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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 : Jurnal Teknik Informatika (JUTIF)

 1 
PNEUMONIA PREDICTION USING CONVOLUTIONAL NEURAL NETWORK Praskatama, Vincentius; Sari, Christy Atika; Rachmawanto, Eko Hari; Mohd Yaacob, Noorayisahbe
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.5.1353

Abstract

Pneumonia is condition which our lungs become inflamed due to infection from viruses, bacteria, or fungi. Pneumonia can affect anyone, both adults and children. Because of this, prevention of pneumonia is important. Prevention can be done by the process of maintain our immunity and lungs. In this study, had been done classify pneumonia based on X-ray images. This study using X-ray images dataset with total data is 5840 images in .jpg extensions. With a total number of images from training data is 5216 images and number of images from the test data is 624 images. The dataset that used in this research has 2 main classes, namely class normal and pneumonia. Normal class indicates that the X-Ray results are not detected with pneumonia. While the pneumonia class indicates that the processed X-Ray results are diagnose affected by pneumonia. The purpose of this research is building model that can be used to classify pneumonia based on X-Ray images. The classification process carried out in this study uses the Convolutional Neural Network method. The purpose of using the CNN method in the classification process of this research is because, in the process, CNN can extract features automatically and independently, so that the data provided does not need to be preprocessing first, but the data still produces good extraction features and can provide accurate classification results. The results from the testing process is carried out to run or perform in the pneumonia classification process, the CNN model built obtained a classification test accuracy of 87.82051205635071%.
A ROBUST AND IMPERCEPTIBLE FOR DIGITAL IMAGE ENCRYPTION USING CHACHA20 Nugroho, Widhi Bagus; Susanto, Ajib; Sari, Christy Atika; Rachmawanto, Eko Hari; Doheir, Mohamed
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 2 (2024): JUTIF Volume 5, Number 2, April 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.2.1470

Abstract

In the current era, data security is mandatory because it protects our personal data from being used by irresponsible people. The objective of this research is to show the robustness of the method we propose to encrypt images using the chacha20 algorithm which is included in the symmetric encryption cryptography technique and uses one key for both encryption and decryption processes. we use the encryption method by reading the bits from a digital image which is processed using the chacha20 algorithm to get the results of the digital image encryption. The results of this study indicate that the Chacha20 algorithm is secure to use when encrypting and decrypting digital images. The average MSE value generated by the chacha20 algorithm is 0.1232. The average PSNR value is 57.4784. The average value of UACI is 49.99%. The average value of NPCR is 99.602%. The test values were acquired by executing encryption and decryption processes on 5 distinct colour digital images with different size. Additionally, this study displays histograms for the original digital image, as well as for the encrypted and decrypted digital images, illustrating the pixel distribution in each. The histogram also serves as material for analysis of the success of the encryption and decryption processes in digital images.
VGG-16 ARCHITECTURE ON CNN FOR AMERICAN SIGN LANGUAGE CLASSIFICATION Meitantya, Mutiara Dolla; Sari, Christy Atika; Rachmawanto, Eko Hari; Ali, Rabei Raad
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2160

Abstract

Every country has its sign language such as in Indonesia there are 2 types namely Indonesian Sign Language System called SIBI and BISINDO (Indonesian Sign Language). American Sign Language (ASL) is a sign language that is widely used in the world. In this research, the classification of American Sign Language (ASL) using the Convolutional Neural Network (CNN) method using VGG-16 architecture with Adam optimizer. The data used is 14000 ASL image data with 28 classes consisting of letters A to Z plus space and nothing with a division of 90% training data and 10% validation data. From this research, the overall accuracy is obtained with a value of 98% and the accuracy value of validation data evaluation is 89.07%.
CLASSIFICATION OF ORGANIC AND NON-ORGANIC WASTE WITH CNN-MOBILENET-V2 Oktayaessofa, Eqania; Sari, Christy Atika; Rachmawanto, Eko Hari; Yaacob, Noorayisahbe Mohd
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2165

