Articles
<![CDATA[Analysis of Document Clustering based on Cosine Similarity and K-Main Algorithms ]]>
<![CDATA[Bambang Krismono Triwijoyo]]>;
<![CDATA[Kartarina Kartarina]]>
<![CDATA[ Journal of Information System and Informatics Vol 1 No 2 (2019): Journal of Information Systems and Informatics ]]>
Publisher : <![CDATA[Universitas Bina Darma ]]>
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DOI: 10.33557/journalisi.v1i2.18
<![CDATA[Clustering is a useful technique that organizes a large number of non-sequential text documents into a small number of clusters that are meaningful and coherent. Effective and efficient organization of documents is needed, making it easy for intuitive and informative tracking mechanisms. In this paper, we proposed clustering documents using cosine similarity and k-main. The experimental results show that based on the experimental results the accuracy of our method is 84.3%.]]>
<![CDATA[Analisis Perubahan Ukuran Citra Medis Menggunakan Algoritma Interpolasi Bikubik ]]>
<![CDATA[Bambang Krismono Triwijoyo]]>;
<![CDATA[Ahmat Adil]]>
<![CDATA[ Jurnal Ilmu Komputer Vol 14 No 1 (2021): Jurnal Ilmu Komputer ]]>
Publisher : <![CDATA[Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University ]]>
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DOI: 10.24843/JIK.2021.v14.i01.p03
<![CDATA[Image interpolation is the most basic requirement for many image processing tasks such as medical image processing. Image interpolation is a technique used in resizing an image. To change the image size, each pixel in the new image must be remapped to a location in the old image to calculate the new pixel value. There are many algorithms available for determining the new pixel value, most of which involve some form of interpolation between the closest pixels in the old image. In this paper, we use the Bicubic interpolation algorithm to change the size of medical images from the Messidor dataset and then analyze it by measuring it using three parameters Mean Square Error (MSE), Root Mean Squared Error (RMSE), and Peak Signal-to-Noise Ratio (PSNR), and compare the results with Bilinear and Nearest-neighbor algorithms. The results showed that the Bicubic algorithm is better than Bilinear and Nearest-neighbor and the larger the image dimensions are resized, the higher the degree of similarity to the original image, but the level of computation complexity also increases.]]>
<![CDATA[ANALISA SPASIAL SEBARAN PEMUKIMAN DI PULAU RINCA (Kawasan Taman Nasional Komodo) ]]>
<![CDATA[Ahmat Adil]]>;
<![CDATA[Bambang Krismono Triwijoyo]]>
<![CDATA[ SENTIA 2015 Vol 7, No 2 (2015) ]]>
Publisher : <![CDATA[SENTIA 2015 ]]>
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<![CDATA[Permukiman merupakan kebutuhan perorangan (individu) namun dapat berkembang menjadi kebutuhan bersama jika manusia berkeluarga dan bermasyarakat. Selain sebagai makhluk individu manusia juga sebagai makhluk sosial maka manusia tidak hidup sendiri-sendiri akan tetapi hidup bersama dan membentuk kelompok�kelompok. Menurut data statistik Kecamatan komodo tahun 2012 ada 4 desa yang terdapat di kawasan TNK yaitu desa Pasir Panjang (pulau Rinca dan sekitarnya) dengan jumlah 386 kepala keluarga atau jumlah penduduk 1.557, desa Komodo dengan 397 kepala keluarga dan jumlah penduduk 1.404 orang, desa pasir putih dengan 534 kepala keluarga dan jumlah penduduk mencaai 2.383 jiwa, dan desa papagarang dengan 327 kepala keluarga dengan jumlah jiwa mencapai 1.256 orang. Khusus untuk pulau Renca (desa Pasir Panjang), dihuni oleh 2 pemukiman yaitu kampung Renca dan kerora. Kedua kampung ini terus berkembang dari tahun ketahun,menyebabkan areal pemukiman semakin bertambah. Analisis spasial dimaksudkan untuk menentukan lokasi penyebaran pemukiman penduduk disesuaikan dengan habitat komodo dan zonasi yang ditetapkan oleh pengelola taman nasional agar tidak terjadi konflik antara pengelola Taman nasional Komodo dan masyarakat sekitarnya.]]>
<![CDATA[SEGMENTASI CITRA PEMBULUH DARAH RETINA MENGGUNAKAN METODE DETEKSI GARIS MULTI SKALA ]]>
<![CDATA[Bambang Krismono Triwijoyo]]>
<![CDATA[ MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 15 No 1 (2015) ]]>
Publisher : <![CDATA[LPPM Universitas Bumigora ]]>
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DOI: 10.30812/matrik.v15i1.28
<![CDATA[Changes in retinal blood vessels feature a sign of serious illnesses such as heart disease and stroke. Therefore, the analysis of retinal vascular features can help in detecting these changes and allow patients to take preventive measures at an early stage of this disease. Automation of this process will help reduce the costs associated with the specialist and eliminate inconsistencies that occur in manual detection system. Among the retinal image analysis, image extraction retinal blood vessels is a crucial step before measurement. In this paper, we use an effective method of automatically extracting the blood vessels of the color images of the retina using a length detector line in several different scales, in order to maintain the strength and eliminates the weaknesses of each detector individual lines, the result of the detection lines on various scales combined to produce a segmentation of each image of the retina. The performance of the method is evaluated quantitatively using DRIVE dataset. Test results show that this method achieve high accuracy is 0.9407 approaching measurement results manually by experts, and this method produces accurate segmentation in detecting retinal blood vessels with effciency by quickly segmenting time is 2.5 seconds per image.]]>
