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Listyalina, Latifah
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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.
Pengaruh Tegangan dan Arus di Pengambilan Data Waktu Cahaya Matahari pada Perancangan Kontrol Intensitas Lampu Jalan Otomatis Tenaga Surya Listyalina, Latifah; Susilo, Eko; Yudianingsih, Yudianingsih; Utari, Evrita Lusiana; Buyung, Irawadi
Jurnal Teknologi Informasi RESPATI Vol 16, No 3 (2021)
Publisher : Universitas Respati Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/jtir.v16i3.421

Abstract

INTISARIPada naskah ini akan dilakukan analisis nilai tegangan dan arus pada Alat Kontrol Intensitas Lampu Jalan Otomatis Tenaga Surya. Data tersebut diperoleh dari hasil pengujian alat terssebut dengan waktu/jam yang berbeda-beda untuk mengetahui efektivitas cahaya matahari dalam mengisi daya solar panel. Alat tersebut dibuat agar hemat energi dan sebagai energi alternatif. Sumber utama dari penerangan ini adalah dari energi matahari yang dikonversi oleh panel surya menjadi listrik, dan baterai atau aki berfungsi sebagai penyimpan energi listrik yang akan menyalakan lampu pada malam hari. Oleh sebab itu, apabila listrik PLN mengalami gangguan atau mati listrik maka penerangan jalan ini tidak terpengaruh.Dari alat di atas, diperoleh hasil pengujian untuk variable tegangan arus. Selanjutnya akan dianalisis pengaruh waktu/jam terhadap pengambilan data nilai tegangan dan arus. Pada data waktu pengisian panel surya, rata-rata tegangan dari solar cell sama yaitu 19,54 volt dan median (nilai tengah) sebesar 20 volt serta nilai rerata arus sebesar 0,81 A dan median sebesar 0,8 A. Semakin siang maka arus yang masuk ke baterai semakin besar karena energi dari sinar matahari berada pada puncaknya yaitu pada jam 11:00 sampai 13:00, kemudian semakin sore maka arus yang masuk semakin kecil karena sinar matahari yang diterima solar cell sudah tidak optimal.Kata kunci— solar panel, tegangan, arus, energi matahari ABSTRACTIn this paper, an analysis of the value of voltage and current will be carried out on the Intensity Control Tool for Automatic Solar Street Lights. The data was obtained from the results of testing the tool with different times/hours to determine the effectiveness of sunlight in charging solar panels. The tool is made to save energy and as an alternative energy. The main source of this lighting is from solar energy which is converted by solar panels into electricity, and the battery or battery serves as a store of electrical energy that will turn on the lights at night. Therefore, if the PLN electricity is interrupted or there is a power failure, the street lighting will not be affected.From the above tool, the test results are obtained for the current voltage variable. Furthermore, it will be analyzed the effect of time/hour on data retrieval of voltage and current values. In the solar panel charging time data, the average voltage from the solar cell is the same, namely 19.54 volts and the median (middle value) is 20 volts and the average current value is 0.81 A and the median is 0.8 A. The amount that goes into the battery is getting bigger because the energy from sunlight is at its peak at 11:00 to 13:00, then later in the afternoon, the incoming current gets smaller because the sunlight received by the solar cell is not optimal.Kata kunci—  solar panels, voltage, current, solar energy
PENENTUAN KOMBINASI KERNEL TERBAIK MENGGUNAKAN MEDIAN FILTER Yudianingsih Yudianingsih; Latifah Listyalina
Teknoin Vol. 22 No. 3 (2016)
Publisher : Faculty of Industrial Technology Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/teknoin.vol22.iss3.art8

Abstract

Many factors such as the use of low-quality lens, inappropriate image acquisition technique, and the uncertainty of environment condition affect digital image acquisition process. As a result, noisy image may be obtainedwhich is difficult to be recognized, processed, and analysed. The most occurred noise is salt and pepper which appears as white and black spots in image. This noise is usually removed or suppressed using median filter. However, improper size of median filter kernel may yield in poor result. This work aims to find the most suitable median filter kernel size combination using Breadth search, Depth Searchand Generate and Testmethods in order to obtain the best median filtering result. In this work, four median filter kernel sizes are used, i.e. 3×3, 5×5, 7×7, and 9×9. Filtering performance using each obtained combination is defined by measuring the Mean Square Error (MSE) of the filtered and unnoisy image (ground truth). Result shows that the best median filter kernel size combination is {3×3}. This combination is obtained using Breadth Search Method with the MSE of 27.0308.
Verifikasi citra tanda tangan berbasis perceptron Latifah Listyalina; Irawadi Buyung
Teknoin Vol. 24 No. 2 (2018)
Publisher : Faculty of Industrial Technology Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/teknoin.vol24.iss2.art4

