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KOMBINASI DCT DAN BEAUFORT CHIPER UNTUK PENINGKATAN KEAMANAN HAK CIPTA CITRA DIGITAL Setiadi, De Rosal Ignatius Moses; Jatmoko, Cahaya; Rachmawanto, Eko Hari; Sari, Christy Atika
JST (Jurnal Sains dan Teknologi) Vol. 7 No. 2 (2018)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jstundiksha.v7i2.13795

Abstract

Informasi penting seperti hak cipta tentunya perlu diamankan, terlebih saat era digital saat ini yang semakin canggih. Pengamanan informasi dapat dilakukan dengan teknik kriptografi atau penyandian. Sedangkan untuk pengamanan hak cipta dapat dilakukan dengan teknik watermarking. Penelitian ini mengkombinasi teknik kriptografi dan watermarking. Sebelum watermark disisipkan watermark disandikan terlebih dahulu. Metode watermarking yang diusulkan adalah DCT dan metode kriptografi yang diusulkan adalah Beaufort cipher. DCT dipilih karena merupakan transformasi domain yang tahan terhadap macam-macam manipulasi, cukup ringan dalam kalkulasi dan menghasilkan watermarking yang impercept. Sedangkan Beaufort cipher merupakan algoritma yang sederhana tapi sangat aman untuk pengamanan data. Alat ukur yang digunakan  dalam eksperimen adalah SSIM, CC dan analisis histogram. Berdasarkan pengukuran terhadap hasil eksperimen dari metode yang diusulkan didapatkan hasil watermarking yang tahan terhadap serangan, impercept, dan aman.
KLASIFIKASI TERUMBU KARANG MENGGUNAKAN CNN MOBILENET Hadi, Heru Pramono; Rachmawanto, Eko Hari; Sari, Christy Atika
Semnas Ristek (Seminar Nasional Riset dan Inovasi Teknologi) Vol 8, No 01 (2024): SEMNAS RISTEK 2024
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/semnasristek.v8i01.7177

Abstract

Terumbu karang merupakan bagian dari ekosistem laut yang indah, namun dibalik keindahan tersebut, terumbu karang juga rentan akan kerusakan ekosistem yang terjadi, yang dimana dapat disebabkan oleh terumbu karang rentan mengalami pemutihan oleh aktivitas yang terjadi di sekitar ekosistem terumbu karang tersebut. Oleh karena itu, diperlukan proses klasifikasi atau pemilahan antara terumbu karang yang terkena pemutihan, sehat ataupun mati sehingga dapat diambil suatu tindakan konservatif yang tidak merusak ekosistem terumbu karang tersebut. Pada penelitian ini, akan dilakukan proses klasifikasi terumbu karang dengan menggunakan metode transfer learning Convolutional Neural Network yaitu dengan arsitektur MobileNet. Dalam proses penelitian ini, akan menggunakan dataset yang berjumlah total 1582 data citra terumbu karang yang memiliki 3 kelas utama dengan sebaran data yaitu 720 data bleached, 150 data dead dan 712 data healthy. Hasil yang didapatkan setelah dilakukannya proses pengujian pada penelitian ini yaitu arsitektur MobileNet mendapatkan akurasi pengujian yaitu sebesar 88%.
OPTIMASI INVISIBLE WATERMARKING METODE DCT BERBASIS SVD PADA CITRA BERWARNA Utomo, Danang Wahyu; Sari, Christy Atika; Rachmawanto, Eko Hari
Semnas Ristek (Seminar Nasional Riset dan Inovasi Teknologi) Vol 8, No 01 (2024): SEMNAS RISTEK 2024
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/semnasristek.v8i01.7140