Abstract

Data from the Ministry of Environment and Forestry shows that the amount of organic and non-organic waste in 2023 has started to decline compared to the previous year. However, waste management in the central landfill is still not optimal. This is a problem for the community and the environment because it can cause pollution and disrupt public health around the disposal site. The reason for the difficulty of waste management at the landfill is that people still dispose of waste without separating it first. In addition, it is also due to a lack of public awareness and knowledge. One of the things that can be done to help overcome the problem of waste and its management is to develop an application that can help people understand the importance of waste selection and facilitate socialization in the community. For that, a model is needed that can classify waste based on its type with accurate accuracy. In this study, we propose a deep learning model, CNN with mobilenetV2 architecture, to classify organic and non-organic waste. This model uses a dataset consisting of 4380 images of organic and non-organic waste. Then 3 preprocessing stages were carried out, namely resize, normalization, and augmentation. From this process, data training was carried out and researchers obtained model evaluation results with 98.47% accuracy, 97% precision, 97% recall, and 97% F1 Score evaluation results. These results show that the proposed model is categorized as excellent.
Enhancing MPEG-1 Video Quality Using Discrete Wavelet Transform (DWT) with Coefficient Factor and Gamma Adjustment Krismawan, Andi Danang; Susanto, Ajib; Rachmawanto, Eko Hari; Muslih, Muslih; Sari, Christy Atika; Ali, Rabei Raad
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 2 (2025): JUTIF Volume 6, Number 2, April 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.2.4422

Abstract

Low-quality video caused by compression artifacts, noise, and loss of detail remains a significant challenge in video processing, affecting applications in streaming, surveillance, and medical imaging. Existing enhancement techniques often struggle with excessive noise amplification or high computational complexity, making them inefficient for real-time applications. This study proposes an improved video enhancement method using Discrete Wavelet Transform (DWT) with optimized coefficient factor and gamma adjustment. DWT is a mathematical approach that decomposes video frames into frequency subbands, enabling selective enhancement of important details. To analyze the impact of different wavelets, this study evaluates Coif5, db1, sym4, and sym8 wavelets. The sym8 wavelet, known for its high symmetry and ability to minimize artifacts, achieves the best results in preserving fine details and structural integrity. The coefficient factor is dynamically adjusted to sharpen details while preventing noise amplification, and gamma adjustment is applied to optimize brightness and contrast. The proposed method was evaluated using Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index (SSIM). Experimental results show that sym8 wavelet with gamma 0.7 and coefficient factor 0.3 provides the best balance, achieving an MSE of 0.062, a PSNR of 12.050 dB, and an SSIM of 0.674, outperforming Coif5, db1, and sym4 wavelets. The results indicate that wavelet selection significantly impacts video enhancement performance, with sym8 providing superior contrast enhancement and noise suppression. This study contributes to real-time video processing and AI-based applications, ensuring enhanced visual quality with minimal computational overhead.
Imperceptible Watermarking Using Discrete Wavelet Transform and Daisy Descriptor for Hiding Noisy Watermark Abdussalam, Abdussalam; Umam, Chaerul; Sari, Wellia Shinta; Rachmawanto, Eko Hari; Shidik, Guruh Fajar; Andono, Pulung Nurtantio; Lestiawan, Heru; Islam, Hussain Md Mehedul
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 2 (2025): JUTIF Volume 6, Number 2, April 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.2.4423

