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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Dinamik Jurnal Ilmu Komputer dan Informasi Jurnal Masyarakat Informatika Jurnal Sains dan Teknologi Semantik Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Prosiding SNATIF Journal of ICT Research and Applications Teknika: Jurnal Sains dan Teknologi Scientific Journal of Informatics JAIS (Journal of Applied Intelligent System) Proceeding SENDI_U Jurnal Ilmiah Dinamika Rekayasa (DINAREK) Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Teknologi dan Sistem Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Eksplora Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Manajemen Informatika Jurnal Kridatama Sains dan Teknologi Infotekmesin Jurnal Mnemonic Abdimasku : Jurnal Pengabdian Masyarakat Variabel Journal of Intelligent Computing and Health Informatics (JICHI) SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Teknik Informatika (JUTIF) JUDIMAS (Jurnal Inovasi Pengabdian Kepada Masyarakat) Jurnal Program Kemitraan dan Pengabdian Kepada Masyarakat Journal of Soft Computing Exploration Advance Sustainable Science, Engineering and Technology (ASSET) Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Prosiding Seminar Nasional Hasil-hasil Penelitian dan Pengabdian Pada Masyarakat Jurnal Informatika Polinema (JIP) Jurnal Informatika: Jurnal Pengembangan IT Scientific Journal of Informatics LogicLink: Journal of Artificial Intelligence and Multimedia in Informatics Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) Advance Sustainable Science, Engineering and Technology (ASSET)
Eko Hari Rachmawanto
Universitas Dian Nuswantoro
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

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Journal : Scientific Journal of Informatics

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A High Performace of Local Binary Pattern on Classify Javanese Character Classification Susanto, Ajib; Sinaga, Daurat; Sari, Christy Atika; Rachmawanto, Eko Hari; Setiadi, De Rosal Ignatius Moses
Scientific Journal of Informatics Vol 5, No 1 (2018): May 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i1.14017

Abstract

The classification of Javanese character images is done with the aim of recognizing each character. The selected classification algorithm is K-Nearest Neighbor (KNN) at K = 1, 3, 5, 7, and 9. To improve KNN performance in Javanese character written by the author, and to prove that feature extraction is needed in the process image classification of Javanese character. In this study selected Local Binary Patter (LBP) as a feature extraction because there are research objects with a certain level of slope. The LBP parameters are used between [16 16], [32 32], [64 64], [128 128], and [256 256]. Experiments were performed on 80 training drawings and 40 test images. KNN values after combination with LBP characteristic extraction were 82.5% at K = 3 and LBP parameters [64 64].
Cryptography Triple Data Encryption Standard (3DES) for Digital Image Security Atika Sari, Christy; Rachmawanto, Eko Hari; Haryanto, Christanto Antonius
Scientific Journal of Informatics Vol 5, No 2 (2018): November 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i2.14844

Abstract

Advances in technology in the field of internet, making the Internet become the most popular data transmission media for now. This is certainly not free from the incidence of cyber crime, such as theft and data modification. Given the losses caused by data manipulation is very detrimental to the owner, then the original data can be misused in the cyber world. Cryptography offers an algorithm for randomizing data, so it can not be read by unauthorized people. The cryptography technique was implemented using Triple Data Encyption Standard (3DES) given the results of a randomized cryptographic algorithm, it is possible to arouse suspicion from the viewer. For that will be done the process of insertion of cryptographic files into another media in the form of images commonly referred to as steganography. The steganography technique that will be used is End of File (EOF). The combination of 3DES and EOF in the 64x64 pixel image with grayscale color format produces the fastest image processing time of 173.00192 seconds with the highest Peak Signal to Noise Ratio (PSNR) value of 25.0004 dB, while in the 128x128 pixel image with grayscale format has produced the highest PSNR 21.0084 dB.
DWT-SVD Combination Method for Copyrights Protection Kusumaningrum, Desi Purwanti; Rachmawanto, Eko Hari; Atika Sari, Christy; Pradana, Rizky Putra
Scientific Journal of Informatics Vol 7, No 1 (2020): May 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i1.21050