Abstract

Studi ini mengevaluasi efektivitas metode watermarking dalam menyembunyikan informasi rahasia pada citra digital menggunakan Discrete Cosine Transform (DCT) dan Singular Value Decomposition (SVD). Pendekatan ini penting untuk menjaga keamanan dan hak cipta dalam era digital. Penggunaan DCT memungkinkan penyematan watermark tanpa mengorbankan kualitas visual citra. Hasil evaluasi menggunakan Mean Squared Error (MSE) menunjukkan bahwa citra Lena.bmp mencapai nilai MSE terendah pada Level 1 dengan 0.075, sementara Peppers.png memiliki nilai MSE terendah pada Level 1 dengan 0.0083, dan Baboon.jpg pada Level 1 dengan 0.0097. Pada sisi lain, hasil evaluasi menggunakan Peak Signal-to-Noise Ratio (PSNR) menunjukkan bahwa nilai PSNR tertinggi tercatat pada Level 1 untuk ketiga citra dengan nilai 48.17 dB. Temuan ini menunjukkan bahwa metode watermarking yang diterapkan menggunakan DCT dan SVD berhasil dalam menyematkan informasi rahasia pada citra digital dengan tingkat preservasi kualitas yang tinggi.
OTOMATISASI SISTEM KONTROL TUMBUH KEMBANG TOGA (TANAMAN OBAT KELUARGA) BERBASIS FUZZY C-MEANS Sari, Christy Atika; Sari, Wellia Shinta; Rachmawanto, Eko Hari
Semnas Ristek (Seminar Nasional Riset dan Inovasi Teknologi) Vol 8, No 01 (2024): SEMNAS RISTEK 2024
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/semnasristek.v8i01.7127

Abstract

Tanaman TOGA adalah tanaman obat keluarga yang memiliki peran penting dalam pengobatan tradisional. Dalam beberapa tahun terakhir, terjadi permasalahan serius terkait dengan pertumbuhan dan pemeliharaan tanaman TOGA, yang disebabkan oleh perubahan iklim, urbanisasi, dan kurangnya pengetahuan dalam budidaya tanaman ini. Untuk mengatasi tantangan ini, penelitian mengenai pengembangan Prototype Hidroponik Cerdas dilakukan. Prototype ini mengadopsi teknologi canggih yang memungkinkan pemantauan dan pengendalian otomatis terhadap semua aspek yang memengaruhi pertumbuhan tanaman, termasuk suhu, kelembaban udara, intensitas cahaya, pH larutan nutrisi, dan kadar oksigen dalam air. Dengan demikian, sistem ini mampu meningkatkan konsistensi, kecepatan pertumbuhan, dan kualitas tanaman TOGA, yang pada gilirannya mendukung ketersediaan sumber daya TOGA yang berkualitas tinggi bagi masyarakat serta berkontribusi pada pelestarian lingkungan yang lebih baik secara keseluruhan.
PERFORMA CONVOLUTIONAL NEURAL NETWORK DALAM DEEP LAYERS RESNET-50 UNTUK KLASIFIKASI MRI TUMOR OTAK Rachmawanto, Eko Hari; Hermanto, Didik; Pratama, Zudha; Sari, Christy Atika
Semnas Ristek (Seminar Nasional Riset dan Inovasi Teknologi) Vol 8, No 01 (2024): SEMNAS RISTEK 2024
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/semnasristek.v8i01.7125

Abstract

Tumor otak merupakan penyakit yang sangat kompleks dan beragam, dengan dampak yang serius pada kesehatan manusia. Berdasarkan data dari International Agency for Research on Cancer (IARC), variasi kondisi kesehatan penderita tumor otak disebabkan oleh faktor-faktor seperti ukuran, jenis, lokasi, dan tingkat keparahan tumor. Penelitian ini bertujuan untuk memberikan kontribusi signifikan dalam pemahaman dan deteksi dini tumor otak, dengan harapan dapat meningkatkan prognosis dan pengelolaan penyakit yang mengancam nyawa ini. Menggunakan metode Convolutional Neural Network (CNN) dengan arsitektur ResNet-50, penelitian ini mengembangkan model klasifikasi berdasarkan citra MRI tumor otak. Hasil evaluasi menunjukkan keberhasilan model dengan akurasi rata-rata mencapai 98.82%, memungkinkan identifikasi jenis tumor otak, seperti tumor jinak, meningioma, dan pituitary, dengan tingkat presisi dan recall mencapai 99.22% dan 100% secara berturut-turut. Penelitian ini memberikan harapan baru dalam diagnosis dini, memperkuat penanganan penyakit tumor otak, dan memberikan landasan bagi pengembangan solusi medis yang lebih efektif, membawa dampak positif pada pasien yang mengidap penyakit ini.
High-Quality Evaluation for Invisible Watermarking Based on Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD) Sofyan, Ega Adiasa; Sari, Christy Atika; Rachmawanto, Eko Hari; Cahyo, Nur Ryan Dwi
Advance Sustainable Science, Engineering and Technology Vol 6, No 1 (2024): November-January
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i1.17186