<![CDATA[SEGMENTASI CITRA MRI MENGGUNAKAN DETEKSI TEPI UNTUK IDENTIFIKASI KANKER PAYUDARA ]]>
<![CDATA[Ervina Farijki]]>;
<![CDATA[Bambang Krismono Triwijoyo]]>
<![CDATA[ MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 15 No 2 (2016) ]]>
Publisher : <![CDATA[LPPM Universitas Bumigora ]]>
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DOI: 10.30812/matrik.v15i2.38
<![CDATA[One type of cancer that is capable identifed using MRI technology is breast cancer. Breast cancer is still the leading cause of death world. therefore early detection of this disease is needed. In identifying breast cancer, a doctor or radiologist analyzing the results of magnetic resonance image that is stored in the format of the Digital Imaging Communication In Medicine (DICOM). It takes skill and experience suffcient for diagnosis is appropriate, and accurate, so it is necessary to create a digital image processing applications by utilizing the process of object segmentation and edge detection to assist the physician or radiologist in identifying breast cancer. MRI image segmentation using edge detection to identifcation of breast cancer using a method stages gryascale change the image format, then the binary image thresholding and edge detection process using the latest Robert operator. Of the 20 tested the input image to produce images with the appearance of the boundary line of each region or object that is visible and there are no edges are cut off, with the average computation time less than one minute.]]>
<![CDATA[Model Fast Tansfer Learning pada Jaringan Syaraf Tiruan Konvolusional untuk Klasifikasi Gender Berdasarkan Citra Wajah ]]>
<![CDATA[Bambang Krismono Triwijoyo]]>
<![CDATA[ MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 18 No 2 (2019) ]]>
Publisher : <![CDATA[LPPM Universitas Bumigora ]]>
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DOI: 10.30812/matrik.v18i2.376
<![CDATA[The face is a challenging object to be recognized and analyzed automatically by a computer in many interesting applications such as facial gender classification. The large visual variations of faces, such as occlusions, pose changes, and extreme lightings, impose great challenge for these tasks in real world applications. This paper explained the fast transfer learning representations through use of convolutional neural network (CNN) model for gender classification from face image. Transfer learning aims to provide a framework to utilize previously-acquired knowledge to solve new but similar problems much more quickly and effectively. The experimental results showed that the transfer learning method have faster and higher accuracy than CNN network without transfer learning.]]>
<![CDATA[Developing Application in Anticipating DDoS Attacks on Server Computer Machines ]]>
<![CDATA[Anthony Anggrawan]]>;
<![CDATA[Raisul Azhar]]>;
<![CDATA[Bambang Krismono Triwijoyo]]>;
<![CDATA[Mayadi Mayadi]]>
<![CDATA[ MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 20 No 2 (2021) ]]>
Publisher : <![CDATA[LPPM Universitas Bumigora ]]>
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DOI: 10.30812/matrik.v20i2.410
<![CDATA[The use of server computer machines in companies is primarily a web hosting server that is very easy to experience threats, especially external security threats such as attempts to infiltrate, hacking, viruses, and other malicious attacks. Having a secure server is indispensable for working online and especially if involved in business-related network transactions. The Server's realization to be safe from threats is to protect the server machine's security on the hardware and software side and pay attention to network security that goes to the server machine. Generally, firewall applications on router devices have configuration limitations in securing the network, namely non-integrated applications. In other words, it is necessary to manage the perfect firewall configuration to anticipate Distributed Daniel attacks of Service (DDoS) attacks. Therefore, this study aims to integrate existing firewall applications for router devices into an integrated program to secure the network. The methodology used is the Network Development Life Cycle (NDLC). The research results on this developed application program can overcome DDoS attacks without setting up a firewall on the router device and can automatically monitor DDoS attack activities from outside the Server. Securing servers from DDoS attacks without setting up a firewall on the router device and automating the monitoring of DDoS attack activity from outside the Server are the novelties of this study that have not been available in previous studies.]]>
