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Rancang Bangun Klasifikasi Citra Dengan Teknologi Deep Learning Berbasis Metode Convolutional Neural Network Ari Peryanto; Anton Yudhana; Rusydi Umar
FORMAT Vol 8, No 2 (2019)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2019.v8.i2.007

Abstract

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%.
Klasifikasi Citra Menggunakan Convolutional Neural Network dan K Fold Cross Validation Ari Peryanto; Anton Yudhana; Rusydi Umar
Journal of Applied Informatics and Computing Vol 4 No 1 (2020): Juli 2020
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1169.96 KB) | DOI: 10.30871/jaic.v4i1.2017

Abstract

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%.
Analisis Recovery Bukti Digital Skype berbasis Smartphone Android Menggunakan Framework NIST Anton Yudhana; Abdul Fadlil; Muhammad Rizki Setyawan
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 4 (2020): Agustus 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i4.2093

Abstract

Cybercrime is an activity utilizing electronic devices and network technology as tools or media to commit crimes. One of them uses the Skype application that is installed on the smartphone. In finding evidence from a cybercrime case, a forensic activity known as digital forensic must be carried out. This study aims to recover digital evidence that has been erased using the NIST framework and forensic tools such as Oxygen and Belkasoft. The results of digital evidence recovery from smartphone Samsung J2 in the removal scenario via the application manager, the Oxygen tool cannot recover deleted data and the percentage of success using Belkasoft is 26%. While the results of data recovery with the manual removal method the percentage of success using Oxygen was 63% and Belkasoft was 44%. Digital evidence recovery results from smartphones Andromax A on the erase scenario through the application manager, Oxygen and Belkasoft tools cannot recover deleted data. While manual removal of Oxygen by 61% and Belkasoft cannot restore data. It can be concluded the results of data recovery from both smartphones that are used according to the erasure method through the application manager, Belkasoft has better performance than Oxygen, and data recovery according to the method of erasing manually, Oxygen has better performance than Belkasoft.
Analisis Recovery Bukti Digital Skype berbasis Smartphone Android Menggunakan Framework NIST Anton Yudhana; Abdul Fadlil; Muhammad Rizki Setyawan
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 4 (2020): Agustus 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i4.2093

Abstract

Cybercrime is an activity utilizing electronic devices and network technology as tools or media to commit crimes. One of them uses the Skype application that is installed on the smartphone. In finding evidence from a cybercrime case, a forensic activity known as digital forensic must be carried out. This study aims to recover digital evidence that has been erased using the NIST framework and forensic tools such as Oxygen and Belkasoft. The results of digital evidence recovery from smartphone Samsung J2 in the removal scenario via the application manager, the Oxygen tool cannot recover deleted data and the percentage of success using Belkasoft is 26%. While the results of data recovery with the manual removal method the percentage of success using Oxygen was 63% and Belkasoft was 44%. Digital evidence recovery results from smartphones Andromax A on the erase scenario through the application manager, Oxygen and Belkasoft tools cannot recover deleted data. While manual removal of Oxygen by 61% and Belkasoft cannot restore data. It can be concluded the results of data recovery from both smartphones that are used according to the erasure method through the application manager, Belkasoft has better performance than Oxygen, and data recovery according to the method of erasing manually, Oxygen has better performance than Belkasoft.
RESEARCH ON SECURE VIRUS TROJAN IN CYBERSECURITY PLATFORM Ahmad Fajar Sidiq; Rusydi Umar; Anton Yudhana
JSI (Jurnal sistem Informasi) Universitas Suryadarma Vol 5, No 2 (2018): JSI (Jurnal sistem Informasi) Universitas Suryadarma
Publisher : Universitas Dirgantara Marsekal Suryadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35968/jsi.v5i2.247

