Achmad Hidayatno
Departemen Teknik Elektro, Fakultas Teknik, Universitas Diponegoro, Jl. Prof. Sudharto, SH, Kampus UNDIP Tembalang, Semarang 50275, Indonesia

Published : 67 Documents
Articles

DETEKSI SUDUT MENGGUNAKAN KODE RANTAI UNTUK PENGENALAN BANGUN DATAR DUA DIMENSI Hastawan, Ahmad Fashiha; Hidayatno, Achmad; Isnanto, R. Rizal
Transmisi Vol 15, No 1 (2013): TRANSMISI
Publisher : Departemen Teknik Elektro, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1154.048 KB) | DOI: 10.12777/transmisi.15.1.1-7

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Abstrak   Sistem computer vision yang handal diperlukan untuk melakukan sistem pengenalan yang konsisten terhadap beberapa kemungkinan gangguan, terutama untuk pengenalan objek  yang memiliki karakteristik khusus, seperti bangun datar dua dimensi. Dengan Salah satu metode yang diterapkan adalah dengan menggunakan deteksi sudut (corner detection). Terdapat beberapa macam algoritma deteksi sudut, salah satunya adalah dengan menggunakan kode rantai (chain code). Dalam PENELITIAN ini sistem pendeteksian sudut menggunakan kode rantai untuk pengenalan bangun datar dua dimensi ini dibuat dengan menggunakan software Matlab dengan memperhatikan beberapa faktor yang mempengaruhi kehandalan sistem. Perancangan dilakukan dengan membuat sistem pengenalan yang memiliki beberapa tahap diantaranya adalah tahap prapengolahan, tahap ekstraksi ciri, tahap identifikasi ciri,serta tahap pengenalan.  Dari hasil pengujian terhadap sistem, setiap tahap proses dalam sistem pengenalan menghasilkan keluaran sesuai yang diharapkan. Untuk pengujian sistem terhadap data yang diuji, didapatkan persentase pengujian bentuk bangun datar dua dimensi terhadap variasi warna adalah sebesar 100%, pengujian terhadap variasi ukuran adalah sebesar 95,24%, pengujian terhadap variasi posisi adalah sebesar 100%, pengujian terhadap variasi jarak hasil capture kamera webcam sebesar 88,09%, pengujian terhadap keakuratan deteksi sudut bangun tak beraturan sebesar  90%, dan pengujian terhadap variasi warna dan  latar objek sebesar 100%. Kata Kunci : Bangun Datar Dua Dimensi, Deteksi Sudut, Kode Rantai     Abstract   Solid vision computer system is needed to do a consistent recognizing system through some disturbance possibilities, especially for object recognitions which has special characteristic such as two dimensions shape. By this two dimensions shape recognition system, it is approximated can ease robot or shape recognition automatic hardware in doing its job. One of the used method is corner detection. There are some corner detection algorithms. One of them is chain code. This corner detection system using chain code for  two dimensions shape recognition system is built by Matlab software with giving special attention to some factors that influence the system solidity. Designing is done by building recognition system that has some stages, such as pre-processing stage, feature extraction stage, and recognition stage. From the system testing, every stage process gives expected results. Testing of two dimensions shape with color varying gives 100%, testing of size varying gives 95.24%, testing of position varying gives 100%, testing of object distance captured by webcam gives 88.09% ,testing the accurancy of the detection angle irregular shape gives 90%, and testing of object and background color variations gives 100%.   Key Words : Two dimensions shape, corner detection, chain code.
PENYEMBUNYIAN DATA RAHASIA PADA CITRA DIGITAL BERBASIS CHAOS DAN DISCRETE COSINE TRANSFORM Prabowo, Anton; Hidayatno, Achmad; Christyono, Yuli
Transmisi Vol 13, No 2 (2011): TRANSMISI
Publisher : Departemen Teknik Elektro, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (537.527 KB) | DOI: 10.12777/transmisi.13.2.46-52

