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<![CDATA[Perancangan Sistem Informasi Keuangan Berbasis Web Multi User Dengan UML ]]>
<![CDATA[Rusydi Umar]]>;
<![CDATA[Sarjimin Sarjimin]]>;
<![CDATA[Arief Setyo Nugroho]]>;
<![CDATA[Achmad Dito]]>;
<![CDATA[Indra Gunawan]]>
<![CDATA[ Jurnal Algoritma Vol 17 No 2 (2020): Jurnal Algoritma ]]>
Publisher : <![CDATA[Institut Teknologi Garut ]]>
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DOI: 10.33364/algoritma/v.17-2.204
<![CDATA[STIE XYZ in managing financial transactions still uses Microsoft Excel which is divided by year and type of payment. The purpose of this research is to build a systemized alternative application for managing financial transactions in accordance with financial management at STIE XYZ. Rapid Application Development (RAD) system development method was chosen because in this method a system can be developed within 180 days and the users are directly involved when developing the system so that the system is developed according to user needs. The RAD design process uses the Unified Modeling Language (UML) method. Dimension of Quality for Goods (Operations, Reliability and Durability, Conformance, Service Ability, Appearance and Perceived, and Quality) test scores> 75.50, 76.50 so that it can be concluded that the product is declared successful, the results of the benefit testing are based on the variables Usability, Learnability, Efficiency and Acceptability (ULEA) produces a value> 70 that is 90.65% so that it can be declared useful. Keywords: Finance, RAD, UML, ULEA]]>
<![CDATA[Deteksi Keaslian Citra Menggunakan Metode Error Level Analysis (ELA) dan Principal Component Analysis (PCA) ]]>
<![CDATA[Dewi Astria Faroek]]>;
<![CDATA[Rusydi Umar]]>;
<![CDATA[Imam Riadi]]>
<![CDATA[ FORMAT Vol 8, No 2 (2019) ]]>
Publisher : <![CDATA[Universitas Mercu Buana ]]>
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DOI: 10.22441/format.2019.v8.i2.006
<![CDATA[Kemajuan teknologi yang ada pada citra digital mempengaruhi banyak kemungkinan pada perangkat pencitraan dengan resolusi yang tinggi dengan biaya yang rendah. Hal ini dapat dimanfaatkan oleh pihak-pihak tertentu dalam memanipulasi citra digital agar lebih baik hingga sangat jauh dari hasil citra aslinya. Pemalsuan citra adalah proses manipulasi pada sebagian atau seluruh daerah citra baik terhadap isi maupun konteks citra dengan bantuan teknik pemrosesan citra digital. Dengan manipulasi citra ini banyak pihak yang dapat melakukan sebuah tindakan kejahatan. Definisi forensik citra merupakan bidang ilmu yang digunakan untuk mengidentifikasi asal dan menverifikasi keaslian sebuah citra tersebut. Hal yang mendasari dalam melakukan deteksi keaslian citra adalah melakukan perbandingan antara dua image dan dua metode yaitu metode Error Level Analysis (ELA) dan Principal Component Analysis (PCA) dengan menggunakan tools forensically-beta. Penelitian ini diharapkan menunjukkan hasil yang baik dalam mendeteksi objek pada citra sehingga dapat membantu dalam mendeteksi citra yang asli dan citra yang telah dimanipulasi berdasarkan metode ELA dan PCA.]]>
<![CDATA[Rancang Bangun Klasifikasi Citra Dengan Teknologi Deep Learning Berbasis Metode Convolutional Neural Network ]]>
<![CDATA[Ari Peryanto]]>;
<![CDATA[Anton Yudhana]]>;
<![CDATA[Rusydi Umar]]>
<![CDATA[ FORMAT Vol 8, No 2 (2019) ]]>
Publisher : <![CDATA[Universitas Mercu Buana ]]>
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DOI: 10.22441/format.2019.v8.i2.007