Abstract

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.
Sistem Informasi Kereta Api Berbasis SMS Kartika Firdausy; Anton Yudhana; Lutfatul Kholifah
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2007
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Jumlah penumpang yang memakai transpotasi kereta api dari tahun ke tahun mengalami peningkatanyang cukup besar terutama menjelang dan setelah lebaran. Bertitik tolak dari hal tersebut, peningkatan mutupelayanan dan mutu stasiun perlu ditingkatkan, dan salah satunya adalah dengan melakukan sistem informasijadwal kedatangan/jadwal keberangkatan serta pemesanan tiket kereta api menggunakan komputerisasi. Tujuanpenelitian ini adalah merancang suatu sistem informasi kereta api dan melakukan uji coba terhadap sisteminformasi kereta api tersebut.Permasalahan dalam penelitian ini adalah bagaimana membuat suatu sistem informasi kereta apiberbasis SMS dan bagaimana melakukan uji coba terhadap sistem informasi kereta api tersebut.Subjek penelitian ini adalah sistem informasi kereta api berbasis SMS yang di rancang sebagai suatumedia penyedia informasi yang diwujudkan dalam bentuk SMS.Penelitian ini menghasilkan suatu program sistem informasi kereta api berbasis SMS yang telah di ujicoba dengan dengan baik. Dari hasil uji coba program tersebut dapat dioperasikan dengan baik.Kata kunci: Sistem informasi kereta api, SMS, dan MobileFBUS.
Webcam Untuk Sistem Pemantauan Menggunakan Metode Deteksi Gerakan Kartika Firdausy; Daryono Daryono; Anton Yudhana
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2008
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Recently, numerous daily activities force people to leave their home more often. This situation oftentriggers crimes. Slow handling and lack of anticipation cause the number of crimes increases. Therefore, amonitoring mechanism is needed to improve the security and as an anticipation to unexpected offenses. Thispaper discusses the design of movement detecting system using webcam to monitor the presence of movingobjects with size of human bodyWebcam Logitech QuickCamTM IM is used to capture the object movement at 30 fps. The actual image iscompared to the previous image. The comparison is done for every 5 frames. The software is written in Pascallanguage. A buzzer type alarm is also included in the system. If the camera captures an image of an object withsize greater than or equal to a threshold value, the alarm will be activated and the system records the objectimages. The system is capable in detecting the movement of objects at effective range of 3.5 m.Key words: movement detection, webcam, monitoring
SISTEM KELAS KATA BERIMBUHAN MENGGUNAKAN ALGORITMA PORTER STEMMER SEBAGAI PEMBELAJARAN BAHASA INDONESIA Muhamad Rosidin; Abdul Fadlil; Anton Yudhana
Telematika Vol 16, No 1 (2019): Edisi April 2019
Publisher : Jurusan Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v16i1.2988

