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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Penelitian Multidisiplin Bangsa The Impact : Jurnal Pengabdian Kepada Masyarakat
Raharjo, Toto
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Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Nursing Public Health Social Sciences

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Penerapan Layanan Bimbingan Karir dengan Menggunakan Permainan Monopoli Karier untuk Meningkatkan Perencanaan Karier Siswa Kelas XI SMA Pusaka 1 Jakarta Azwania, Rafa Mufidah; Zuraida, Dita Juwita; Raharjo, Toto
Jurnal Penelitian Multidisiplin Bangsa Vol. 1 No. 9 (2025): Februari
Publisher : Amirul Bangun Bangsa Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpnmb.v1i9.332

Abstract

Bimbingan karier merupakan salah satu bentuk layanan dukungan yang cangkupannya sangat luas, dan berdampak pada kesehatan mental suatu masyarakat yang berkembang dalam proses mencari jati dirinya. Perencanaan karir (career planning) adalah suatu proses penyusunan dan pelaksanaan yang bertujuan untuk mencapai karir yang diinginkan. Tujuan penelitian untuk mengetahui pemberian layanan bimbingan karir dengan permainan monopoli karir dapat meningkatkan perencanaan karir siswa, metode yang digunakan yaitu metode kuantitatif non-equivalent two-group pretest-post test control group design, dan dari hasil analisis pre-test dan post-test terdapat perbedaan antara sebelum dan sesudah siswa diberikan layanan bimbingan karir menggunakan metode permainan monopoli karir dari rata-rata 219,14 menjadi sebesar 246,29.
ANALISIS FORENSIK DEEPFAKE BERBASIS CONVOLUTIONAL NEURAL NETWORK (CNN) UNTUK DETEKSI INKONSISTENSI TEKSTUR DAN POLA PADA CITRA WAJAH Raharjo, Toto; Irfan Adristi, Fikri; Yusroni Romadhona, Frendi; Rahmadi Syahputra, Rosi; Yusuf Halim, Muhammad; Ashshidiqie Rachman, Mikhail; Nur Marjianto, Rohsan; Santicho, Desylo; Kusuma, Permadi; Ramadhani, Erika
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 2 (2025): JATI Vol. 9 No. 2
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i2.13058

Abstract

Perkembangan teknologi artificial intelligence (AI) yang semakin pesat memunculkan teknologi deepfake yang menggunakan basis algoritma seperti generative adversarial networks (GANs) untuk memanipulasi citra wajah dengan tingkat realisme yang tinggi. Fenomena ini memunculkan tantangan dalam keamanan digital karena potensi penyalahgunaan, disinformasi, pelanggaran privasi, dan kejahatan dunia maya. Penelitian ini bertujuan mengembangkan model deteksi deepfake berbasis convolutional neural networks (CNN) yang mampu mengidentifikasi inkonsistensi tekstur dan pola biologis pada citra wajah secara efisien secara resource hadware dan efektif dalam proses deteksi image. Metode penelitian meliputi pengumpulan data dari dataset FaceForensics++ dan Celeb-DF, pra-proses data menggunakan augmentasi dan normalisasi, serta pengembangan model dengan arsitektur EfficientNetB0 yang dilatih menggunakan transfer learning pada dataset besar dengan menggunakan TensorFlow dan GPU. Hasil pengujian menunjukkan bahwa Model cenderung mengklasifikasikan gambar asli dengan nilai prediksi dari model neural network di atas 0,5, sementara gambar palsu justru dideteksi sebagai asli karena nilainya juga melebihi 0,5. Evaluasi menunjukkan bahwa model ini mencapai tingkat akurasi tinggi dalam mendeteksi manipulasi citra wajah, dengan teknik augmentasi yang meningkatkan kehandalan model terhadap berbagai skenario. Penelitian ini menyimpulkan bahwa pendekatan berbasis CNN efektif untuk deteksi deepfake, namun perlu pengembangan lebih lanjut untuk mengatasi keterbatasan pada data yang kompleks.
Securing Electronic Medical Documents Using AES and LZMA Raharjo, Toto; Yudi Prayudi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 2 (2025): April 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i2.6260

Abstract

With increasing threats in cyberspace, maintaining the integrity of electronic medical data is crucial. This study aims to develop a method that integrates encryption using Advanced Encryption Standard (AES) and compression with the Lempel-Ziv-Markov Algorithm (LZMA) to protect DICOM files containing sensitive information. This method is designed to address two main challenges: the growth of file sizes after the encryption process and the efficiency in data storage. In this study, an experimental design with random sampling was applied, testing 427 DICOM files from open libraries ranging in size from 513.06 KB to 513.39 KB to evaluate the implementation of this method in reducing file size, encryption time, and maintaining data integrity. The results show that this method is able to reduce file size by between 40-50% with an average encryption time of about 0.2-0.3 seconds per file. In addition, the data remains intact before and after the encryption process, which indicates that the integrity of the data is well maintained. Further analysis revealed that CPU usage during the encryption process reached 94.05%, while memory usage was recorded at 92.95 KB. In contrast, in the decryption process, CPU usage decreased to 78.16% with a much lower memory consumption, which was 31.07 KB. The findings have significant implications for medical information systems, allowing developers to easily implement these methods through APIs. This research is expected to be a reference for future studies that focus on data security in health information systems and provide new insights into the combination of encryption and compression in the context of medical data.
Peningkatan Kemampuan Problem Solving Siswa SMP Al-Ikhlas dengan Metode Mind Mapping dan Pohon Masalah Zuraida, Dita Juwita; Sulis, Ken Heryani; Asih, Marlia Tyas; Raharjo, Toto
The IMPACT : Jurnal Pengabdian Kepada Masyarakat Universitas Islam As-Syafiiyah Vol 2 No 1 (2025): The IMPACT : Jurnal Pengabdian Kepada Masyarakat Vo. 2 No. 1 Tahun 2025
Publisher : Lembaga Penelitian Dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34005/the impact.v2i1.4329

Abstract

The purpose of this program was to enhance the problem-solving skills of 8th-grade students at SMP Al-Ikhlas, Jakarta, who often face difficulties in applying learned concepts to real-life situations. This community service activity was conducted on August 19, 2024, involving 150 students. The methods used were Mind Mapping and Problem Trees, chosen as visualization tools to help students systematically and creatively identify problems, analyze root causes, and formulate solutions. The implementation stages included material explanation, a Q&A session, hands-on practice with relevant case studies, and evaluation through group presentations. The evaluation results showed a significant improvement, with 78.4% of participants reporting that they felt capable of solving problems independently after participating in the activity. Nevertheless, continued guidance from school counselors is still considered important. This program proved effective in equipping students with essential foundational skills to face future challenges.
Co-Authors Ashshidiqie Rachman, Mikhail Asih, Marlia Tyas Azwania, Rafa Mufidah Dita Juwita Zuraida Irfan Adristi, Fikri Kusuma, Permadi Nur Marjianto, Rohsan Rahmadi Syahputra, Rosi Ramadhani, Erika Santicho, Desylo Sulis, Ken Heryani Yudi prayudi Yusroni Romadhona, Frendi Yusuf Halim, Muhammad