Abstract

Many irresponsible people who download other people's artwork then modify and redistribute the work of someone without permission by not including the owner's name. Based on that problem an attempt was made to provide an invisible watermark so as not to be easy to do the watermark removal process on the artwork, using a 2-level DWT and SVD combination method that can embed watermarks invisibly and increase watermarking resistance to the image from various image manipulation processes such as noise, JPEG compression, and so on. From combination method of DWT-SVD got the highest PSNR value with watermark image size 32x32 and 64x64 which is 59.2656 dB and 54.7414 dB, respectively.
Fake Twitter Account Classification of Fake News Spreading Using Naïve Bayes Santoso, Heru Agus; Rachmawanto, Eko Hari; Hidayati, Ulfa
Scientific Journal of Informatics Vol 7, No 2 (2020): November 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i2.25747

Abstract

Twitter is a very popular microblog, where users can search for various information, current news, celebrity posts, and hot topics. Indonesia is ranked 5th for the most Twitter users. The large number of users makes Twitter used for the benefit of certain parties with bad goals, such as spreading fake news using fake accounts. Fake accounts are often used by several parties to spread fake news, therefore the spread of fake news must be immediately limited to minimize the negative impact caused by fake news. For this reason, this research is written with the aim of being able to classify fake and genuine Twitter accounts. In this study, using data mining techniques that are closely related to big data in decision making by applying the Naive Bayes method. Naïve Bayes is one of the most widely used classification methods because it has good accuracy and faster computation time. The classification process uses nine parameters, namely based on the Profile Created, Favorite Count, Follower Count, Following Count, Geo Enabled, Follower Rate, Following Rate, Follower Following Ratio, Verified. This study uses 210 datasets of twitter accounts that spread fake news, the result is that Naïve Bayes works very promising  in the classification of fake twitter accounts and in the testing process using 5% of training set produces an accuracy of 80%.
DWT-SVD Combination Method for Copyrights Protection Kusumaningrum, Desi Purwanti; Rachmawanto, Eko Hari; Atika Sari, Christy; Pradana, Rizky Putra
Scientific Journal of Informatics Vol 7, No 1 (2020): May 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i1.21050

Abstract

Many irresponsible people who download other people's artwork then modify and redistribute the work of someone without permission by not including the owner's name. Based on that problem an attempt was made to provide an invisible watermark so as not to be easy to do the watermark removal process on the artwork, using a 2-level DWT and SVD combination method that can embed watermarks invisibly and increase watermarking resistance to the image from various image manipulation processes such as noise, JPEG compression, and so on. From combination method of DWT-SVD got the highest PSNR value with watermark image size 32x32 and 64x64 which is 59.2656 dB and 54.7414 dB, respectively.
Fake Twitter Account Classification of Fake News Spreading Using Naïve Bayes Santoso, Heru Agus; Rachmawanto, Eko Hari; Hidayati, Ulfa
Scientific Journal of Informatics Vol 7, No 2 (2020): November 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i2.25747

Abstract

Twitter is a very popular microblog, where users can search for various information, current news, celebrity posts, and hot topics. Indonesia is ranked 5th for the most Twitter users. The large number of users makes Twitter used for the benefit of certain parties with bad goals, such as spreading fake news using fake accounts. Fake accounts are often used by several parties to spread fake news, therefore the spread of fake news must be immediately limited to minimize the negative impact caused by fake news. For this reason, this research is written with the aim of being able to classify fake and genuine Twitter accounts. In this study, using data mining techniques that are closely related to big data in decision making by applying the Naive Bayes method. Naïve Bayes is one of the most widely used classification methods because it has good accuracy and faster computation time. The classification process uses nine parameters, namely based on the Profile Created, Favorite Count, Follower Count, Following Count, Geo Enabled, Follower Rate, Following Rate, Follower Following Ratio, Verified. This study uses 210 datasets of twitter accounts that spread fake news, the result is that Naïve Bayes works very promising  in the classification of fake twitter accounts and in the testing process using 5% of training set produces an accuracy of 80%.
Cryptography Triple Data Encryption Standard (3DES) for Digital Image Security Atika Sari, Christy; Rachmawanto, Eko Hari; Haryanto, Christanto Antonius
Scientific Journal of Informatics Vol 5, No 2 (2018): November 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i2.14844

