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All Journal Telematika : Jurnal Informatika dan Teknologi Informasi International Journal of Advances in Intelligent Informatics Journal of Electrical Technology UMY Jurnal Sistem dan Manajemen Industri Journal of Robotics and Control (JRC) Prosiding Seminar Nasional Multidisiplin Ilmu Jurnal Nasional Teknik Elektro dan Teknologi Informasi The Indonesian Journal of Computer Science
Dharmawan, Dhimas Arief
Program Studi Informatika, Universitas Pembangunan Nasional Veteran Yogyakarta, Indonesia
Aerospace Engineering Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering Transportation Other

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DETEKSI BIDANG ORIENTASI PADA CITRA SIDIK JARI Dhimas Arief Dharmawan, Latifah Listyalina, Ikhwan Mustiadi,
Prosiding Seminar Nasional Multidisiplin Ilmu Vol 1, No 2 (2019): Prosiding Seminar Nasional : Pemanfaatan Literasi Digital Dalam Publikasi Ilmiah
Publisher : Universitas Respati Yogyakarta

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Abstract

Sistem biometrik ialah sistem yang mempelajari metode dasar autentifikasi dengan menggunakan anggota tubuh atau perilaku dari manusia sebagai basisnya, misalnya sidik jari, tanda tangan, iris, dan DNA. Salah satu sistem biometrik yang digunakan di dalam penelitian ini ialah sidik jari. Sidik jari digunakan sebagai pembeda antara individu satu dengan lainnya karena kehandalannya sangat tinggi, yaitu tidak ada individu yang mempunyai bentuk fisik dan pola yang sama. Untuk dapat mengekstrak area dari sidik jari, orientasi area tersebut telah dilakukan. Operator sobel dan Gaussian diaplikasikan pada teknik orientasi yang bertujuan mencari gradien dari pola sidik jari tersebut. Hasil orientasi menunjukkan pola sidik jari dari sampel citra yang adaKeywords: Gaussian; orientation; fingerprint; Sobel
PENINGKATAN KUALITAS PEMBELAJARAN IPA DI SDIT INSAN UTAMA MELALUI PENGADAAN DAN PELATIHAN PENGGUNAAN ALAT PERAGA PEMBELAJARAN Ahmad Zaki, Mursid Sabdullah, Latifah Listyalina, Dhimas Arief Dharmawan,
Prosiding Seminar Nasional Multidisiplin Ilmu Vol 2, No 1 (2020): Tetap Produktif dan Eksis Selama dan Pasca Pandemi COVID-19
Publisher : Universitas Respati Yogyakarta

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Abstract

Melaksanakan kegiatan pengabdian masyarakat bagi tenaga pendidik di dalam merupakan salah satu upaya untuk melaksanakan tugas sebagai pelaksanaan tridarma perguruan tinggi. Salah satu bentuk pengabdian tersebut ialah memberikan sumbangsih ilmu pengetahuan dan teknologi kepada masyarakat, khususnya pada dunia Pendidikan. Berdasarkan hal ini, kami mengajukan usulan kegiatan pengabdian di salah satu sekolah dasar di Kabupaten Bantul, yaitu SDIT Insan Utama. Tujuan pengabdian ini adalah memberikan bekal pengetahuan kepada anak usia sekolah sejak dini dengan menggunakan alat peraga di mana alat ini merupakan salah satu komponen yang menentukan efektivitas pembelajaran. Dengan alat peraga, hal-hal yang abstrak dapat disajikan dalam bentuk model-model berupa benda konkret yang dapat dilihat, dipegang, diputarbalikkan sehingga dapat lebih mudah dipahami. Fungsi utama dari alat peraga adalah untuk menurunkan keabstrakan konsep agar siswa mampu menangkap arti konsep tersebut. Materi yang akan kami berikan berupa materi Ilmu Pengetahuan Alam (IPA) tingkat Sekolah Dasar (SD). Target luaran yang diharapkan dari kegiatan ini adalah siswa mampu mampu memahami konsep dasar mengenai materi Ilmu Pengetahuan Alam dan tenaga pendidik memiliki penguatan pembelajaran dengan menggunakan alat peraga demi peningkatan kualitas proses pembelajaran SD yang bervariatif, menarik, dan efektif.
Detection of Cervical Cancer Based on Learning Vector Quantization and Wavelet Transform Dharmawan, Dhimas Arief; Listyalina, Latifah
Journal of Electrical Technology UMY Vol 3, No 3 (2019): September
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.3357