Abstract

AbstractClass of word are categories of forms, meanings and functions in the Indonesian grammar system. Determining the basic words of the word affix is still difficult. The word affix class system is a solution to determine the basic words at same time with the class of words that are affixed so that they can be used as learning Indonesian language. The word affix class system was developed using the PHP programming language. Porter algorithms are algorithms that are used to change the word affix into a root word. In this study, the word affix detected by system and separated by infiltration section, then system would process types of affixes juxtaposed with the root words to form a class of words. This can facilitate Indonesian language, basic words and word classes learning. The output is in the form of a table of steps in stemming process and determining affix words class.Keywords: Word Class, Porter, Porter Stemmer, Impression, Stemming AlgorithmAbstrakKelas kata adalah kategori bentuk, makna dan fungsi dalam sistem bahasa indonesia. Penentuan kata dasar dari kata berimbuhan masih sulit dilakukan. Sistem Kelas kata berimbuhan adalah solusi untuk menentukan kata dasar sekaligus dengan kelas kata berimbuhan sehingga dapat digunakan sebagai media pembelajaran bahasa Indonesia. Pengembangan sistem kelas kata berimbuhan berbasis web dan proses codingnya dengan bahasa pemrograman PHP. Porter algorithm merupakan algoritma stemming yang digunakan untuk mengubah kata berimbuhan menjadi kata dasar. Pada penelitian ini, kata berimbuhan dideteksi oleh sistem dan dipisahkan per bagian imbuhannya, kemudian sistem akan memroses jenis imbuhan yang disandingkan dengan kata dasar akan membentuk sebuah kelas kata. Hal ini dapat memudahkan pembelajaran Bahasa Indonesia mengenai kata berimbuhan, kata dasar dan kelas kata. Stemming dan perumusan formula sangat mempengaruhi penentuan kelas kata, karena bahasa indonesia memiliki imbuhan yang kompleks dan memerlukan algoritma stemming yang memiliki kemampuan tinggi dalam menentukan root word. Terdapat sejumlah stemming algorithme yang telah dikembangkan, pada penelitian ini stemming porter algorithme yang dipakai dalam penentuan kata dasar. Output yang dihasilkan berupa table langkah-langkah dalam proses stemming dan penentuan kelas kata berimbuhan.Kata Kunci : Kelas Kata, Algoritma Porter, Porter Stemmer, Imbuhan, Stemming
Rancang Bangun Modulator Digital BPSK Berbasis CPLD MAX7000S Anton Yudhana; Tole Sutikno; Muhammad Aris Fajar Ilmawan
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2007
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Permasalahan dalam merancang hardware modulator digital BPSK sangat rumit ketika dihadapkan padadata input yang mempunyai banyak bit, sehingga perlu dikembangkan modulator digital menggunakan metodelain. Modulator Digital BPSK Berbasis CPLD MAX7000S menjadi salah satu pilihan karena CPLD memuatribuan gerbang logika yang dapat diprogram untuk membentuk suatu logika. Tujuan dari penelitian ini adalahmerancang dan membuat modulator digital BPSK berbasis CPLD.Metode penelitian dilakukan dengan suatu perancangan software dan hardware modulator BPSK. Tahapperancangan rangkaian logika dengan perangkat lunak MAX+Plus II Baseline meliputi: perancanganrangkaian untuk menghasilkan frekuensi pembawa 20 KHz dan frekuensi informasi 5 KHz, perancanganrangkaian memori sinusoida, perancangan multiplexer 8 ke 1 untuk data input, dan perancangan multiplexer 2ke 1 untuk memilih memori sinusoida. Perancangan hardware meliputi: perancangan saklar input, perancanganDAC, dan perancangan BPF. Proses berikutnya menguji setiap bagian dengan mengkompilasi danmensimulasikan rangkaian logika yang digambar pada perangkat lunak. Hasil simulasi output modulator digitalBPSK ditampilkan dengan Microsoft Office Excel.Hasil penelitian menunjukkan bahwa rangkaian modulator digital BPSK yang dirancang telah dapat dicompiledan secara simulasi dengan perangkat lunak MAX+Plus II Baseline telah menunjukkan hasil sesuaiyang diharapkan. Fase output dari modulator digital BPSK berubah jika data yang dikirimkan berbeda logika.Hal ini menunjukkan bahwa hasil perancangan sesuai dengan teori modulasi BPSK.Kata kunci: Modulator digital, BPSK, CPLD.
Compression Analysis Using Coiflets, Haar Wavelet, and SVD Methods Muhamad Aznar Abdillah; Anton Yudhana; Abdul Fadlil
JUITA: Jurnal Informatika JUITA Vol. 9 No. 1, May 2021
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v9i1.8559

Abstract

The image problem lies in the amount of storage space required, to save memory as little as possible image compression is required. The image compression technique is a technique used to represent an image by reducing the quality of the original image but still retaining the information inside. This study compares the best compression method between Coiflets, Haar wavelets, and SVD with JPG image material. The comparison process has done by calculating the compression ratio (CR), Space Saving (SS), Mean Square Error (MSE), Root Mean Square Error (RMSE), and Peak Signal to Noise Ratio (PSNR). The results obtained prove that the SVD method has the highest compression ratio of 3.25 while in the case of Space Saving (SS) the Coiflets method gives the best performance with a value of 73. Measurement in terms of MSE and RMSE is the best for the Coiflets method because it has an average value. -The smallest average among all methods is 0.02395 and 0.111383. provides the best performance in maintaining compression quality. The best PSNR based image quality assessment is the Coiflets method with the highest PSNR average of 63.02 dB. Overall, the Coiflets, Haar wavelet, and SVD compression methods used for JPG images can reduce file size and preserve image information and quality.