Imanuel Harkespan
Fakultas Ilmu Komputer Dian Nuswantoro Semarang

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Kriptostegano Menggunakan Data Encryption Standard dan Least Significant Bit dalam Pengamanan Pesan Gambar Rizqa, Ifan; Safitri, Aprilyani Nur; Harkespan, Imanuel
Jurnal Masyarakat Informatika Vol 13, No 2 (2022): JURNAL MASYARAKAT INFORMATIKA
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.13.2.44547

Abstract

Aplikasi yang menerapkan metode LSB dan algoritma kriptografi DES ini berjalan dengan baik dan mampu menyisipkan dan mengekstrakan pesan dan dapat mengenkripsi dan deskripsi isi pesan. Pada penelitian Penyisipan Pesan Ke Dalama Gambar Dengan Menggunakan Metode Least Significant Bit (LSB) dan enkripsi dengan menggunakan Algoritma Data Encryption Standard (DES) yang mempunyai tujuan untuk menambah keamanan pesan agar seseorang yang tidak bertanggung jawab tidak dapat mengetahui sebuah pesan rahasia yang akan dikirim. Aplikasi ini hanya mengamankan sebuah pesan kedalam sebuah citra dan merubah isi pesan dari yang dikethaui maknanya ke yang tidak diketahui maknanya. Pada penelitian ini telah diterapkan metode LSB-DES pada gambar 281x320 pixel dengan cover berupa gambar berwarna dan pesan berupa kata. PSNR yang dihasilkan adalah 86.64 db untuk pesan kata “rahasia. Berdasarkan penelitian dapat disimpulkan hasil PSNR nilainya tinggi, maka kualitas citra bagus, maka dari itu hasil gambar steganogragi pun sangat baik.
PENGEMBANGAN WEB SERVICE MENGGUNAKAN FRAMEWORK FASTAPI UNTUK MENINGKATKAN KEMUDAHAN INTEGRASI SISTEM INFORMASI AKADEMIK MULTIPLATFORM Safitri, Aprilyani Nur; Harkespan, Imanuel
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 12 No 2 (2024): TEKNOIF OKTOBER 2024
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2024.V12.2.149-157

Abstract

Academic activities at Dian Nuswantoro University are managed using a web-based and mobile-based (Android and IOS) academic information system for students, lecturers, educators, and parents (guardians). The data retrieval process used by the academic information system is currently in each system itself so that it is prone to errors. Therefore, a back-end service is needed in the form of a web service that acts as a portal for the data retrieval process that can be used by the multiplatform academic information system. In addition to helping to avoid data retrieval errors, the web service that is built also provides complete and easy-to-understand documentation of web service usage. The average time required for the web service to provide a response when accessed by 1000 users is 6198ms (minimum 17ms and maximum 10017ms), meaning that the web service has good performance under high loads. The Extreme Programming method was chosen for the development of the web service in this study. This method consists of four stages, namely planning (analysis of what the system needs), design (visualization with Use Case diagrams), coding (using FastAPI Framework), and the last is testing (using BlackBox and JMeter for testing functions and security). The simplicity of this method can support the achievement of the desired results, namely a back-end service in the form of a web service, which can be used by a multi-platform academic information system to exchange data easily and accurately so that errors can be avoided, especially inconsistencies in presenting academic data.
Feature Fusion with Albumentation for Enhancing Monkeypox Detection Using Deep Learning Models Pratama, Nizar Rafi; Setiadi, De Rosal Ignatius Moses; Harkespan, Imanuel; Ojugo, Arnold Adimabua
Journal of Computing Theories and Applications Vol. 2 No. 3 (2025): JCTA 2(3) 2025
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.12255

Abstract

Monkeypox is a zoonotic disease caused by Orthopoxvirus, presenting clinical challenges due to its visual similarity to other dermatological conditions. Early and accurate detection is crucial to prevent further transmission, yet conventional diagnostic methods are often resource-intensive and time-consuming. This study proposes a deep learning-based classification model by integrating Xception and InceptionV3 using feature fusion to enhance performance in classifying Monkeypox skin lesions. Given the limited availability of annotated medical images, data augmentation was applied using Albumentation to improve model generalization. The proposed model was trained and evaluated on the Monkeypox Skin Lesion Dataset (MSLD), achieving 85.96% accuracy, 86.47% precision, 85.25% recall, 78.43% specificity, and an AUC score of 0.8931, outperforming existing methods. Notably, data augmentation significantly improved recall from 81.23% to 85.25%, demonstrating its effectiveness in enhancing sensitivity to positive cases. Ablation studies further validated that augmentation increased overall accuracy from 82.02% to 85.96%, emphasizing its role in improving model robustness. Comparative analysis with other models confirmed the superiority of our approach. This research enhances automated Monkeypox detection, offering a robust and efficient tool for low-resource clinical settings. The findings reinforce the potential of feature fusion and augmentation in improving deep learn-ing-based medical image classification, facilitating more reliable and accessible disease identification.
PENGEMBANGAN WEB SERVICE MENGGUNAKAN FRAMEWORK FASTAPI UNTUK MENINGKATKAN KEMUDAHAN INTEGRASI SISTEM INFORMASI AKADEMIK MULTIPLATFORM Safitri, Aprilyani Nur; Harkespan, Imanuel
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 12 No 2 (2024): TEKNOIF OKTOBER 2024
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2024.V12.2.149-157

Abstract

Academic activities at Dian Nuswantoro University are managed using a web-based and mobile-based (Android and IOS) academic information system for students, lecturers, educators, and parents (guardians). The data retrieval process used by the academic information system is currently in each system itself so that it is prone to errors. Therefore, a back-end service is needed in the form of a web service that acts as a portal for the data retrieval process that can be used by the multiplatform academic information system. In addition to helping to avoid data retrieval errors, the web service that is built also provides complete and easy-to-understand documentation of web service usage. The average time required for the web service to provide a response when accessed by 1000 users is 6198ms (minimum 17ms and maximum 10017ms), meaning that the web service has good performance under high loads. The Extreme Programming method was chosen for the development of the web service in this study. This method consists of four stages, namely planning (analysis of what the system needs), design (visualization with Use Case diagrams), coding (using FastAPI Framework), and the last is testing (using BlackBox and JMeter for testing functions and security). The simplicity of this method can support the achievement of the desired results, namely a back-end service in the form of a web service, which can be used by a multi-platform academic information system to exchange data easily and accurately so that errors can be avoided, especially inconsistencies in presenting academic data.