Abstract

Steganography is one of technique that developed to keep the security of data by hidding or embedding it in other data media so that it?s content or even it?s existence is not notice. Many steganography methode have been developed in the last few years, but it still needed a steganography system with highest capacity and robustness. By combining and modifying few technic, in this Final Project has made a steganography system that used to embedding and extracting secret data in image data form (BMP 8 bit grayscale and 24 bit color), voice data form (WAV PCM 11.025 KHz 8 bit mono), and text data form (TXT) into cover data in image data form (BMP 8 bit grayscale). Data hidding was done at frequency domain by applying DCT (Discrete Cosine Transform) and chaos theory was applied using logistic map equation. Program was made using Borland Delphi 7 programming language. By using subjectif quality, RMS (Root Mean Square) metrics, and similarity ratio measurement parameter, program performance was observed by doing research consist of: research of initialitation parameter change influences; research of embedding and extracting secret digital data in image, voice, and text form into cover digital data in image form; research of program realibility from data manipulation operation including brigthness modification, contrast modification, resizing, cropping, and JPEG compression. Keyword : steganography, discrete cosine transform, chaos theory, logistic map, root mean square.
APLIKASI PENCIRIAN DENGAN LINEAR PREDICTIVE CODING UNTUK PEMBELAJARAN PENGUCAPAN NAMA HEWAN DALAM BAHASA INGGRIS MENGGUNAKAN JARINGAN SARAF TIRUAN PROPAGASI BALIK Rohman, Sigit Nur; Hidayatno, Achmad; Zahra, Ajub Ajulian
Transmisi Vol 14, No 4 (2012): TRANSMISI
Publisher : Departemen Teknik Elektro, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (583.865 KB) | DOI: 10.12777/transmisi.14.4.150-158

Abstract

Abstract In this research designed a recognition system for learning the pronunciation of the word animal names in English. Original speech signal sample at 8000 Hz pick out a small portion For voice parameter extraction process used method Linear Predictive Coding (LPC??) to obtain cepstral coefficients. LPC cepstral coefficients are transformed into the frequency domain with Fast Fourier Transform (FFT). For decision making process of the introduction and use Neural Networks (NN) back propagation. Testing is done using the data train, according to a database of test data and test data do not fit database. While the networks do a variation of 3, 4 and 5 hidden layers respectively for 1, 2 and 3 the number of syllables said. Based on the results of testing training data, the recognition rate for each variation of each network the number of syllables showed no difference in test results, the percentage was 99% for the 1 syllable, 98.5% for the 2 syllables and 100% for 3 syllables. Test data suitable for testing the database, the highest recognition rate for type 1 syllable is a network with 4 hidden layers using a variation of the percentage is 85%, whereas type 2 syllables highest recognition rate using a variation of 5 hidden layers with the correct percentage of 75% and 81.67 % for type 3 syllables using 5 hidden layers. While the test results do not fit the test database, the highest recognition rate for type 1 syllable is a network with 4 hidden layers using a variation of the percentage is 15.83% while the type 2 syllables highest recognition rate using a variation of 3 hidden layers with percentage correct, 20.83% and 33.33% for type 3 syllables using 3 and 4 hidden layers. Keywords : Linear Predictive Coding, Fast Fourier Transform, Neural Network, Backpropagation.
SISTEM PENGENALAN WAJAH MENGGUNAKAN METODE PRINCIPAL COMPONENTS ANALYSIS (PCA) DAN JARINGAN SYARAF TIRUAN Y.S., Frans Bertua; Hidayatno, Achmad; Zahra, Ajub Ajulian
Transmisi Vol 15, No 3 (2013): TRANSMISI
Publisher : Departemen Teknik Elektro, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (241.025 KB) | DOI: 10.12777/transmisi.15.3.128-131

