quickly but has a standard error that can be tolerated The preprocessing has been done by canny edge detection The k-means clustering algorithm can detect the centroid point after segmentation preprocessing of the spinal segment and polynomial curve fitting will be used in the process for determining the spinal curve From the spinal curvature information, the scoliosis curve can be classified into 4 condition, normal, mild, moderate, and severe scoliosis

Keylogger Is A Hacking Technique That Allows Threatening Information On Mobile Banking User

Abstract: Modern society is use of mobile phones for business interests, especially financial activities related to banking. The growth of mobile financial services is not only dependent on technological progress, but also on consumer confidence in the services provided. An example of banking services discussed in this study is the mobile banking application. Communities increasingly comfortable to use the application because it is easy to use and very helpful financial process. But still few people are aware of the threat of crimes that threaten financial accounts using mobile banking applications. In this study discusses the possibility of attacks that can threaten users of mobile banking services using keylogger. The forensic data is analyzed with the static method expected to obtain important information or data that can be used as digital evidence. Suppose the access log, transaction records, customer profiles, and so on. Because the important information that can be misused as a security loophole to carry out illegal access. The results showed that there is no important information that can be used for unauthorized access and the security level had been applied is good enough to secure from unauthorized access action.

Spinal curvature determination from scoliosis X-Ray image using sum of squared difference template matching

Abstract: Scoliosis is a disorder in which there is a sideways curve of the spine. Curve are often S-shaped or C-shaped. One of the methods to ascertain a patient with scoliosis is through using Cobb angle measurement. The importance of the automatic spinal curve detection system is to detect any spinal disorder quicker and faster. This study is intended as a first step based on computer-aided diagnosis. The spinal detection method that we propose is using template matching based on Sum of Squared Difference (SSD). This method is used to estimate the location of the vertebra. By using polynomial curve fitting, a spinal curvature estimation can be done. This paper discusses the performance of SSD method used to detect a variety of data sources of X-Ray from numerous patients. The results from the implementation indicate that the proposed algorithm can be used to detect all the X-ray images. The best result in this experiment has 96.30% accuracy using 9-subdivisions poly 5 algorithm, and the average accuracy is 86.01%.

Pengembangan Sistem Informasi Berbasis Website Sebagai Media Pengelolaan Peminjaman dan Pengembalian Alat Laboratorium Fikes UMP

Abstract: Sebagai salah satu jurusan yang berada di Fakultas Ilmu Kesehatan, Universitas Muhammadiyah Purwokerto, di dalam Program Studi Ilmu Keperawatan terdapat laboratorium kesehatan yang memiliki peralatan terbanyak dan terlengkap di Fakultas Ilmu Kesehatan. Seluruh peralatan tersebutdi kelola oleh Unit Pelaksana Teknis (UPT) yang menyediakan fasilitas sarana dan prasarana peralatan kesehatan. Sarana dan prasarana perkuliahan yang memadai merupakan faktor penting dalam menunjang proses belajar mengajar. Sarana perkuliahan seperti alat praktik dan alat ukur memiliki resiko besar terhadap kerusakan dan kehilangan, sehingga dibutuhkan sebuah sistem peminjaman alat yang baik agar data peminjam dan keberadaan alat dapat diketahui. Dengan kondisi mahasiswa yang setiap tahunnya mengalami peningkatan, penerapan sistem manual sudah tidak efisien dan tidak efektif lagi untuk diterapkan. Karena dengan meningkatnya jumlah mahasiswa maka semakin meningkat pula intensitas kebutuhan peminjaman alat laboratorium.Penggunaan sistem manual dengan pencatatan pada buku memang kurang efektif serta tidak efisien dalam proses peminjaman dan pengembalian alat yang rutin dilakukan. Maka pada penelitian ini dibutuhkan suatu sistem informasi berbasis komputer yang dapat membantu pengelolaan peralatan laboratorium sehingga pelayanan peminjaman dan pengembalian bisa lebih efektif. Penerapan sistem informasi ini bertujuan agar dapat membantu pelayanan di laboratorium dalam proses peminjaman dan pengembalian peralatan, serta membuat pelaporan rutin harian, bulanan, dantahunan.

SISTEM INFORMASI SARANA DAN PRASARANA SEKOLAH BERBASIS WEBSITE (Studi Kasus : SMK Bakti Purwokerto)

Abstract: Bakti Purwokerto Vocational School is one of the Vocational High Schools (VHS) in Banyumas which was established on January 1, 1968 with its address at Jl. Dr. Soeparno No. 13 Purwokerto, Banyumas Regency, Central Java, 53111. At the school the management of goods and infrastructure is currently still using manual methods, namely by recording in books. Management of goods in this way causes less than maximum management of existing facilities and infrastructure. Some other problems are the difficulty of the Deputy Chief of Facilities and Infrastructure staff in the process of finding information on goods, due to incomplete and detailed data in the bookkeeping process. Therefore, the goods in the Facilities and Infrastructure that have been moved or borrowed are very difficult to find out. Website-based information systems use qualitative methods. This method is a system with a prototype method as the development of the system. The results of this study are creating a website-based school infrastructure and information system at the Bakti Purwokerto Vocational School with the aim of being able to assist the Deputy Head of Facilities and Infrastructure starting from the process of searching for goods using a QR Code scan, recording reports to grouping infrastructure data. The conclusion of the Acceptance Testing or the term from Beta Testing produced 88.65% which is included in the excellent category of the proposed system.

