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All Journal Telematika : Jurnal Informatika dan Teknologi Informasi Seminar Nasional Informatika (SEMNASIF) Compiler
Bambang Yuwono
Universitas Pembangunan Nasional Veteran Yogyakarta
Computer Science & IT Electrical & Electronics Engineering

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Content Based Image Retrieval Using Gray Level Co-Occurrence Matrix to Detect Pneumonia in X-Ray Thorax Image Wilis Kaswidjanti; Bambang Yuwono; Nisa’ul Azizah; Nur Heri Cahyana
Telematika Vol 18, No 2 (2021): Edisi Juni 2021
Publisher : Jurusan Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v18i2.5508

Abstract

Purpose:This study aims to detect the presence of pneumonia or not in thorax x-ray images using the Gray Level Co-Occurence Matrix (GLCM) method as well as find out the accuracy of the accuracy of pneumonia detection accuracy.Design/methodology/approach:The process of detecting pneumonia in thorax x-ray images can use Content Based Image Retriveal (CBIR). CBIR is an image search method by comparing the input image feature with the image feature in the database. Extraction features x-ray texture of thorax in pneumonia detection using Color Histogram, Discrete Cosine Transform and Gray Level Cooccurence Matrix (GLCM). From the day of extraction the feature will be carried out similarity measurements with database images using Euclidean Distance..Findings/result: The test results showed that the GLCM extraction feature with euclidean distance similarity measurements gained 95% accuracy on 100 training data and 20 test data, with the number of images displayed 6. Whereas when testing using data that has been trained produces 100% accuracy.Originality/value/state of the art:The difference between this study and previous research is in the pre-processing method section of imagery. This pre-processing process, x-ray image of thorax is carried out color histogram and discrete cosine transform process. Then continued the extraction of features using GLCM. The output of this system is the result of detection whether normal or pneumonia. Tujuan:Penelitian ini bertujuan untuk mendeteksi adanya Pneumonia atau tidak pada citra x-ray thorax menggunakan metode Gray Level Co-Occurence Matrix (GLCM) serta mengetahui akurasi tingkat akurasi deteksi pneumonia.Perancangan/metode/pendekatan:Proses deteksi penyakit Pneumonia pada citra x-ray thorax dapat menggunakan Content Based Image Retriveal (CBIR). CBIR adalah suatu metode pencarian citra dengan melakukan perbandingan antara fitur citra input dengan fitur citra yang ada didalam database. Ekstraksi  fitur tekstur x-ray thorax dalam deteksi pneumonia menggunakan Color Histogram, Discrete Cosine Transform dan Gray Level Cooccurence Matrix (GLCM). Dari hari ekstraksi fitur tersebut akan dilakukan pengukuran kemiripan dengan citra database menggunakan jarak Euclidean Distance.Hasil:Hasil pengujian menunjukkan bahwa fitur ekstraksi GLCM dengan pengukuran kemiripan Euclidean Distance diperoleh akurasi sebesar 95% pada data latih 100 dan data uji 20, dengan jumlah citra yang ditampilkan 6. Sedangkan bila pengujian menggunakan data yang sudah dilatihkan menghasilkan akurasi 100%.State of the art:Perbedaan penelitian ini dengan penelitian sebelumnya adalah pada bagian metode pre processing citra. Proses pre processing  ini,  citra x-ray thorax di lakukan proses Color Histogram dan Discrete Cosine Transform. Kemudian dilanjutkan ekstraksi fitur menggunakan GLCM. Output dari sistem ini berupa hasil deteksi apakah normal atau pneumonia.
PENERAPAN METODE MULTI ATTRIBUTE UTILITY THEORY (MAUT) DALAM PEMETAAN TINGKAT DAMPAK BENCANA BANJIR DI KABUPATEN BANTUL Afif Irfan Abdurrahman; Bambang Yuwono; Yuli Fauziah
Telematika Vol 17, No 1 (2020): Edisi April 2020
Publisher : Jurusan Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v17i1.3402