<![CDATA[Sistem Informasi Geografis Pemetaan Jaringan Irigasi dan Embung di Lombok Tengah ]]>
<![CDATA[Ahmat Adil]]>;
<![CDATA[Bambang Krismono Triwijoyo]]>
<![CDATA[ MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 20 No 2 (2021) ]]>
Publisher : <![CDATA[LPPM Universitas Bumigora ]]>
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DOI: 10.30812/matrik.v20i2.1112
<![CDATA[Irigasi sebagai alternatif pengairan lahan tadah hujan pada musim kemarau, digunakan untuk meningkatkan produksi hasil pertanian. Pemetaan Jaringan irigasi dan embung pada Kabupaten Lombok Tengah menggunakan sistem data spasial dan non-spasial, yang selama ini masih menggunakan pemetaan secara konvensional. Data Spasial dapat menunjuk posisi geografis dengan setiap karakteristik memiliki satu lokasi yang harus ditentukan dengan cara yang unik. Pemetaan dengan model data spasial, dirancang dengan tahapan seperti analisa kebutuhan perangkat lunak, desain, pembuatan kode program dan pengujian. Metode yang digunakan dalam penelitian ini adalah Analisis spasial, merupakan kumpulan – kumpulan dari teknik yang dapat digunakan untuk melakukan pengolahan data SIG. Hasil dari analisis data spasial sangat bergantung dari lokasi atau tempat di mana objek sedang dianalisis. Manipulasi data, akan menampilkan jendela manipulasi data non-spasial jaringan irigasi, embung, dan kecamatan. Pada jendela manipulasi data, pengguna dapat melakukan penambahan, perubahan dan penghapusan terhadap data tabular yang ada, dan memiliki fasilitas pencarian sesuai dengan data yang sedang diakses.]]>
<![CDATA[Convolutional Neural Network With Batch Normalization for Classification of Emotional Expressions Based on Facial Images ]]>
<![CDATA[Bambang Krismono Triwijoyo]]>;
<![CDATA[Ahmat Adil]]>;
<![CDATA[Anthony Anggrawan]]>
<![CDATA[ MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 21 No 1 (2021) ]]>
Publisher : <![CDATA[LPPM Universitas Bumigora ]]>
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DOI: 10.30812/matrik.v21i1.1526
<![CDATA[Emotion recognition through facial images is one of the most challenging topics in human psychological interactions with machines. Along with advances in robotics, computer graphics, and computer vision, research on facial expression recognition is an important part of intelligent systems technology for interactive human interfaces where each person may have different emotional expressions, making it difficult to classify facial expressions and requires training data. large, so the deep learning approach is an alternative solution., The purpose of this study is to propose a different Convolutional Neural Network (CNN) model architecture with batch normalization consisting of three layers of multiple convolution layers with a simpler architectural model for the recognition of emotional expressions based on human facial images in the FER2013 dataset from Kaggle. The experimental results show that the training accuracy level reaches 98%, but there is still overfitting where the validation accuracy level is still 62%. The proposed model has better performance than the model without using batch normalization.]]>
<![CDATA[Aplikasi Spasial Rekomendasi Wisata Terdekat dengan Metode Haversine Berbasis Mobile ]]>
<![CDATA[Ahmat Adil]]>;
<![CDATA[Risca Anggraeni Dwiputri]]>;
<![CDATA[Bambang Krismono Triwijoyo]]>
<![CDATA[ Jurnal Bumigora Information Technology (BITe) Vol 4 No 1 (2022) ]]>
Publisher : <![CDATA[Prodi Ilmu Komputer Universitas Bumigora ]]>
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DOI: 10.30812/bite.v4i1.1948
<![CDATA[Banyaknya pergerakan wisatawan nusantara berarti makin besar dan dinamis dampaknya pada pergerakan dan pertumbuhan ekonomi negara. Maka untuk memudahkan wisatawan dalam mengunjungi lokasi yang diinginkan diperlukan aplikasi yang dapat merekomendasikan objek wisata terdekat dengan memanfaatkan koordinat geolocation yang diterapkan pada metode haversine. Metode geolocation merupakan fasilitas dari google maps api di gunakan untuk menemukan lokasi pengguna dengan IP address, dedicated GPS atau embedded GPS yang mengandung nilai latitude dan longtitud untuk pengembangan aplikasi menggunakan GRAPPLE (Guidelines for Rapid Application Engineering) yang mempunyai 5 tahapan yaitu, Requirement Gathering, Analysis, Design, Development, Deployment. Sebagai contoh hasil aplikasi adalah destinasi wisata Air Terjun Tiu Kelep terletak pada latitude : -8.3113 dan longitude: 116.404, dengan lokasi user saat ini terlatak pada latitude : -8.27963 dan longitude 116.4166, dengan alat = -0.14505950121–(-0.144506804347)= -0.0005527457741, long = 2.0316330624915-2.0318529739772 =-0.00021991148575. Kesimpulan dari penelitian ini yaitu aplikasi yang di bangun dapat digunakan dengan layak, sehingga dapat dimanfaat oleh wisatawan lokal atau mancanegara dalam mendapatkan rekomendasi wisata dengan ranting terbaik dan jarak terdekat]]>