Computer-Aided Cobb Measurement Based on Automatic Detection of Vertebral Slopes Using Deep Neural Network.

Abstract: Objective. To develop a computer-aided method that reduces the variability of Cobb angle measurement for scoliosis assessment. Methods. A deep neural network (DNN) was trained with vertebral patches extracted from spinal model radiographs. The Cobb angle of the spinal curve was calculated automatically from the vertebral slopes predicted by the DNN. Sixty-five in vivo radiographs and 40 model radiographs were analyzed. An experienced surgeon performed manual measurements on the aforementioned radiographs. Two examiners used both the proposed and the manual measurement methods to analyze the aforementioned radiographs. Results. For model radiographs, the intraclass correlation coefficients were greater than 0.98, and the mean absolute differences were less than 3°. This indicates that the proposed system showed high repeatability for measurements of model radiographs. For the in vivo radiographs, the reliabilities were lower than those from the model radiographs, and the differences between the computer-aided measurement and the manual measurement by the surgeon were higher than 5°. Conclusion. The variability of Cobb angle measurements can be reduced if the DNN system is trained with enough vertebral patches. Training data of in vivo radiographs must be included to improve the performance of DNN. Significance. Vertebral slopes can be predicted by DNN. The computer-aided system can be used to perform automatic measurements of Cobb angle, which is used to make reliable and objective assessments of scoliosis.

Analisis metode pengembangan sistem informasi berbasis website: a literatur review

Abstract: AbstrakSaat ini perkembangan teknologi informasi sangat pesat. Teknologi informasi sangat dibutuhkan dalam kehidupan manusia. Salah satu fungsi teknologi sistem informasi adalah membantu atau mendorong pekerjaan manusia agar berjalan lebih efektif dan efisien. Pengembangan sistem informasi memiliki banyak metode dan platform yang beragam. Platform yang dapat digunakan dalam pengembangan sistem informasi adalah platform berbasis mobile, web atau desktop. Penelitian ini bertujuan untuk menentukan model pengembangan sistem informasi berbasis website, dan datanya diperoleh melalui literatur yang relevan dari tahun 2016 hingga 2020. Metode yang digunakan dalam penelitian ini adalah System Literature Review (SLR). Metode SLR digunakan untuk mengidentifikasi, meninjau, mengevaluasi, dan menafsirkan semua penelitian yang tersedia di bidang subjek dari fenomena yang menarik, serta pertanyaan penelitian terkait tertentu. Dengan menggunakan metode SLR, artikel jurnal dapat direview dan diidentifikasi secara sistematis, dan langkah atau prosedur yang telah ditentukan dapat diikuti dalam setiap proses. Hasil penelitian ini menunjukkan bahwa metode utama yang digunakan dalam pengembangan sistem informasi berbasis website, dan kelebihan dan kekurangan pengembangan sistem informasi berbasis website yang digunakan dalam penelitian ini.Kata Kunci: Pengembangan Sistem Informasi, Systematic Literatur Review (SLR), Website.

Detection of Micro-Defects on Metal Screw Surfaces Based on Deep Convolutional Neural Networks

Abstract: This paper proposes a deep convolutional neural network (CNN) -based technique for the detection of micro defects on metal screw surfaces. The defects we consider include surface damage, surface dirt, and stripped screws. Images of metal screws with different types of defects are collected using industrial cameras, which are then employed to train the designed deep CNN. To enable efficient detection, we first locate screw surfaces in the pictures captured by the cameras, so that the images of screw surfaces can be extracted, which are then input to the CNN-based defect detector. Experiment results show that the proposed technique can achieve a detection accuracy of 98%; the average detection time per picture is 1.2 s. Comparisons with traditional machine vision techniques, e.g., template matching-based techniques, demonstrate the superiority of the proposed deep CNN-based one.

Localization and Edge-Based Segmentation of Lumbar Spine Vertebrae to Identify the Deformities Using Deep Learning Models

Abstract: The lumbar spine plays a very important role in our load transfer and mobility. Vertebrae localization and segmentation are useful in detecting spinal deformities and fractures. Understanding of automated medical imagery is of main importance to help doctors in handling the time-consuming manual or semi-manual diagnosis. Our paper presents the methods that will help clinicians to grade the severity of the disease with confidence, as the current manual diagnosis by different doctors has dissimilarity and variations in the analysis of diseases. In this paper we discuss the lumbar spine localization and segmentation which help for the analysis of lumbar spine deformities. The lumber spine is localized using YOLOv5 which is the fifth variant of the YOLO family. It is the fastest and the lightest object detector. Mean average precision (mAP) of 0.975 is achieved by YOLOv5. To diagnose the lumbar lordosis, we correlated the angles with region area that is computed from the YOLOv5 centroids and obtained 74.5% accuracy. Cropped images from YOLOv5 bounding boxes are passed through HED U-Net, which is a combination of segmentation and edge detection frameworks, to obtain the segmented vertebrae and its edges. Lumbar lordortic angles (LLAs) and lumbosacral angles (LSAs) are found after detecting the corners of vertebrae using a Harris corner detector with very small mean errors of 0.29° and 0.38°, respectively. This paper compares the different object detectors used to localize the vertebrae, the results of two methods used to diagnose the lumbar deformity, and the results with other researchers.