<![CDATA[Dengan berkembang pesatnya teknologi saat ini, mengakibatkan Deep Learning menjadi salah satu metode machine learning yang sangat diminati. Teknologi GPU Acceleration menjadi salah satu sebab dari pesatnya perkembangan Deep Learning. Deep learning sangat cocok digunakan untuk memecahkan permasalahan klasik dalam Computer Vision, yaitu dalam pengklasifikasian citra. Salah satu metode dalam deep learning yang sering digunakan dalam pengolah citra adalah Convolutional Neural Network dan merupakan pengembangan dari Multi Layer Perceptron. Pada penelitian ini pengimplementasian metode ini dilakukan menggunakan library keras dengan bahasa pemrograman phyton. Pada proses training menggunakan Convolutional Neural Network, dilakukan setting jumlah epoch dan memperbesar ukuran data training untuk meningkatkan akurasi dalam pengklasifikasian citra. Ukuran yang digunakan adalah 32x32, 64x64 dan 128x128. Proses training dengan jumlah epoch 40 dan ukuran 32x32 didapat nilai akurasi tertinggi yang mencapai 98,02% dan rata-rata akurasi tertinggi yaitu 97,56 %, serta akurasi sistem sebesar 96,64%.]]>
<![CDATA[RESEARCH ON SECURE VIRUS TROJAN IN CYBERSECURITY PLATFORM ]]>
<![CDATA[Ahmad Fajar Sidiq]]>;
<![CDATA[Rusydi Umar]]>;
<![CDATA[Anton Yudhana]]>
<![CDATA[ JSI (Jurnal sistem Informasi) Universitas Suryadarma Vol 5, No 2 (2018): JSI (Jurnal sistem Informasi) Universitas Suryadarma ]]>
Publisher : <![CDATA[Universitas Dirgantara Marsekal Suryadarma ]]>
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DOI: 10.35968/jsi.v5i2.247
<![CDATA[Security is main issue of this generation of computing because many types of attacks are increasing day by day. Establishing a network is not a big issue for network administrators but protecting the entire network is a big issue. There are various methods and tools are available today for destroying the existing network. In this paper we mainly emphasize on the network security also we present some major issues that can affect our network, Trojan horse virus can give rise to the leakage of internal data. Keywords:Security, Trojan Horse, System, Network.]]>
<![CDATA[INOVASI PROMOSI OBYEK WISATA PURBALINGGA MENGGUNAKAN TEKNOLOGI VIRTUAL REALITY 360 PANORAMA BERBASIS ANDROID ]]>
<![CDATA[Gema Kharismajati]]>;
<![CDATA[Rusydi Umar]]>;
<![CDATA[Sunardi Sunardi]]>
<![CDATA[ JIKO (Jurnal Informatika dan Komputer) Vol 3, No 2 (2020) ]]>
Publisher : <![CDATA[Journal Of Informatics and Computer ]]>
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DOI: 10.33387/jiko.v3i2.1756
<![CDATA[Purbalinga adalah salah satu kabupaten di Provinsi Jawa Tengah yang menarik untuk dikunjungi wisatawan. Potensi wisata dapat meningkatkan pendapatan dan memberi pengaruh penting dalam perkembangan daerah apalagi jika didukung oleh promosi yang menarik. Salah satu teknologi yang dapat digunakan sebagai penarik minat adalah tersedianya Virtual Reality (VR) yang membawa pengguna dapat berinteraksi dalam lingkungan di dunia maya yang disimulasikan oleh komputer, sehingga pengguna merasa berada didalamnya. Penelitian ini melakukan perancangan dan implementasi aplikasi promosi obyek wisata Kabupaten Purbalingga menggunakan teknologi VR berbasis Android. Penampilan obyek gambar menggunakan panorama 360o sehingga mampu menampilkan gambar tanpa batas dan tidak terpotong serta dapat melihat sekeliling gambar. Pengguna membutuhkan VR Headset untuk menampilkan obyek secara virtual. Pembuatan aplikasi dilakukan dengan metode Multimedia Development Life Cycle (MDLC) dan Unity3D. Aplikasi telah berhasil dioperasikan pada Sistem Operasi Andorid dengan spesifikasi minimal RAM 2GB serta OS Versi 4.4 Kitkat. Hasil penelitian telah dilakukan pengujian melalui kuesioner kepada 10 responden dengan 11 pertanyaan didapatkan rata-rata skor 488 atau persentase kelayakan sebesar 88,72% yang menyatakan bahwa aplikasi sangat layak digunakan. Berdasarkan pengujian black box didapatkan bahwa aplikasi telah berjalan dengan baik dan dapat menampilkan 3600 panorama beserta informasinya.]]>
<![CDATA[Analisis Bentuk Pola Suara Menggunakan Ekstraksi Ciri Mel-Frequencey Cepstral Coefficients (MFCC) ]]>
<![CDATA[Rusydi Umar]]>;
<![CDATA[Imam Riadi]]>;
<![CDATA[Abdullah Hanif]]>
<![CDATA[ CogITo Smart Journal Vol 4, No 2 (2018): CogITo Smart Journal ]]>