Abstract

In this research, we propose an innovative approach that integrates Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD) to enhance the quality and security of digital images. The purpose of this technique is to embed imperceptible watermarks into images, preserving their integrity and authenticity. The integration of DCT allows for an efficient transformation of image data into frequency components, forming the basis for embedding watermarks that are nearly invisible to the human eye. In this context, SVD offers an advantage by separating singular values and corresponding vectors, facilitating a more sophisticated watermarking process. The quality evaluation using metrics such as MSE, PSNR, UQI, and MSSIM demonstrates the effectiveness of this approach. Low average MSE values, ranging from 0.0058 to 0.0064, indicate minimal distortion in the watermarked images. Additionally, high PSNR values, ranging from 67.20 dB to 67.22 dB, affirm the high image quality achieved after watermarking. These results validate that the integration of DCT and SVD provides a high level of security while maintaining optimal visual quality in digital images. This approach is highly relevant and effective in addressing the challenges of image protection in this digital era.
A Good Evaluation Based on Confusion Matrix for Lung Diseases Classification using Convolutional Neural Networks Kamila, Izza Putri; Sari, Christy Atika; Rachmawanto, Eko Hari; Cahyo, Nur Ryan Dwi
Advance Sustainable Science, Engineering and Technology Vol 6, No 1 (2024): November-January
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i1.17330

Abstract

CNN has been widely used to detect a pattern with image classification. This study used CNN to perform a classification analysis of lung abnormality detection on chest X-ray images. The dataset consists of 5,732 2D images with dimensions of 200 x 200 x 1 divided into training data (85%) and testing data (15%). The preprocessing process includes image resizing, enhancement to increase contrast and reduce image complexity, and filtering to improve visibility and reduce noise. CNN is used to classify imagery into three categories, Normal (no abnormalities), Pneumonia, and Tuberculosis. The results showed a good level of accuracy, with an average accuracy of 97.24% in 3 trainings, and a 100% success rate in 6 classification experiments. This research provides insights into the detection of lung disorders and encourages further exploration in medical diagnosis.
Klasifikasi Citra Mengkudu Berdasarkan Perhitungan Jarak Piksel pada Algoritma K-Nearest Neighbour Irawan, Candra; Rachmawanto, Eko Hari; Atika Sari, Christy; Umah Nur, Raisul
Infotekmesin Vol 14 No 2 (2023): Infotekmesin: Juli, 2023
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v14i2.1827

Abstract

Noni fruit is included in exported food commodities in Indonesia. The size of noni fruit, based on human vision, generally has varied shapes with distinctive textures and various patterns, so that the process of filtering fruit based on color and shape can be done in large quantities. In this study, K-Nearest Neighbor (KNN) has been implemented as a classification algorithm because it has advantages in classifying images and is resistant to noise. Noni imagery is a personal image taken from a noni garden in the morning and undergoes a background subtraction process. The imagery quality improvement technique uses the Hue Saturation Value (HSV) color feature and the Gray Level Co-Occurrence Matrix (GLCM) characteristic feature. KNN accuracy without features is lower than using HSV and GLCM features. From the experimental results, the highest accuracy was obtained using HSV-GLCM at K is 1 and d is 1, namely 95%, while the lowest accuracy was 55% using KNN only at K is 5 and d is 8.
SECURE TEXT ENCRYPTION FOR IOT COMMUNICATION USING AFFINE CIPHER AND DIFFIE-HELLMAN KEY DISTRIBUTION ON ARDUINO ATMEGA2560 IOT DEVICES Permana langgeng wicaksono ellwid putra; Sari, Christy Atika; Isinkaye, Folasade Olubusola
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 4 (2023): JUTIF Volume 4, Number 4, August 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.4.1129