Abstract

Flood disaster is a dangerous disaster, an event that occurs due to overflow of water resulting in submerged land is called a flood disaster. Almost every year Bantul Regency is affected by floods due to high rainfall. The flood disaster that struck in Bantul Regency made the Bantul District Disaster Management Agency (BPBD) difficult to handle so that it needed a mapping of the level of the impact of the flood disaster to minimize the occurrence of floods and provide information to the public.This study will create a system to map the level of impact of floods in Bantul Regency with a decision support method namely Multi Attribute Utility Theory (MAUT). The MAUT method stage in determining the level of impact of flood disasters through the process of normalization and matrix multiplication. The method helps in determining the areas affected by floods, by managing the Indonesian Disaster Information Data (DIBI). The data managed is data on criteria for the death toll, lost victims, damage to houses, damage to public facilities, and damage to roads. Each criteria data has a value that can be used to determine the level of impact of a flood disaster. The stages for determining the level of impact of a disaster require a weighting calculation process. The results of the weighting process display the scoring value which has a value of 1 = low, 2 = moderate, 3 = high. To assist in determining the affected areas using the matrix normalization and multiplication process the process is the application of the Multi Attribute Utility Theory (MAUT) method.This study resulted in a mapping of the level of impact displayed on google maps. The map view shows the affected area points and the level of impact of the flood disaster in Bantul Regency. The mapping produced from the DIBI data in 2017 produced the highest affected area in the Imogiri sub-district. The results of testing the data can be concluded that the results of this study have an accuracy rate of 95% when compared with the results of the mapping previously carried out by BPBD Bantul Regency. The difference in the level of accuracy is because the criteria data used are not the same as the criteria data used by BPBD in Bantul Regency so that the accuracy rate is 95%.
Evaluation Of Jogja Application Success From User's Perspective Using Development of Delone And Mclean Models To Support The Realization Of The Smart Province Angelica Amartya Putri; Herlina Jayadianti; Bambang Yuwono
Telematika Vol 18, No 2 (2021): Edisi Juni 2021
Publisher : Jurusan Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v18i2.5316

Abstract

Purpose: This study aims to measure success and determine the factors that support or hinder the success of the Jogja Istimewa application.Methodology: This study uses a modified DeLone and McLean Model 2003. The data used are primary data obtained from interviews with the DISKOMINFO and answers to 125 users of the Jogja Istimewa application as respondents in a distributed questionnaire. The results of the questionnaire were processed using SPSS to test the validity, reliability and normality of the data. After that, the data is processed using Structural Equation Modeling (SEM) to test the inner model and outer model which includes hypothesis testing.Result There are nine hypotheses tested using the SEM model. Nine hypotheses were proposed, it was stated that five hypotheses were accepted and four other hypotheses were rejected. the Jogja Istimewa application has a high success rate. The factors that are stated to influence the success of the Jogja Istimewa application are Information Quality, Service Quality, System Quality and User Satisfaction. The factors that are stated to hinder the success of the Jogja Istimewa application are Format of Output and Reliability in the Information Quality variable, the System Quality variable in the Language indicator, and the Charges for System Use indicator on the Intention to Use variable.Value: Based on previous research, this study has a fairly similar reference but different case studies, indicators, and conceptual models to test hypotheses in addition to knowing the factors that hinder and support the success of the Jogja Istimewa application.
PEMETAAN DATA RECHARGE AIR TANAH DI KABUPATEN SLEMAN BERDASARKAN DATA CURAH HUJAN Bambang Yuwono; Awang Hendrianto Pratomo; Heru Cahya Rustamaji; Puji Pratiknyo; Mochammad Assofa Indera Jati
Telematika Vol 13, No 2 (2016): Edisi Juli 2016
Publisher : Jurusan Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v13i2.1725