Abstract

Abstrak   Identifikasi seseorang berdasarkan biometrik telah berkembang dengan pesat di kalangan akademik dan industri. Metode pengenalan identitas seseorang yang banyak digunakan di antaranya berdasarkan nomor identitas unik (kunci fisik, kartu identitas dan lainnya) atau berdasarkan ingatan terhadap sesuatu (sandi rahasia dan lainnya). Metode tersebut banyak memiliki kekurangan di antaranya adalah kartu identitas dapat hilang dan sandi dapat lupa dari ingatan seseorang. Ada dua jenis biometrik di antaranya adalah physiological (iris mata, wajah dan sidik jari) dan behavioural (suara dan tulisan tangan). Dalam tugas akhir ini dibuat program pengenalan citra wajah dengan menggunakan metode principal components analysis (PCA) dan jaringan saraf tiruan. Dengan tujuan mendapatkan hasil pengenalan yang cukup baik untuk mengenali citra wajah, dan memberikan saran untuk pengembangan sistem pengenalan wajah agar semakin baik lagi. Berdasarkan hasil pengujian keseluruhan data dengan variasi hidden layer = 1,2 maupun 3 memiliki rata-rata tingkat pengenalan 82,40%. dengan pengenalan tertinggi sebesar 86,6% pada variasi jumlah hidden layer = 1, dan terendah sebesar 79,3% pada variasi jumlah hidden layer = 2. Dan berdasarkan hasil pengujian keseluruhan data dengan variasi jumlah komponen utama = 100, 50, 25 maupun 10 memiliki rata-rata tingkat pengenalan 76,9% dengan pengenalan tertinggi sebesar 86,6% pada variasi jumlah komponen utama = 100, dan terendah sebesar 66% pada variasi jumlah komponen utama = 10.   Kata kunci : Pengenalan Wajah, Principal Components Analysis (PCA), Jaringan saraf tiruan     Abstract   Based on biometric identification of a person has been growing very rapidly among academic and industry. A method of the introduction of the identity of someone much used based on identification number of the unique ( the key psychics, identity card and other ) or in terms of memories to something ( a secret password and other ). This method many having a deficiency of them are identity card can be lost and the password can forget of memory someone. There are two kinds of biometric among which are the physiological (, the iris of the eye the face and fingerprints ) and behavioural ( voice and handwriting ). In this final task made program with a face image recognition method using principal components analysis (PCA) and artificial neural networks. With the aim of getting results good enough recognition to recognize facial image, and provide suggestions for the development of face recognition systems in order for the better again. Based on the test results the overall record with a variation of the hidden layer = 1,2 and 3 have an average level of recognition 82,40%. the highest result  86,6% in the number variation of hidden layer = 1, and the lowest of 79.3% in the number of hidden layer variation = 2. And based on the test results the overall record with a variation of principal components = 100, 50, 25 and 10 have an average level of 76,9% recognition with the highest recognition of 86,6% in the number of principal components of variation = 100, and the lowest of 66% in the number of principal components of variation = 10.   Key word : Face recognition, Principal Components Analysis (PCA), artificial neural network
PENGENALAN CITRA IRIS MATA MENGGUNAKAN ALIHRAGAM WAVELET DAUBECHIES ORDE 4 Hartanto, Antonius Dwi; Isnanto, R. Rizal; Hidayatno, Achmad
Transmisi Vol 12, No 4 (2010): TRANSMISI
Publisher : Departemen Teknik Elektro, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (328.001 KB) | DOI: 10.12777/transmisi.12.4.145-149