Abstract

In an Internet of Things (IoT) system, devices connected to the system exchange data. The data contains sensitive information about the connected devices in the system so it needs to be protected. Without security, the data in the IoT system can be easily retrieved. One way to prevent this is by implementing cryptography. Cryptography is a technique for protecting information by using encryption so that only the sender and receiver can see the contents of the information contained therein. The implementation of cryptography on IoT devices must consider the capabilities of IoT devices because in general IoT devices have limited processing capabilities compared to computer devices. Therefore, the selection of encryption algorithms needs to be adjusted to the computational capabilities of IoT devices. In this research, the affine cipher cryptography algorithm and Diffie-hellman key distribution algorithm are applied to the arduino atmega2560 IoT device. The purpose of this research is to increase the security of the IoT system by implementing cryptography. The method used in this research involves setting up a sequence of encryption and decryption steps using an affine cipher and diffie-hellman algorithms. Furthermore, these algorithms were implemented on an Arduino IoT device. Finally, the decryption time based on the number of characters and the avalanche test were tested. The results showed that on average, Arduino can perform decryption using affine cipher and diffie-hellman algorithms in 0.07 milliseconds per character. The avalanche test produced an average percentage of 45.51% from five trials.
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%.
Co-Authors AA Sudharmawan, AA Abdul Qohhar Abdul Syukur Abdussalam Abdussalam Abdussalam Abdussalam, Abdussalam Abiyyi, Ryandhika Bintang Ahmad Salafuddin Ajib Susanto Akbar, Fadhilah Aditya Akbar, Ilham Januar Alfany, Fauzan Maulana Ali, Rabei Raad Alifia Salwa Salsabila Alvian Ideastari, Nukat Alvin Faiz Kurniawan Anak Agung Gede Sugianthara Andi Danang Krismawan Anggraeny, Tiara Anidya Nur Latifa Annisa Sulistyaningsih Anny Yuniarti Antonius Erick Handoyo Arditya Prayogi Arfian, Aldi Azmi Ariq Arsalan Aris Marjuni Aristides Bima Wintaka Ariza, Said Fachri Aryanta, Muhammad Syifa Aryaputra, Firman Naufal Astuti, Yani Parti Auni, Amelia Gizzela Sheehan Bambang Sugiarto Briliantino Abhista Prabandanu Budi Harjo Cahaya Jatmoko Cahyo, Nur Ryan Dwi Candra Irawan Candra Irawan Castaka Agus Sugianto Chaerul Umam Chaerul Umam Cinantya Paramita D.R.I.M. Setiadi Danang Krismawan, Andi Danang Wahyu Utomo Danar Bayu Adi Saputra Danu Hartanto Daurat Sinaga Daurat Sinaga De Rosal Ignatius Moses Setiadi Desi Purwanti Kusumaningrum Desi Purwanti Kusumaningrum Desi Purwanti Kusumaningrum Didik Hermanto Doheir, Mohamed Doheir, Mohamed Doheir, Mohamed A S Dwi Puji Prabowo Edi Faisal Egia Rosi Subhiyakto Egia Rosi Subhiyakto Eko Hari Rachmanto Eko Hari Rachmawanto Eko Septyasari Elkaf Rahmawan Pramudya Ericsson Dhimas Niagara Erika Devi Udayanti Erlin Dolphina Erna Daniati Erna Zuni Astuti Erna Zuni Astuti Ery Mintorini Etika Kartikadarma Farrel Athaillah Putra Feri Agustina Fidela Azzahra Florentina Esti