Abstract

Advances in technology in the field of internet, making the Internet become the most popular data transmission media for now. This is certainly not free from the incidence of cyber crime, such as theft and data modification. Given the losses caused by data manipulation is very detrimental to the owner, then the original data can be misused in the cyber world. Cryptography offers an algorithm for randomizing data, so it can not be read by unauthorized people. The cryptography technique was implemented using Triple Data Encyption Standard (3DES) given the results of a randomized cryptographic algorithm, it is possible to arouse suspicion from the viewer. For that will be done the process of insertion of cryptographic files into another media in the form of images commonly referred to as steganography. The steganography technique that will be used is End of File (EOF). The combination of 3DES and EOF in the 64x64 pixel image with grayscale color format produces the fastest image processing time of 173.00192 seconds with the highest Peak Signal to Noise Ratio (PSNR) value of 25.0004 dB, while in the 128x128 pixel image with grayscale format has produced the highest PSNR 21.0084 dB.
A High Performace of Local Binary Pattern on Classify Javanese Character Classification Susanto, Ajib; Sinaga, Daurat; Sari, Christy Atika; Rachmawanto, Eko Hari; Setiadi, De Rosal Ignatius Moses
Scientific Journal of Informatics Vol 5, No 1 (2018): May 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i1.14017

Abstract

The classification of Javanese character images is done with the aim of recognizing each character. The selected classification algorithm is K-Nearest Neighbor (KNN) at K = 1, 3, 5, 7, and 9. To improve KNN performance in Javanese character written by the author, and to prove that feature extraction is needed in the process image classification of Javanese character. In this study selected Local Binary Patter (LBP) as a feature extraction because there are research objects with a certain level of slope. The LBP parameters are used between [16 16], [32 32], [64 64], [128 128], and [256 256]. Experiments were performed on 80 training drawings and 40 test images. KNN values after combination with LBP characteristic extraction were 82.5% at K = 3 and LBP parameters [64 64].
Capital Optical Character Recognition Using Neural Network Based on Gaussian Filter Erna Zuni Astuti; Christy Atika Sari; Mutiara Syabilla; Hendra Sutrisno; Eko Hari Rachmawanto; Mohamed Doheir
Scientific Journal of Informatics Vol 10, No 3 (2023): August 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i3.43438

Abstract

Purpose: As digital technology advances, society needs to convert physical text into digital text. There are now many methods available for doing this. One of them is OCR (Optical Character Recognition), which can scan images [1]–[4] containing writing and turn them into digital text, making it easier to copy written text from an image. Text recognition in images is complex due to variations in text size, color, font, orientation, background, and lighting conditions.Methods: The technique of text recognition or optical character recognition (OCR) in images can be done using several methods, one of which is a neural network or artificial neural network. The artificial neural network method can help a computer make intelligent decisions with limited human assistance. Intelligent decisions can be made because the neural network can learn and model the relationship between nonlinear and complex input and output data. In this research, the scaled conjugated gradient is applied for optimization. SCG is very effective in finding the minimum value of a complex function, but it takes longer than some other optimization algorithms.Result/Findings: The dataset used is an image with a size of 28 x 28 which is changed in dimension to 784 x 1. This research uses 4000 epochs and obtained the best validation result at epoch 3506 with a value of 0.0087446. Results: From the statistical test results, the effect of perceived usefulness on ease of use has the highest level of influence, obtaining a test value of 3.6. Furthermore, the effect of the attitude towards using on the behavioral intention to use has the lowest level of influence, which obtained a test value of 1.2.Novelty:  In this article, Gaussian filter is used as feature extraction to improve yield. Character detection results using a Gaussian filter are known to be almost 10% higher than those using only a neural network. The result with the Neural Network alone is 82.2%, while the Neural Network-Gaussian Filter produces 92.1%.
Comparative Study of Machine Learning Algorithms for Performing Ham or Spam Classification in SMS Erna Zuni Astuti; Christy Atika Sari; Eko Hari Rachmawanto; Rabei Raad Ali
Scientific Journal of Informatics Vol 11, No 1 (2024): February 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i1.47364