Abstract

Cervical cancer has became the common women dsease in the world. Mostly, cervical cancer has been already known lately, because it is very dificult to detect this in early stage. In this work, a computer based software using Learning Vector Quantization (LVQ) has been designed as the early cervical cancer detection aid tool. There are six methods before the detection is performed, namely preprocessing, contrast stretching, median filtering, morphology operation, image segmentation, and Wavelet Transform based feature extraction. In tihis work, 73 cervical cell images that consist of 50 normal images and 23 cancer images are used. 35 normal images and 14 cancer images are used to train the LVQ. Then, 23 normal images and 9 cancer images are used in the testing process. Our results show 88,89 % cancer image can be detected correctly (sensitivity), 100 % normal image can be detected corerctly (specificity), and 95,83 % for overall detection (accuracy).
Retinal Digital Image Quality Improvement as A Diabetes Retinopatic Disease Detection Effort Listyalina, Latifah; Yudianingsih, Yudianingsih; Dharmawan, Dhimas Arief
Journal of Electrical Technology UMY Vol 4, No 2 (2020): December
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.v4i2.8590

Abstract

Image processing is a technical term useful for modifying images in various ways. In medicine, image processing has a vital role. One example of images in the medical world, namely retinal images, can be obtained from a fundus camera. The retina image is useful in the detection of diabetic retinopathy. In general, direct observation of diabetic retinopathy is conducted by a doctor on the retinal image. The weakness of this method is the slow handling of the disease. For this reason, a computer system is required to help doctors detect diabetes retinopathy quickly and accurately. This system involves a series of digital image processing techniques that can process retinal images into good quality images. In this research, a method to improve the quality of retinal images was designed by comparing the methods for adjusting histogram equalization, contrast stretching, and increasing brightness. The performance of the three methods was evaluated using Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Signal to Noise Ratio (SNR). Low MSE values and high PSNR and SNR values indicated that the image had good quality. The results of the study revealed that the image was the best to use, as evidenced by the lowest MSE values and the highest SNR and PSNR values compared to other techniques. It indicated that adaptive histogram equalization techniques could improve image quality while maintaining its information.
Identifying Glucose Levels in Human Urine via Red Green Blue Color Compositions Analysis Listyalina, Latifah; Dharmawan, Dhimas Arief; Utari, Evrita Lusiana
Journal of Electrical Technology UMY Vol 4, No 1 (2020): June
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet umy.v4i1.8538

Abstract

Diabetes mellitus (DM), a metabolic disorder caused by the lack of the insulin hormone, has become a health problem quite severe and is the most common endocrine disease. Recently, diagnosing diabetes could be carried out through monitoring the glucose level in human blood taken from the patient's finger or arm. On the other hand, a non-invasive blood sugar detector with a benedict test on human urine is an alternative to monitor blood sugar without injuring the body. The test output can be determined from the colour of the colour change of urine. However, manual evaluations on the urine colour are prone to human subjectivity. In this paper, we present a computational method to determine the blood sugar level based on the colour of the given urine automatically. The proposed method identifies the blood sugar level by taking into account the colour intensity on the red, green, and blue (RGB) channels of the urine colour. In the experimental parts, the proposed method is capable of classifying the urine sample correctly. Hence, our approach may be beneficial for practical applications.
Retinal Blood Vessel Segmentation as a Tool to Detect Diabetic Retinopathy Dharmawan, Dhimas Arief; Listyalina, Latifah
Journal of Electrical Technology UMY Vol 3, No 2 (2019): June
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.3253

Abstract

The retina is an important part of the eye for humans. Inbesides its main function as part of the sense of sight, in the worldmedically, the retina after an image can be used to detect a numberdiseases, such as diabetic retinopathy. To detect a number of diseases,Retinal digital images taken using a digital fundus camera are used.In detecting diabetic retinopathy, digital images are neededsegmented retina. Nevertheless, automatic segmentation of digital imagesthe retina is a complex work, given the presence of artifactsas well as noise on the retinal digital image, evenly illuminated, intensitylow, low contrast, and varying lengths of retinal blood vessels.In this research, a blood vessel segmentation software system has been designed through three stagesimage processing, namely (i) preprocessing, (ii) improving image quality, (iii) andsegmentation of retinal blood vessels. With three image processing stages, the performance value is obtained, i.e. 84.62.
Performance Analysis of Lung Cancer Diagnosis Algorithms on X-Ray Images Dharmawan, Dhimas Arief; Listyalina, Latifah
Journal of Electrical Technology UMY Vol 2, No 2 (2018)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.2232