Publisher : <![CDATA[Fakultas Ilmu Komputer, Universitas Klabat ]]>
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DOI: 10.31154/cogito.v4i2.130.294-304
<![CDATA[Sound is a part of the human body that is unique and can be distinguished, so its application can be used in sound pattern recognition technology, one of which is used for sound biometrics. This study discusses the analysis of the form of a sound pattern that aims to determine the shape of the sound pattern of a person's character based on the spoken voice input. This study discusses the analysis of the form of a sound pattern that aims to determine the shape of the sound pattern of a person's character based on the spoken voice input. This study uses the Melf-Frequency Cepstrum Coefficients (MFCC) method for feature extraction process from speaker speech signals. The MFCC process will convert the sound signal into several feature vectors which will then be displayed in graphical form. Analysis and design of sound patterns using Matlab 2017a software. Tests were carried out on 5 users consisting of 3 men and 2 women, each user said 1 predetermined "LOGIN" word, which for 15 words said. The results of the test are the form of a sound pattern between the characteristics of 1 user with other users. Keywords—Voice, Pattern, Feature Extraction, MFCC]]>
<![CDATA[Klasifikasi Citra Menggunakan Convolutional Neural Network dan K Fold Cross Validation ]]>
<![CDATA[Ari Peryanto]]>;
<![CDATA[Anton Yudhana]]>;
<![CDATA[Rusydi Umar]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol 4 No 1 (2020): Juli 2020 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v4i1.2017
<![CDATA[Image classification is a fairly easy task for humans, but for machines it is something that is very complex and is a major problem in the field of Computer Vision which has long been sought for a solution. There are many algorithms used for image classification, one of which is Convolutional Neural Network, which is the development of Multi Layer Perceptron (MLP) and is one of the algorithms of Deep Learning. This method has the most significant results in image recognition, because this method tries to imitate the image recognition system in the human visual cortex, so it has the ability to process image information. In this research the implementation of this method is done by using the Keras library with the Python programming language. The results showed the percentage of accuracy with K = 5 cross-validation obtained the highest level of accuracy of 80.36% and the highest average accuracy of 76.49%, and system accuracy of 72.02%. For the lowest accuracy obtained in the 4th and 5th testing with an accuracy value of 66.07%. The system that has been made has also been able to predict with the highest average prediction of 60.31%, and the highest prediction value of 65.47%.]]>
<![CDATA[A Komparasi Image Matching Menggunakan Metode K-Nearest Neightbor (KNN) dan Support Vector Machine (SVM) ]]>
<![CDATA[Rusydi Umar]]>;
<![CDATA[Imam Riadi]]>;
<![CDATA[Dewi Astria Faroek]]>
<![CDATA[ Journal of Applied Informatics and Computing Vol 4 No 2 (2020): Desember 2020 ]]>
Publisher : <![CDATA[Politeknik Negeri Batam ]]>
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DOI: 10.30871/jaic.v4i2.2226
<![CDATA[Image matching is the process of finding digital images that have a degree of similarity. matching images using the classification method. In measuring image matching, the images used are original logo images and manipulated logo images. Comparison of classification algorithms from the two methods namely K-Nearest Neighbor (KNN) and Support Vector Machine with Sequential Minimal Optimization (SMO) optimization used to calculate matches based on accuracy values. The K-Nearest Neighbor (KNN) classification method is based on proximity or K calculations while the Support Vector Machine (SVM) classification