Abstract

Iris is a part of the circle around the eye pupil. Iris has a very unique pattern, different in each individual. On this basis the iris can be used as the basis for the introduction of biometrics. To identify the texture of the iris in an eye image, method of texture analysis can be used. There are several methods of texture analysis, one of which is to use a wavelet based on image feature extraction energy. The analysis uses the energy characteristics contained in wavelet transform. Based on that reason, in this research an application program to identify the iris of the eye based on Daubechies order 4 wavelet transform.  Eye image used in this research was acquired and processed, beginning take on the characteristics and texture of the iris image which converted into polar form. Then the feature extraction is done using Daubechies wavelet transform order 4. The characteristics obtained is in the form of the energy value. The next stage is the recognition  using nearest normalized Euclidean distance. Tests carried out in the research consist of four types: influence of sample database, influence of the decomposition level of Daubechies wavelet transform order 4, influence of different input image formats, and testing on eye images which are not in database. From the test results, it can be concluded that the highest recognition rate with the parameters shown in testing Daubechies wavelet transform order 4 level 4 with two samples iris image stored is 86.66%. The lowest recognition rate is shown in tests with Daubechies wavelet transform order 4 level 6 with one sample iris image stored is 62.5%. Then from the results of testing the influence of different input image formats, it can be concluded that the samples taken from 40 individuals which one sample is take for each person, use the format BMP as  well as with use JPEG format. Whereas, from the test result for eye images which are not in database with threshold 0.3559, of the recognition level is 96%. Keyword :   texture analysis, Daubechies wavelet transform order 4, iris, Euclidean distance
APLIKASI PENGENALAN UCAPAN DENGAN EKSTRAKSI MEL-FREQUENCY CEPSTRUM COEFFICIENTS (MFCC) MELALUI JARINGAN SYARAF TIRUAN (JST) LEARNING VECTOR QUANTIZATION (LVQ) UNTUK MENGOPERASIKAN KURSOR KOMPUTER Setiawan, Angga; Hidayatno, Achmad; Isnanto, R. Rizal
Transmisi Vol 13, No 3 (2011): TRANSMISI
Publisher : Departemen Teknik Elektro, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (348.436 KB) | DOI: 10.12777/transmisi.13.3.82-86

Abstract

During this time, computer cursor operation was done by pressing and moving the mouse. So, this is less flexible for computer user that require movement in operating a computer, since to use mouse comfortably someone has to sit. Moreover, physical completeness is required for mouse operating, so that for someone who has physical disabilities feels difficult to operate it. Therefore, it is required to develop a system that provides a better comfort and flexibility not only for the healthy user computer but also for the user computer who has physical disabilities. In this final project, computer cursor operation program via voice is created. With this program, someone will have more flexibility when operating the computer cursor and also people with physical disabilities is enabled to communicate with computer. Voice recognition is a technology that is apllied in this program, with the feature extraction process used MFCC (Mel-Frequency Cepstrum Coefficients) method. As for the recognitions process used artificial neural network type LVQ (Learning Vector Quantization). Voice is passed through a microphone and then it is analyzed by MFCC to produce MFCC coefficients. These coefficients are used as input vector for LVQ neural network and used as data to train the network until it has the classification capability. Programming language that is used in creating this software is Delphi programming language. Based on the result of the testing program, it is found that the success percentage rate of voice recognition with training data, that is data which is derived from databases that have been recorded and trained into the program which amounts to 240 data, is 88,89 %. While in the testing with test data, that is data which is derived from the real time sayings of respondents which is amounts to 240 data, it is found that the success percentage rate of voice recognition is 83,99 %. Keyword : voice recognition, computer cursor, MFCC, LVQ
PERANCANGAN SISTEM PEMANTAUAN POSISI PEJALAN KAKI MENGGUNAKAN FUSI DATA MEMS SENSOR DAN GPS Luthfa, Muhammad Fairuz; Hidayatno, Achmad; Setiawan, Iwan
Transmisi Vol 16, No 2 (2014): TRANSMISI
Publisher : Departemen Teknik Elektro, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (654.894 KB) | DOI: 10.12777/transmisi.16.2.79-85