Abstract

A signature has become an important human attribute, which can represent personal information. Human signatures are widely used to authorize documents, both paper-based as well as electronic-based ones.  However, such authorization still poses various privacy issues, such as signature duplication and forgeries. These may not be easy to be addressed, particularly when involving many documents. Hence, advanced procedures are required to verify the signature authenticity. In this paper, we propose a new method for automatic signature verification based on the digitalized signature images. The method comprises successive image processing techniques, such as cropping, resizing, gray-scaling and thresholding. The binary images as the results of thresholding serve as the features of the signatures and are used to train a single layer Perceptron neural network. The experiment in this paper uses 42 digitalized signatures images, collected from two subjects. The obtained images are divided into the training and testing sets, in which the training and testing sets comprise 14 and 28 images, respectively. In the experiment, the proposed method produces the average training and testing accuracies of 100% and 98.85%, respectively. These indicate that the proposed method is reliable for practical applications.
APLIKASI TEKNOLOGI TEPAT GUNA MELALUI PEMANFAATAN ENERGI TERBARUKAN UNTUK PENERANGAN DAN PENGEMBANGAN WISATA WATU TEKEK KULONPROGO Evrita Lusiana Utari; Latifah Listyalina; Novi Irawati
Dharmakarya Vol 8, No 3 (2019): September 2019
Publisher : Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (9088.125 KB) | DOI: 10.24198/dharmakarya.v8i3.22763

Abstract

Pemerintah daerah Kulonprogo memberdayakan potensi alam sebagai modal pembangunan dan pengembangan daerah. potensi wisata merupakan salah satu  faktor pendukung dalam peningkatan lapangan pekerjaan, peningkatan pendapatan, dan perkembangan usaha kecil. Wilayah yang memiliki potensi wisata yang cukup besar salah satunya adalah Propinsi Daerah Istimewa Yogyakarta.Salah satu wilayah yang memiliki potensi wisata, yaitu wisata Watu Tekek di daerah Kabupaten Kulonprogo. Permasalahan yang timbul adanya keterbatasan energi listrik dalam memenuhi kebutuhan energi dikawasan wisata Watu Tekek dikarenakan lokasi wisata yang cukup curam dan medan yang terjal, belum adanya penataan dan pengembangan kawasan wisata Watu Tekek dan masih terbatasnya amenitas/fasilitas pendukung dan sarana prasarana dikawasan wisata Watu Tekek. Dengan program kemitraan masyarakat (PKM) dana hibah dari Kemenristekdikti  memberikan solusi dari permasalahan tersebut dengan memenuhi kebutuhan energi listrik dengan menggunakan tenaga matahari berupa lampu penerangan, lampu hias, dan air mancur. Sedangkan untuk penambahan fasilitas pariwisata berupa penambahan gazebo, kursi taman , penambahan ornament tanah liat dan penataan taman.Metode kegiatan yang dilakukan dengan melaksanakan diskusi dan observasi, sosialisasi dan penyuluhan, melaksanakan pelatihan, perancangan alat dan pemasangan alat. Hasil luaran dari kegiatan ini berupa produk teknologi tepat guna berupa lampu bertenaga solar panel, produk gerabah, kursi, dan gazebo untuk penambahan fasilitas pedukung, dan memberikan informasi kepada masyarakat luas melalui media massa.
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.
Implementation of GLCM for Features Extraction and Selection of Batik Images Dhimas Arief Dharmawan; Latifah Listyalina
Journal of Electrical Technology UMY Vol 2, No 1 (2018)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.2128

Abstract

Batik is a craft that has high artistic value and has been a part of Indonesian culture (especially Java) for a long time. Batik cloth in Indonesia has various types of batik textures, batik cloth colors, and batik fabric patterns that reflect the regional origins of the batik cloth. Regarding the image of batik, the texture feature is an important feature because the ornaments on the batik cloth can be seen as different texture compositions. Besides batik motifs, also influenced by the shape characteristics that become parts of each batik motif. This research will add insight and knowledge to understand batik patterns based on the characteristics of batik motifs, namely texture. There are five batik motifs used, namely inland solo batik, semarang coastal batik, sidhomukti batik, parangklithik batik, and sidhodrajat batik. Initially preprocessing is done by cropping and grayscalling. Of the five image motifs, a cropping process is carried out for each motif. The next step is feature extraction. The features of GLCM were selected in this study. From the features contained in the GLCM, in this study four features were chosen, namely contrast, energy, correlation, and homogeneity. The final step is the selection or selection of features. The result of the feature selection of the four features carried out feature extraction are energy and homogeneity.
Co-Authors Adetya, Nais Pinta Agus Qomaruddin Munir Andri Saputra Ariyanto, Ipan Bagus Seno Wulung, Raden Desty Ervira Puspaningtyas Dharmawan, Dhimas Arief Dwi Wibowo, Midarto Eko Susilo Evrita Lusiana Utari Evrita Lusiana Utari Evrita Lusiana Utari, Evrita Lusiana Hanung Adi Nugroho Ikhwan Mustiadi Irawadi Buyung, Irawadi Mario Sarisky Dwi Ellianto Muh. Wahyu Syabani Novi Irawati Oktoeberza, Widhia KZ Pambudi, Wisnu Pani Satwikanitya Putri, Naimah Ratnaningsih, Wahyu Ratri Retno Utami RR. Ella Evrita Hestiandari Sabdullah, Mursid Sarisky Dwi Ellianto, Mario Satwikanitya, Pani Sugeng Winardi Sunu Wibirama Suwarno, Yuli Uma Fadzilia Arifin Uma Fadzilia Arifin, Uma Fadzilia Wahyu Ratnaningsih Wijaya, Nurhadi Wisnu Pambudi Yudianingsih Yudianingsih Yudianingsih, Yudianingsih