method measures the distance between the hyperplane and the nearest data. Image match values are measured by Precision, Recall, F1-Score, and Accuracy. The image matching steps start from the preparation of data processing, extraction of HSV color features and shapes, then the classification stage. Digital images are used as many as 10 images consisting of one original logo and 9 manipulated logos. In the classification testing stage, using the WEKA application by applying the 10-fold cross-validation method. From the results of tests conducted that the closest k-neighbor (KNN) classification method is 80% and has a k = 0.889 which is quite good in measuring proximity, while the SVM classification method is 70%. The results of this image matching comparison can be concluded that the K-Nearest Neighbor classification method works better than SVM for image matching.]]>
<![CDATA[Analisis Kerentanan Serangan Cross Site Scripting (XSS) pada Aplikasi Smart Payment Menggunakan Framework OWASP ]]>
<![CDATA[Imam Riadi]]>;
<![CDATA[Rusydi Umar]]>;
<![CDATA[Tri Lestari]]>
<![CDATA[ JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 5 No. 3 (2020): November 2020 ]]>
Publisher : <![CDATA[UIN Sunan Kalijaga Yogyakarta ]]>
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DOI: 10.14421/jiska.2020.53-02
<![CDATA[E-commerce that is growing so rapidly can provide space for unauthorized parties in carrying out cybercrime, security anticipation is needed so that e-commerce applications can be protected from harassment or hacking attacks such as cross-site scripting (XSS), malware, exploits, and database injection. This research was conducted to determine the vulnerability of the Smart Payment application by self-test using the ZAP tool. This test is carried out to secure applications that serve as recommendations for follow-up in securing the Smart Payment application. The results of this study found vulnerabilities in the Smart Payment application. Vulnerabilities found were Information Disclosure-Suspicious Comments, X-Frame-Options Header not Set, X-Content-Type-Options Header Missing, Timestamp Disclosure-Unix, XSS Protection Not Enabled Web Browsers, and Directory Browsing. In addition to obtaining vulnerabilities from the Smart Payment application, solutions are also provided to overcome vulnerabilities in the Smart Payment application. ]]>
<![CDATA[Perancangan Sistem Informasi Keuangan Berbasis Web Multi User Dengan UML ]]>
<![CDATA[Rusydi Umar]]>;
<![CDATA[Sarjimin Sarjimin]]>;
<![CDATA[Arief Setyo Nugroho]]>;
<![CDATA[Achmad Dito]]>;
<![CDATA[Indra Gunawan]]>
<![CDATA[ Jurnal Algoritma Vol 17 No 2 (2020): Jurnal Algoritma ]]>
Publisher : <![CDATA[Institut Teknologi Garut ]]>
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DOI: 10.33364/algoritma/v.17-2.204
<![CDATA[STIE XYZ in managing financial transactions still uses Microsoft Excel which is divided by year and type of payment. The purpose of this research is to build a systemized alternative application for managing financial transactions in accordance with financial management at STIE XYZ. Rapid Application Development (RAD) system development method was chosen because in this method a system can be developed within 180 days and the users are directly involved when developing the system so that the system is developed according to user needs. The RAD design process uses the Unified Modeling Language (UML) method. Dimension of Quality for Goods (Operations, Reliability and Durability, Conformance, Service Ability, Appearance and Perceived, and Quality) test scores> 75.50, 76.50 so that it can be concluded that the product is declared successful, the results of the benefit testing are based on the variables Usability, Learnability, Efficiency and Acceptability (ULEA) produces a value> 70 that is 90.65% so that it can be declared useful. Keywords: Finance, RAD, UML, ULEA]]>