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Abstrak Pada sejumlah bidang aplikasi seperti militer, keamanan dan layanan darurat, informasi posisi pejalan kaki dapat memiliki arti  sangat penting dan strategis. Sampai sekarang kebutuhan akan informasi posisi disediakan oleh GPS yang memiliki kelemahan akurasi. Pada tahun 2000 mulai dikembangkan sistem pemantauan posisi pejalan kaki menggunakan MEMS sensor yang memiliki kelemahan adanya drift. Pada penelitian ini dirancang suatu sistem pemantauan posisi untuk pejalan kaki dengan menggabungkan data posisi dari MEMS Sensor dan GPS menggunakan algoritma complementary filter.  Penggunaan complementary filter bertujuan untuk menggabungkan data dari kedua sensor sehingga didapatkan hasil informasi posisi pejalan kaki dengan tingkat akurasi yang lebih tinggi dibandingkan hanya dengan menggunakan salah satu metode saja. Perancangan simulasi dari complementary filter menggunakan Simulink Matlab 2012. Perancangan perangkat keras dibagi menjadi 3 subsistem, yaitu slave, master dan ground station. Sensor accelerometer ADXL345, magnetometer CMPS10 dan GPS EM411 digunakan untuk mendapatkan data-data yang dibutuhkan dalam proses estimasi posisi pejalan kaki. Pengiriman data posisi dari handheld ke ground station menggunakan modul RF Parallax 433 MHz. Hasil dari pengujian sistem dengan fusi data menunjukkan adanya peningkatan akurasi informasi posisi dibandingkan dengan hanya mengandalkan salah satu dari MEMS sensor atau GPS. Kata kunci: Posisi Pejalan Kaki, MEMS Sensor,GPS,Complementary Filter.     Abstract Information position of a pedestrian is very important for military, security and emergency services application.  For now, information position has been provided by GPS that has weakness its accuracy. In 2000, development of pedestrian positioning system using MEMS sensor has been developed and it gets drift as its weakness. In this research  a method for pedestrian positioning system that fuse the data of MEMS sensor and GPS by using complementary filter is proposed. The use of complementary filter aims to combine the data from both sensors to obtain the results of pedestrian position information with accuracy higher than using only one method alone. The design of a complementary filter simulation using Matlab Simulink 2012. Hardware design is divided into three subsystems, namely the slave, the master and the ground station. ADXL345 accelerometer sensor, magnetometer CMPS10 and GPS EM411 used to obtain the data required in the process of estimation pedestrian position. Delivery of position data from the handheld to the ground station using Parallax 433 MHz RF modules. The results of testing the system with data fusion showed an increase in accuracy of positioning information as opposed to just relying on one of the MEMS sensors or GPS. Keywords: Pedestrian Positioning, MEMS sensor, GPS, Complementary Filter.
PERANCANGAN SISTEM PERBAIKAN NADA SUARA MANUSIA DENGAN MENGGUNAKAN METODE PHASE VOCODER TERHADAP NADA REFERENSI MUSIK Prasetio, Rudi; Hidayatno, Achmad; Santoso, Imam
Transmisi Vol 16, No 4 (2014): TRANSMISI
Publisher : Departemen Teknik Elektro, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (539.533 KB) | DOI: 10.12777/transmisi.16.4.160-166