Abstract

Purpose: Fraud is rampant in the current era, especially in the era of technology where there is now easy access to a lot of information. Therefore, everyone needs to be able to sort out whether the information received is the right information or information that is fraudulent. In this research, the process of classifying messages including ham or spam has been carried out. The purpose of this research is to be able to build a model that can help classify messages. The purpose of this research is also to determine which machine learning method can accurately and efficiently perform the ham or spam classification process on messages.Methods: In this research, the ham or spam classification process has been using machine learning methods. The machine learning methods used are the classification process with Random Forest, Logistic Regression, Support Vector Classification, Gradient Boosting, and XGBoost Classifier algorithms. Results: The results obtained after testing in this study are the classification process using the Random Forest algorithm getting an accuracy of 97.28%, Logistic Regression getting an accuracy of 94.67%, with Support Vector Classification getting an accuracy of 97.93%, and using XGBoost Classifier getting an accuracy of 96.47%. The best precision value obtained in this study is 98% when using the random forest algorithm. The best recall value is 94% when using the SVC algorithm. While the best f1-score value is 95% when using the SVC algorithm.Novelty: This research has been compared with several algorithms. In previous research, it is still very rarely done using XGBoost to classify the ham or spam in messages. We focus on giving brief information based con comparison algorithm and show the best algorithm to classify classify the ham or spam in messages. And for the novelty that exists from this research, the machine learning model built gets better accuracy when compared to previous research.
Co-Authors Abdussalam Abdussalam Abdussalam Abdussalam, Abdussalam Abu Salam Adhitya Nugraha Adiyah Mahiruna Agustina, Feri Ahmad Salafuddin Ajib Susanto Akbar Aji Nugroho Akbar, Ilham Januar Al-Ghiffary, Maulana Malik Ibrahim Ali, Rabei Raad Alifia Salwa Salsabila Alvin Faiz Kurniawan Anak Agung Gede Sugianthara Andi Danang Krismawan Annisa Sulistyaningsih Antonio Ciputra Antonius Erick Handoyo Ardika Alaudin Arsa Arfian, Aldi Azmi Aryanta, Muhammad Syifa Aryaputra, Firman Naufal Astuti, Yani Parti Asyari, Fajar Husain Aulia, Lathifatul Auni, Amelia Gizzela Sheehan Bijanto Bijanto Briliantino Abhista Prabandanu Cahaya Jatmoko Cahyo, Nur Ryan Dwi Candra Irawan Candra Irawan Chaerul Umam Chaerul Umam Christy Atika Sari Cinantya Paramita Ciputra, Antonio D.R.I.M. Setiadi Danar Bayu Adi Saputra Danu Hartanto Daurat Sinaga De Rosal Ignatius Moses Setiadi Desi Purwanti Kusumaningrum Desi Purwanti Kusumaningrum Desi Purwanti Kusumaningrum Destriana, Rachmat Didik Hermanto Dila Ananda Oktafiani Dimas Irawan Ihya‘ Ulumuddin Doheir, Mohamed Doheir, Mohamed Dwi Puji Prabowo Dwi Puji Prabowo, Dwi Puji Egia Rosi Subhiyakto Egia Rosi Subhiyakto Elkaf Rahmawan Pramudya Ellen Proborini Eqania