Article Per Year (5 Year)
p-Index From 2021 - 2026
1.857
P-Index
This Author published in this journals
All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika Voice Of Informatics Abdimasku : Jurnal Pengabdian Masyarakat BERNAS: Jurnal Pengabdian Kepada Masyarakat Journal of Multiscale Materials Informatics Journal of Future Artificial Intelligence and Technologies
T. Sutojo
Program Studi Teknik Informatika, Fakultas Ilmu Komputer Universitas Dian Nuswantoro
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Neuroscience Nursing Public Health Social Sciences Veterinary Other

Published : 14 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 14 Documents
Search

 1   2 
IMPLEMENTASI COMPUTATIONAL THINKING PADA KURIKULUM MERDEKA MENGGUNAKAN METODE UNPLUGGED PROGRAMMING ACTIVITY (UPA) Sutojo, T.; Rustad, Supriadi; Akrom, Muhamad; Herowati, Wise
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 7, No 1 (2024): JANUARI 2024
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v7i1.1830

Abstract

The application of Computational Thinking (CT) in the Kurikulum Merdeka is one way to strengthen fundamental competencies and holistic understanding in education. CT skills can be taught through Unplugged Programming Activities (UPA), which is an approach to teaching CT skills without using computer tools. This approach is appropriate for schools that do not have adequate technological infrastructure and for the little ones, namely students under 9 years of age. This service aims to provide UPA method training for teachers at Gaussian Kamil School (GKS) so that it can be applied to the Merdeka Curriculum at GKS. The UPA activity materials used were the games "Bee-bot" and "My Robotic Friends Activity". It is hoped that this material can provide knowledge and skills regarding CT to training participants at GKS. The results of the pre-test and post-test evaluation showed an increase in scores before and after the training process for the participants. So it can be said that the results of this service show that the UPA method is suitable for use to teach CT skills in schools that do not have adequate technological infrastructure.
Finite-Key Analysis of BB84 and B92 QKD with Discrete Phase Randomization and Koashi Bound Oktaviansyah, Brenendra Putra; Sutojo, T.; Akrom, Muhamad
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 2 (2026): Article Research April, 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i2.15882

Abstract

Quantum Key Distribution (QKD) enables theoretically secure key exchange based on fundamental quantum principles such as the no-cloning theorem and Heisenberg’s uncertainty principle. However, practical implementations remain vulnerable to side-channel attacks caused by device imperfections, while many existing studies primarily analyze asymptotic security or isolated attack scenarios rather than realistic finite-key conditions. Unlike prior studies that focus on asymptotic or single-attack analyses, this work presents a comprehensive finite-key security evaluation of BB84 and B92 protocols under hybrid side-channel attacks using Discrete Phase Randomization (DPR) as a lightweight mitigation strategy and the Koashi bound for improved phase-error estimation in B92. Numerical simulations are performed using realistic system parameters with a finite-key size of 100 billion pulses across ten representative attack scenarios. The results show that applying DPR (M = 32) significantly suppresses phase-sensitive attack-induced errors, reducing the quantum bit error rate (QBER) from 11–50% to approximately 1.5–3.02%, thereby restoring practical secure key generation. B92 with the Koashi bound achieves secure transmission distance improvements from 181.6 km to 190.8 km without attacks and reaches 187.0 km under hybrid attacks with DPR, slightly exceeding BB84 in certain conditions. Peak secret key rates reach 0.1363 bit/pulse for BB84 and 0.0741 bit/pulse for B92. These findings demonstrate that non-orthogonal protocols can remain competitive under realistic finite-key constraints using practical mitigation techniques, although literature based induced QBER assumptions remain a limitation.
Evaluasi Dampak Pelatihan Portofolio Digital Berbasis Google Sites pada Siswa SMKN 9 Semarang Al Azies, Harun; Pertiwi, Ayu; Sutojo, T.; Setiadi, De Rosal Ignatius Moses; Pratama, Ananta Surya; Irnanda, Muhammad Diva; Umam, Taufiqul
BERNAS: Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 2 (2026)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/jb.v7i2.17536