Abstract

Abstrak   Audio merupakan sinyal suara yang dapat dideteksi manusia dengan frekuensi terendah 20 Hz dan tertinggi 20 kHz.Suara beraturan dengan frekuensi tungal tertentu disebut sebagai nada dan sering dikomposisikan dengan beberapa nada lain sehingga terdengar apik. Seorang penyanyi dalam melakukan pengambilan suara terkadang mengalami ketidak tepatan nada. Berdasarkan hal tersebut, maka dirancang sebuah sistem perbaikan nada suara manusia terhadap nada referensi musik dengan menggunakan metode phase vocoder. Perancangan ini terbagi menjadi 2 tahapan utama yaitu pitch detection dan pitch correction. Metode yang digunakan pada deteksi nada adalah FFT dengan ukuran variasi frame sebesar 256, 512, dan 1024 buah sampel serta jarak overlapping antara frame sebesar 25%, 50%, dan 75%. Hasil frekuensi suara yang diperoleh kemudian dibandingkan dengan frekuensi referensi musik.Apabila terdapat perbedaan maka dilakukan proses pitch correction dengan menggunakan metode phase vocoder dengan variasi overlapping sebesar 25%, 50%, dan 75%. Hasil yang diperoleh dari sistem menunjukkan bahwa parameter terbaik dalam mendeteksi nada menggunakan ukuran frame 512 dan 1024 buah sampel, serta nilai overlapping sebesar 50% dan 75%. Sedangkan parameter overlapping terbaik yang dapat digunakan untuk mengkoreksi nada sebesar 50% dan 75%. Sistem ini kemudian diujikan dengan menggunakan data suara dan memperoleh tingkat keberhasilan sebesar 96,2538%.   Kata kunci: Pitch Detection, Pitch Correction     Abstract Audio is a sound that can be detected by human ears with the lowest frequency is 20 Hz and the highest frequency is 20 kHz. It is produced by the vibration of the object. Sound or the uniform sound with the only one special frequency is called by a tone and always be combined by the others to heard more beautiful. As we known, a singer sometimes wrong to takes a pitch from a tone. Therefore, this research designed a tone rectifying system of human voice to the music reference using phase vocoder method. This design will be divided into 2 steps, pitch detection and pitch correction. Fast Fourier Tranform (FFT) is used in pitch detection process with 256, 512, and 1024 variation of size frame and 25%, 50%, 75% variation of overlapping between two frames. The frequency result from pitch detection then compared by the frequency of music reference. If there is a difference between it so the process of pitch correction will be done to the system using phase vocoder method with 25%, 50%, and 75% variation of overlapping. Analytical results from the system show that the best parameters can be used in pitch detection is 512 or 1024 frame size and 50% or 75% overlapping. While the best parameters can be used in pitch correction is 50% or 75% overlapping. This system then tested by voice data and get 96,2538% success rate. Keywords: Pitch Detection, Pitch Correction
PEWUJUDAN TAPIS DIGITAL FIR PEMILIH FREKUENSI MENGGUNAKAN DSK TMS320C6713 Erwin, Gidion; Hidayatno, Achmad; Darjat, Darjat
Transmisi Vol 12, No 1 (2010): TRANSMISI
Publisher : Departemen Teknik Elektro, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (496.81 KB) | DOI: 10.12777/transmisi.12.1.1-7

Abstract

Digital frequency selector filter is the simplest application of digital signal processing, in which process only passing signal with specific desired frequency or band frequency. Digital frequency selector filter can be implemented as software or hardware. In this final project, frequency selector filter is implemented as hardware using DSK (Digital Signal Processor Starter Kit)  TMS320C6713. In this final project, designed three type of  frequency selector filter : Low Pass Filter (LPF), High Pass Filter (HPF), and Band Pass Filter (BPF) with filter length (N) and cut-off frequency (Fc) variation. Filter coefficient is the final product of design stage. FDATool Matlab is used to help filter design and filter coefficient calculation. Then, this filter coefficient is implemented as digital filter in DSK TMS320C6713 using CCS (Code Composer Studio) v.3.1. In CCS, it is also arranged some source code to initialize internal peripheral device on DSK TMS320C6713 (Codec, McBSP, etc), initialize interrupt mode, and initialize memory mapping. Based on experiment?s result, it?s known that the implemented?s magnitude response  approriate with FDATool?s magnitude response (frequency selector filter algorithm was successfully implemented in DSK TMS320C6713). However, gain?s value at pass band region is not exactly 0 dB because resistance losses from cables and the low precision of measurement device. Based on experiment?s result, it?s also known that filter with higher filter length produces better magnitude response characteristics, especially narrower transition width characteristic. Keyword :   digital signal processing, digital filter, frequency selector filter, DSK TMS320C6713.
APLIKASI METODE TEMPLATE MATCHING UNTUK KLASIFIKASI SIDIK JARI Leksono, Bowo; Hidayatno, Achmad; Isnanto, R. Rizal
Transmisi Vol 13, No 1 (2011): TRANSMISI
Publisher : Departemen Teknik Elektro, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (326.037 KB) | DOI: 10.12777/transmisi.13.1.1-6