Abstract

Among several types of cancer, lung cancer is regarded as one of the most common and serious. In this respect, early diagnosis is required and beneficial to reduce mortalities caused by this type of cancer. Such diagnosis is typically performed by doctors through manual examinations on X-Ray images. However, manual examinations are labor extensive and time consuming. In this paper, we conduct a study to analyze the performance of some computer-based lung cancer diagnosis algorithms. The algorithms are built using different feature extraction (gray-level co-occurrence matrix, pixel intensity, histogram and combination of the three) and machine learning (Multi-layer Perceptron and K-Nearest Neighbor) techniques and the performance of each algorithm is compared and analyzed. The result of the study shows that the best performance of lung cancer classification is obtained by the computer algorithm that uses the combined features to characterize lung cancer and subsequently classifies the features using Multi-layer Perceptron.
Adaptive Modelling of Multipath Communication Channels Based on the Least Mean Square Algorithm Dhimas Arief Dharmawan
Journal of Electrical Technology UMY Vol 1, No 4 (2017)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.1423

Abstract

The objective of this research is to design an adaptive model for multipaths communication channels. To evaluate the performance of the model, the authors used two indicators, namely the attainment of a minimum value of error signals in the form of interface and echo on the channel, and Filter Finite Impulse Response (FIR) has the same form of equation as the channel equation used. This adaptation process uses the Least Mean Square (LMS) algorithm. The LMS algorithm is known as a simple algorithm, which is fast computation time and the computation results are quite satisfying. In this study, the authors used Simulink software on Matlab. In general, this research is divided into three stages, namely modeling multipaths communication channels as an adaptive system, designing an adaptive system model on Simulink, and designing a simulation of 250 iterations. After obtaining the simulation results in the form of errors and weight of the FIR filter, it is observed that both of the results have met the requirements of the indicators of the success of this study. With 250 iterations used, satisfactory results were obtained in the form of the fulfillment of all indicators of the success of this study.
Detection of Optic Disc Centre Point in Retinal Image Latifah Listyalina; Dhimas Arief Dharmawan
Journal of Electrical Technology UMY Vol 3, No 1 (2019): March
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.3150

Abstract

Glaucoma and diabetic retinopathy (DR) are the two most common retinal related diseases occurred in the world. Glaucoma can be diagnosed by measuring optic cup to disc ratio (CDR) defined as optic cup to optic disc vertical diameter ratio of retinal fundus image. A computer based optic disc is expected to assist the ophthalmologist to find their location which are necessary for glaucoma and DR diagnosis. However, many optic disc detection algorithms available now are commonly non-automatic and only work in healthy retinal image. Therefore, there is not information on how optic disc in retinal image of unhealthy patient can be extracted computationally. In this research work, the method for automated detection of optic disc on retinal colour fundus images has been developed to facilitate and assist ophthalmologists in the diagnosis of retinal related diseases. The results indicated that the proposed method can be implemented in computer aided diagnosis of glaucoma and diabetic retinopathy system development.
Segmentation of the Electrocardiography Images as a Tool to Identify Heart Diseases Latifah Listyalina; Dhimas Arief Dharmawan
Journal of Electrical Technology UMY Vol 3, No 4 (2019): December
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.3466

Abstract

The heart is a very vital organ. Cardiac examination can be done periodically by using an electrocardiograph. So that the heart's condition can be known. One of the optimization in helping the detection of heart disease automatically by using computer assistance. Automatic detection can be done by image processing methods as input, especially ECG images that have been segmented. In this study, ECG image segmentation is carried out through several stages, such as grayscalling, contrast enhancement, and segmentation. The hope, the results of this study can be used as input for automatic detection of heart disease.
Co-Authors Adjie Wibowo Soedjono Agus Qomaruddin Munir Andiko Putro Suryotomo ARDIANSYAH ARDIANSYAH Asih, Hayati Mukti Evrita Lusiana Utari Evrita Lusiana Utari, Evrita Lusiana Hayati Mukti Asih Ikhwan Mustiadi Irawadi Buyung, Irawadi Latifah Listyalina Latifah Listyalina Leuveano, Raden Achmad Chairdino Listyalina, Latifah Michel Pierce Tahya Raden Achmad Chairdino Leuveano Raden Achmad Chairdino Leuveano Ridho, Muhammad Ihsan Sani, Sayang Sayang Sani Tahya, Michel Pierce Yudianingsih Yudianingsih Yudianingsih, Yudianingsih