Nilawati Florentina Esti Nilawati Florentina Esti Nilawati Folasade Olubusola Isinkaye Folasade Olubusola Isinkaye Gede Pradistya Evan Aryaputra Giovani Ardiansyah Gumelar, Rizky Syah Guruh Fajar Shidik Gusta, Muhammad Bima Hadi, Heru Pramono Haqikal, Hafidz Haris Pujianto Hartono, Matthew Raymond Haryanto, Christanto Antonius Haryanto, Christanto Antonius Hasbi, Hanif Maulana Hayu Wikan Kinasih Heru Lestiawan Hidayah Rahmalan Hidayah Rahmalan Himawan, Reyshano Adhyarta Hussain Md Mehedul Islam Hyperastuty, Agoes Santika Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ibnu Utomo Wahyu Mulyono Ifan Rizqa Ihya Ulumuddin, Dimas Irawan Ikhsanuddin, Rohmatulloh Muhamad Imam Prayogo Pujiono Inzaghi, Reza Bayu Ahmad Isinkaye, Folasade Olubusola Islam, Hussain Md Mehedul Istiqomah, Annisa Ayu Ivan Stepheng Kamila, Izza Putri Kas Raygaputra Ilaga Kholifatun, Isnaeni Krismawan, Andi Danang Kumala, Raffa Adhi Kurniawan, Nicholas Alfandhy Kusuma, Edi Jaya Kusuma, Mohammad Roni Kusumawati, Yupie L. Budi Handoko Laksana, Deddy Award Widya Lalang Erawan Liya Umaroh Liya Umaroh, Liya Lucky Arif Rahman Hakim Mabina, Ibnu Farid Maulana Malik Ibrahim Al-Ghiffary Maxentia Kathleen Md Kamruzzaman Sarker Md Kamruzzaman Sarker Md Kamruzzaman Sarker Megan Febriana Putri Johana Mehta Pradnyatama Meitantya, Mutiara Dolla Mohamed A. S. Doheir Mohamed Doheir Mohamed Doheir Mohammad Rizal, Mohammad Mohd Yaacob, Noorayisahbe Muchamad Akbar Nurul Adzan Muhammad Eswin Bakkar Muhammad Khanif Naufal Muhammad Rikzam Kamal Mulyono, Ibnu Utomo Wahyu Mulyono, Ibnu Utomo Wahyu Munandar Rahmat Prayogi Munis Zulhusni Musab Iqtait Musab Iqtait Musfiqur Rahman Sazal Muslih Muslih Nabila, Qotrunnada Neni Kurniawati Ningrum, Amanda Prawita Nisa, Yuha Aulia Noor Ageng Setiyanto Noor Ageng Setiyanto, Noor Ageng Noorayisahbe Mohd Yaacob Noorayisahbe Mohd Yacoob Nova Rijati Nova Rijati Nugroho, Widhi Bagus Nur Ryan Dwi Cahyo Oktaridha, Harwinanda Oktayaessofa, Eqania Ozagastra Caluella Prambudi Ozagastra Caluella Prambudi Parti Astuti, Yani Parti Astuti, Yani parti astuti, yani Parti Astuti1, Yani Parti Astuti1, Yani Permana langgeng wicaksono ellwid putra Pradana, Luthfiyana Hamidah Sherly Pradana, Rizky Putra Praskatama, Vincentius Pratama, Zudha Pratiwi, Saniya Rahma Pulung Nurtantio Andono Purwanto Purwanto Purwanto Purwanto Puspa, Silfi Andriana Putri Mega Arum Wijayanti Raafiandy Wirawan Avicenna Rabei Raad Ali Rabei Raad Ali Rahmalan, Hidayah Raihan Ramadhan Hamzah Raisul Umah Nur Ramadhan Rakhmat Sani Ratih Ariska Rizka Dian Safitri Rizky Damara Ardy Robert Setyawan Sabilillah, Ferris Tita Saifullah, Zidan Salma Shafira Fatya Ardyani Sania, Wulida Rizki Santoso, Bagus Raffi Sari, Wellia Shinta Sari Shinta Sarker, Md Kamruzzaman Sarker, Md. Kamruzzaman Setiarso, Ichwan Setiawan, Fachruddin Ari Shelomita, Viki Ari 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 Tiara Anggraeny Titien Suhartini Sukamto Umah Nur, Raisul Umaroh, Liya Umaroh, Liya Utomo, Danang Wahyu Velarati, Khoirizqi Wellia Shinta Sari Wellia Shinta Sari Wellia Shinta Sari Wellia Shinta Sari Wellia Shinta Sari Wellia Shinta Sari Yaacob, Noorayisahbe Mohd Yani Parti Astuti Yupie Kusumawati Zaenal Arifin Zahra Ghina Syafira