Abstract

Water is a basic need for humans and other living things. Various sources of water on this earth has formed a system of close interaction with the components of living things in it. Over the years, water resources have changed in terms of both quality and quantity. This can be due to population growth in addition to the natural changes in nature. The more narrow field of water absorption followed by high water consumption causes the supply of ground water reserves can be threatened. So, we need a mapping and ground water recharge calculations to assist in the monitoring of groundwater reserves.The method used in this research is the Water Balance (keseimbangan air)method. This method is based on any incoming rain water will be equal to the output evapotranspiration and runoff hereinafter this method is applied in the application. Factors affecting groundwater recharge the water balance method is precipitation, evapotranspiration and run off. Information og groundwater recharge is also displayed on the map using Google Map function are related to the database system to produce informative mapsCalculation of groundwater recharge is applied to the daily rainfall data input into the application which then included in the water balance equation method so it can be easy to determine the value of groundwater recharge. Groundwater recharge information can be displayed in the form of mapping, making them easier to understand visually.Based on testing, the highest recharge results of this research on the Kemput station is 1119,5 mm/year with rainfall of 2750 mm/year. Seyegan and Bronggang station is 1026,25 mm/year with rainfall of 2625 mm/year. Angin-angin and Prumpung station is 933 mm/year with rainfall of 2500 mm/year. Beran and Gemawang station is 839.5 mm/year with rainfall of 2375 mm/year. Plataran station is 808.42 mm/year with rainfall of 2333 mm/year. Godean station is 699.5 mm/year with rainfall of 2187 mm/year and the lowest at Tirto Tanjungand Santan stastion 560 mm / year with rainfall of 2000 mm / year.
Fish detection using morphological approach based on K means segmentation Shoffan Saifullah; Andiko Putro Suryotomo; Bambang Yuwono
Compiler Vol 10, No 1 (2021): May
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1221.396 KB) | DOI: 10.28989/compiler.v10i1.946

Abstract

Image segmentation is a concept that is often used for object detection. This detection has difficulty detecting objects with backgrounds that have many colors and even have a color similar to the object being detected. This study aims to detect fish using segmentation, namely segmenting fish images using k-means clustering. The segmentation process is processed by improving the image first. The initial process is preprocessing to improve the image. Preprocessing is done twice, before segmentation using k-means and after. Preprocessing stage 1 using resize and reshape. Whereas after k-means is the contrast-limited adaptive histogram equalization. Preprocessing results are segmented using k-means clustering. The K-means concept classifies images using segments between the object and the background (using k = 8). The final step is the morphological process with open and close operations to obtain fish contours using black and white images based on grayscale images from color images. Based on the experimental results, the process can run well, with the ssim value close to 1, which means that image information does not change. Processed objects provide a clear picture of fish objects so that this k-means segmentation can help detect fish objects.
Co-Authors Afif Irfan Abdurrahman Agus Sasmito Aribowo Andiko Putro Suryotomo Angelica Amartya Putri Awang Hendrianto Pratomo Azizah, Nisa’ul Danny Wijaksono Firna Sholihuda Sholihuda Heriyanto Heriyanto Herlina Jayadianti Herry Sofyan Heru Cahya Rustamadji Heru Cahya Rustamaji Heru Cahya Rustamaji Jalu Satrio Wibowo Jefri Hutama Arbi Mangaras Yanu F Mochammad Assofa Indera Jati Muhadjir Fachrurradjie Nandha Juniaroesita Peksi Nisa’ul Azizah Nur Heri Cahyana Nur Heri Cahyana Nur Heri Cahyana Oliver Samuel Simanjuntak Puji Pratiknyo Saifullah, Shoffan Simon Pulung Nugroho Siswanto Budi Wardoyo, Siswanto Budi Usamah Dani, Usamah Wilis Kaswidjanti Wilis Kaswidjanti Wilis Kaswidjanti Yuli Fauziah