Abstract

Perkembangan teknologi digital menuntut siswa sekolah menengah kejuruan memiliki kemampuan mendokumentasikan pengalaman dan kompetensi secara terstruktur melalui portofolio digital. Namun, pemanfaatan portofolio digital sebagai media representasi diri dan personal branding siswa masih belum optimal. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk mengevaluasi dampak pelatihan portofolio digital berbasis platform Google Sites terhadap pemahaman siswa Organisasi Siswa Intra Sekolah di SMK Negeri 9 Semarang. Metode yang digunakan adalah pendekatan evaluatif dengan desain one-group pretest–posttest. Data dikumpulkan melalui instrumen tes pemahaman yang mencakup klaster personal branding dan konsep portofolio digital, serta dianalisis menggunakan uji Wilcoxon Signed-Rank Test. Hasil kegiatan menunjukkan adanya peningkatan skor pemahaman siswa setelah pelaksanaan pelatihan, yang didukung oleh perbedaan skor pretest dan posttest yang signifikan secara statistik. Analisis berdasarkan klaster pemahaman juga menunjukkan peningkatan ketepatan jawaban pada kedua klaster yang diukur. Kegiatan ini menunjukkan bahwa pelatihan portofolio digital berbasis Google Sites memberikan dampak positif terhadap penguatan pemahaman siswa. Kegiatan pengabdian ini berpotensi dikembangkan melalui pendampingan berkelanjutan agar portofolio digital dapat dimanfaatkan secara optimal sebagai media dokumentasi dan pengembangan diri siswa.
Machine Learning-Assisted Prediction of Oxygen Evolution Reaction (OER) Activity for Catalyst Discovery: A Review Herowati, Wise; Akrom, Muhamad; Sutojo, Totok; Kurniawan, Achmad Wahid
Journal of Multiscale Materials Informatics Vol. 3 No. 1 (2026): April (In Progress)
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jimat.v3i1.15917

Abstract

The Oxygen Evolution Reaction (OER) is a fundamental process in electrochemical water splitting, playing a crucial role in sustainable hydrogen production. However, its intrinsically sluggish kinetics, involving complex four-electron transfer steps, remain a major bottleneck for efficient energy conversion. In recent years, Machine Learning (ML) has emerged as a powerful approach to accelerate catalyst discovery by enabling data-driven prediction of OER activity and reducing reliance on costly experimental and density functional theory (DFT) calculations. This review systematically summarizes recent advances in ML-assisted OER research, focusing on key aspects including dataset construction, descriptor engineering, model development, and performance evaluation. Various ML techniques, ranging from traditional algorithms such as Random Forest and Support Vector Machines to advanced deep learning approaches, are critically discussed in the context of catalyst screening and activity prediction. Particular attention is given to the role of physicochemical descriptors, including adsorption energies and electronic structure parameters, in governing model performance and interpretability. Furthermore, this review highlights current challenges, such as data scarcity, lack of standardization, and limited model generalization, while discussing emerging trends including active learning, explainable AI, and integration with high-throughput simulations. By providing a comprehensive overview, this work aims to guide future research toward the development of robust, interpretable, and scalable ML frameworks for accelerating the discovery of efficient OER catalysts.
Co-Authors Achmad Wahid Kurniawan Andreas Widiyantoro Astuti, Yani Parti Ayu Pertiwi Budi, Setyo Catur Supriyanto De Rosal Ignatius Moses Setiadi Egia Rosi Subhiyakto, Egia Rosi Erlin Dolphina Erna Zuni Astuti Etika Kartikadarma Fauzi Adi Rafrastara Hanny Haryanto Harun Al Azies Herowati, Wise Hidayat, Novianto Nur Ignatius Moses Setiadi, De Rosal Irnanda, Muhammad Diva Liya Umaroh, Liya Moch Anjas Aprihartha Muljono Muljono Mulyanto, Edy Noor Ageng Setiyanto, Noor Ageng Oktaviansyah, Brenendra Putra Pratama, Ananta Surya Rahmadianto, Rizky Setiawan, Marcell Adi Sudaryanto Sudaryanto Supriadi Rustad Suria Sandi Winarto Trisnapradika, Gustina Alfa Umam, Taufiqul Wisinggya, Kadhana Reya