Abstract

This research aims at overcoming the challenge of improving security and robustness in digital image watermarking, a critical activity in protecting intellectual property against misuse and manipulation. In a move to overcome such a challenge, this work introduces a new form of watermarking that incorporates Discrete Wavelet Transform (DWT) and Daisy Descriptor, with a view to enhancing both durability and invisibility of the watermark. The proposed method embeds a noise-variant watermark into selected frequency sub-bands using DWT, while the Daisy Descriptor enhances resistance to noise-based attacks. Testing conducted with three grayscale images, namely Lena, Cameraman, and Lion, each with a resolution of 512 × 512 pixels, showed that the proposed DWT-Daisy Descriptor outperforms current methodologies, producing high Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) values. In fact, in Lena, a PSNR value of 63.71 dB and an SSIM value of 1 were attained, with Cameraman having a PSNR value of 68.33 dB and an SSIM value of 1. As for attack resistivity, a high PSNR value of 50.11 dB under Gaussian attack and 55.70 dB under Salt-and-Pepper attack, with SSIM values approaching 1, confirm the robustness of the proposed scheme. This study highlights the significance of an efficient and secure watermarking technique that not only preserves image quality but also withstands various distortions, making it highly relevant for digital content protection in modern multimedia applications.
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 Anidya Nur Latifa Annisa Sulistyaningsih Antonio Ciputra Antonius Erick Handoyo Aqsel, Aryasatya Muhammad Ardika Alaudin Arsa Arfian, Aldi Azmi Ariska, Ratih Aryanta, Muhammad Syifa Aryaputra, Firman Naufal Astuti, Yani Parti Asyari, Fajar Husain Aulia, Lathifatul Auni, Amelia Gizzela Sheehan Azzahra, Fidela Bijanto Bijanto Briliantino Abhista Prabandanu Cahaya Jatmoko Cahyo, Nur Ryan Dwi Candra Irawan Candra Irawan Castaka Agus Sugianto 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 Doheir, Mohamed Doheir, Mohamed Dwi Puji Prabowo Dwi Puji Prabowo, Dwi Puji Egia Rosi Subhiyakto Egia Rosi Subhiyakto Elkaf Rahmawan Pramudya Ellen Proborini Erna Daniati 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 Herman Yuliansyah, Herman Heru Agus Santoso Heru Lestiawan Hidayat, Muhammad Taufiq Hidayati, Ulfa Himawan, Reyshano Adhyarta Hyperastuty, Agoes Santika Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ihya Ulumuddin, Dimas Irawan Imam Prayogo Pujiono Inzaghi, Reza Bayu Ahmad Isinkaye, Folasade Olubusola Islam, Hussain Md Mehedul Istiawan, Deden Istiqomah, Annisa Ayu Ivan Stepheng Kamila, Izza Putri 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 Liya Umaroh Liya Umaroh, Liya Lucky Arif Rahman Hakim Lungido, Joshua Mabina, Ibnu Farid Mahadika Pradipta Himawan Mahiruna, Adiyah Maulana Malik Ibrahim Al-Ghiffary Md Kamruzzaman Sarker Md Kamruzzaman Sarker Md Kamruzzaman Sarker Meitantya, Mutiara Dolla Mohammad Rizal, Mohammad Mohd Yaacob, Noorayisahbe Muchamad Akbar Nurul Adzan Muhammad Khanif Naufal Muhammad Mahdi Mulyono, Ibnu Utomo Wahyu Munis Zulhusni Musab Iqtait Musfiqur Rahman Sazal Muslih Muslih Muslih Muslih Nabila, Qotrunnada Nanna Suryana Herman NGATIMIN, NGATIMIN Ningrum, Amanda Prawita Nisa, Yuha Aulia Noor Ageng Setiyanto Noor Ageng Setiyanto, Noor Ageng Noorayisahbe Mohd Yacoob Nova Rijati Novi Hendriyanto, Novi Nugroho, Dicky Anggriawan Nugroho, Widhi Bagus Nur Ryan Dwi Cahyo Nuri Nuri Oktaridha, Harwinanda Oktayaessofa, Eqania 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 Praskatama, Vincentius 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 Raisul Umah Nur Ramadhan Rakhmat Sani Ratih Ariska Ruri Suko Basuki Safitri, Melina Dwi Saifullah, Zidan Salsabila, Alifia Salwa Sania, Wulida Rizki Santoso, Bagus Raffi Saputra, Danar Bayu Adi Saputro, Fakhri Rasyid Sarker, Md Kamruzzaman Setiarso, Ichwan Setiawan, Fachruddin Ari Setiawan, Tan Valencio Yobert Geraldo Sinaga, Daurat Sinaga, Daurat Sinaga, Daurat Sinaga, Daurat Sofyan, Ega Adiasa Solichul Huda, Solichul Sudibyo, Usman Sudibyo, Usman Sudibyo, Usman Sumarni Adi, Sumarni Suprayogi Suprayogi Suprayogi Suprayogi Sutrisno, Hendra Syabilla, Mutiara Tan Samuel Permana Tan Samuel Permana Titien Suhartini Sukamto Tri Esti Rahayuningtyas Umah Nur, Raisul Umam, Choerul Umaroh, Liya Umaroh, Liya Utomo, Danang Wahyu Velarati, Khoirizqi Wahyu Dwy Permana Wellia Shinta Sari Wellia Shinta Sari Wellia Shinta Sari Winarsih, Nurul Anisa Sri Winaryanti, Hida Sekar Yaacob, Noorayisahbe Bt Mohd Yaacob, Noorayisahbe Mohd Yani Parti Astuti Zulhusni, Munis