Abstract

The development of image processing technologies now provide the possibility of human to create a system that can recognize a digital image. One method to recognize a digital image is the template matching. This method serves to find small parts of the image that matches the template image. Among the technologies to solve the problem of image processing is a system of classifying fingerprints into the form of software that is able to process the fingerprint image enhancement and match fingerprint images that have been recorded by the database system and classify fingerprints into a particular class. In this final project made ??an application that aims to classify the fingerprint image into a particular class using template matching method.Classification process is started with fingerprint image acquisition, images size distorting 256x256, grayscale(gray level), histeq (histogram equalization), binary (image distorting becomes two scales black and white), thinning, image gets to aim, and resize 32x32. The process will then be calculated percentage of similarity with the template fingerprint image file by using the calculation of NC (Normalized Cross Correlation). The biggest percentage value indicates that the template matches the fingerprint image files. The experiment has been done classification process as much as 61 input fingerprint image with each 5 image formats are *.bmp, *.gif, *.jpg, *.png, and *.tif, so the total input fingerprint image as much as 305. For image format type *.bmp, *. gif, *. png, and *.tif on type template Plain Arch, Plain Whorl, and Double Loop point out that its success zoom as big as 100%. On Tented Arch increase supreme success on image format *.bmp, *. jpg, *. png, *. tif, on Ulnair Loop increase supreme success on image format *.png, *. tif and Radial Loop increase supreme success on image format *.bmp, *. png, *. tif. Image format that right usually experience fault which is on success zoom is contemned to image format *.jpg to type template Plain Arch, Radial Loop, Plain Whorl and Double Loop, then for image format *.gif on type template Tented Arch and Ulnair Loop. Keyword : image processing, fingerprint, template matching
Co-Authors Achmad Chusnul Khuluqi Achmad Widodo Aditya Satya Raya Afiq, Raihan Aghus Sofwan Agung Wicaksono Ahmad Fashiha Hastawan Ajub Ajulian Z. Ajub Ajulian Zahra Anang Setiaji, Anang Andi Pangerang, Andi Andrio Ghara Pratama Angga Setiawan Anton Prabowo Antonio Christian Simanjuntak, Antonio Christian Antonius Dwi Hartanto Arie Firmansyah Permana Arif Munandar Aris Triwiyanto Aris Triwiyatno Arlies Bayu S Azizah, Mega Tiara Nur Bagus Aditya Benny Raharjo, Benny Bondhan Tunjung Bowo Leksono Buana, Dian Kurnia Widya Chairunnisa Adhisti Prasetiorini Dani Wijayanto Darjat Darjat David Sebastyan Simangunsong Dhody Kurniawan Dictosendo Noor Pambudi Rahayu Dita Marta Dewi Onasiska Donny Zaviar Rizky Dudi Hariyanto Dwi Anasthasia Pasaribu Eskanesiari Eskanesiari Faizal Haris M Frans Bertua Y.S. Gidion Erwin Gilang Ananggadipa Hariyanto, Monica Sari Hartadhianty, Vivere Hendra William Imam Gaffar Imam Santoso Iwan Setiawan Kurniawan, Yuniar Dwi Aman Listyono, A. F. M. Antisto Akbar M. Ikhsan Mulyadi Maman Somantri Maulana, Kresna Lita Muhammad Ardi Nur Syamsu, Muhammad Ardi Nur Muhammad Arfan Muhammad Aswan Muhammad Fairuz Luthfa Muhammad Widyanto Tri Saksono Mujib, Khusnil Munawar Agus Riyadi Mutiara Shabrina Nanang Trisnadik Nur Rizky Rosna Putra Parlys, Albert Pratama, Muhammad Harry Bintang Prayogi, A. S. Putra, Nanda Ariawan R. Rizal Isnanto Rachmad Arief Setiawan Ramadhani, Natalia Putri Rio Lenardo Karo Karo, Rio Lenardo Rudi Prasetio Sigit Nur Rohman Susilo Adi Widyanto Suwoko Suwoko Taufik Agung Wibowo Taufiqurrohman Taufiqurrohman Teddy Ekatamto, Teddy Teguh Prakoso Wahyudi Wahyudi Wahyul Amien Syafei Yudhi Prabowo Yuli Christiyono Yuli Christyono Yuli Chrityono, Yuli Zaini Agung Utama