Oktayaessofa Erna Daniati Erna Zuni Astuti Erna Zuni Astuti Erna Zuni Astuti Ery Mintorini Faisal, Edi Farrel Athaillah Putra Fazlur Rahman Hafidz Fida Maisa Hana Fidela Azzahra Florentina Esti Nilawati Florentina Esti Nilawati Florentina Esti Nilawati Folasade Olubusola Isinkaye Giovani Ardiansyah Gumelar, Rizky Syah Guruh Fajar Shidik Hadi, Heru Pramono Haryanto, Christanto Antonius Haryanto, Christanto Antonius Hasbi, Hanif Maulana Hendra Sutrisno Herman Yuliansyah, Herman Heru Agus Santoso Heru Lestiawan Hidayat, Muhammad Taufiq Hidayati, Ulfa Himawan, Mahadika Pradipta Himawan, Reyshano Adhyarta Hyperastuty, Agoes Santika Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Imam Prayogo Pujiono Inzaghi, Reza Bayu Ahmad Isinkaye, Folasade Olubusola Islam, Hussain Md Mehedul Istiawan, Deden Istiqomah, Annisa Ayu Ivan Stepheng Kas Raygaputra Ilaga Krismawan, Andi Danang Kumala, Raffa Adhi Kunio Kondo Kurniawan, The, Obed Danny Kusuma, Edi Jaya L. Budi Handoko Laksana, Deddy Award Widya Lalang Erawan Latifa, Anidya Nur Liya Umaroh Liya Umaroh, Liya Lucky Arif Rahman Hakim Lungido, Joshua Mabina, Ibnu Farid Mahiruna, Adiyah Maulana Malik Ibrahim Al-Ghiffary Md Kamruzzaman Sarker Md Kamruzzaman Sarker Mohamed Doheir Mohamed Doheir Mohammad Rizal, Mohammad Mohd Yaacob, Noorayisahbe Muchamad Akbar Nurul Adzan Muhammad Mahdi Mulyono, Ibnu Utomo Wahyu Munis Zulhusni Musfiqur Rahman Sazal Muslih Muslih Muslih Muslih Mutiara Dolla Meitantya Mutiara Syabilla Nabila, Qotrunnada Nanna Suryana Herman NGATIMIN, NGATIMIN Ningrum, Amanda Prawita Nisa, Yuha Aulia Noor Ageng Setiyanto Noor Ageng Setiyanto, Noor Ageng Noorayisahbe Mohd Yaacob Noorayisahbe Mohd Yaacob Noorayisahbe Mohd Yaacob Noorayisahbe Mohd Yacoob Nova Rijati Novi Hendriyanto, Novi Nugroho, Dicky Anggriawan Nur Ryan Dwi Cahyo Nuri Nuri Oktaridha, Harwinanda Oleiwi, Ahmed Kareem Parti Astuti, Yani Parti Astuti, Yani parti astuti, yani Parti Astuti1, Yani Parti Astuti1, Yani Pradana, Luthfiyana Hamidah Sherly Pradana, Rizky Putra Pradnyatama, Mehta Praskatama, Vincentius Pratama, Reza Arista Pratama, Zudha Pratiwi, Saniya Rahma Proborini, Ellen Pulung Nurtantio Andono Purwanto Purwanto Putra, Ifan Perdana Putri, Ni Kadek Devi Adnyaswari Rabei Raad Ali Rabei Raad Ali Rabei Raad Ali Rabei Raad Ali Raisul Umah Nur Ramadhan Rakhmat Sani Ratih Ariska Ruri Suko Basuki Safitri, Melina Dwi Saifullah, Zidan Sania, Wulida Rizki Santoso, Bagus Raffi Saputro, Fakhri Rasyid Sarker, Md Kamruzzaman Setiarso, Ichwan Setiawan, Fachruddin Ari Sinaga, Daurat Sinaga, Daurat Sinaga, Daurat Sinaga, Daurat Solichul Huda, Solichul Sudibyo, Usman Sudibyo, Usman Sudibyo, Usman Sugianto, Castaka Agus Sumarni Adi, Sumarni Suprayogi Suprayogi Suprayogi Suprayogi Tan Samuel Permana Tan Samuel Permana Titien Suhartini Sukamto Tri Esti Rahayuningtyas Umam, Choerul Umaroh, Liya Umaroh, Liya Utomo, Danang Wahyu Velarati, Khoirizqi Vincentius Praskatama Wahyu Dwy Permana Wellia Shinta Sari Wellia Shinta Sari Wellia Shinta Sari Widhi Bagus Nugroho Winarsih, Nurul Anisa Sri Winaryanti, Hida Sekar Wintaka, Aristides Bima Yaacob, Noorayisahbe Bt Mohd Yaacob, Noorayisahbe Mohd Yani Parti Astuti