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All Journal Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Layanan Masyarakat (Journal of Public Service) Journal of Multiscale Materials Informatics
Hidayat, Novianto Nur
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Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Social Sciences Other

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Investigation of Corrosion Inhibition Efficiency of Pyridine-Quinoline Compounds through Machine Learning Herowati, Wise; Akrom, Muhamad; Hidayat, Novianto Nur; Sutojo, Totok
Journal of Multiscale Materials Informatics Vol. 1 No. 1 (2024): April
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jimat.v1i1.10448

Abstract

Corrosion in materials is a significant concern for the industrial and academic fields because corrosion causes enormous losses in various fields such as the economy, environment, society, industry, security, safety, and others. Currently, material damage control using organic compounds has become a popular field of study. Pyridine and quinoline stand out as corrosion inhibitors among a myriad of organic compounds because they are non-toxic, inexpensive, and effective in a variety of corrosive environments. Experimental investigations in developing various candidate potential inhibitor compounds are time and resource-intensive. In this work, we use a quantitative structure-property relationship (QSPR)-based machine learning (ML) approach to investigate support vector machine (SVR), random forest (RF), and k-nearest neighbors (KNN) algorithms as predictive models of inhibition performance. (Inhibition efficiency) corrosion of pyridine-quinoline derivative compounds as corrosion inhibitors on iron. We found that the RF model showed the best predictive ability based on the coefficient of determination (R2) and root mean squared error (RMSE) metrics. Overall, our study provides new insights regarding the ML model in predicting corrosion inhibition on iron surfaces.
Penerapan Gamifikasi Materi Pembelajaran Tingkat SMA dengan Menggunakan Wordwall Setiyanto, Noor Ageng; Hidayat, Novianto Nur; Akrom, Muhamad; Pertiwi, Ayu; Aprihartha, Moch. Anjas; Safitri, Aprilyani Nur; Sudibyo, Usman; Prabowo, Wahyu Aji Eko; Al Azies, Harun; Naufal, Muhammad
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 8, No 1 (2025): JANUARI 2025
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v8i1.2851

Abstract

Kegiatan Pengabdian Masyarakat ini dilaksanakan di SMA Negeri 2 Mranggen, Demak, dengan tujuan untuk menciptakan variasi materi pembelajaran melalui proses gamifikasi, sehingga pembelajaran menjadi lebih menarik dan interaktif bagi siswa tingkat menengah. Tema dari kegiatan ini adalah gamifikasi materi pembelajaran menggunakan alat bantu Wordwall, yang memungkinkan pengintegrasian elemen permainan dalam proses belajar-mengajar. Kegiatan ini melibatkan para guru di SMA Negeri 2 Mranggen, Demak. Metode yang digunakan meliputi observasi untuk memahami kebutuhan pembelajaran di sekolah, serta pelatihan langsung dalam bentuk seminar, demonstrasi, dan sesi diskusi interaktif. Teknik ini dirancang agar para guru dapat memahami konsep gamifikasi, mempraktikkan penggunaan Wordwall, dan mengembangkan materi ajar yang kreatif serta sesuai dengan kurikulum yang ada. Hasil kegiatan menunjukkan bahwa implementasi gamifikasi materi pembelajaran melalui Wordwall efektif dalam meningkatkan pemahaman guru terhadap konsep gamifikasi. Selain itu, para guru merasa terbantu dan termotivasi untuk menciptakan materi pembelajaran yang lebih kreatif, menarik, dan dinamis.
Tree Tensor Network Quantum-Classical Hybrid Neural Architecture for Efficient Data Classification Hidayat, Novianto Nur; Akrom, Muhamad
Journal of Multiscale Materials Informatics Vol. 2 No. 1 (2025): April
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jimat.v2i1.12949

Abstract

We introduce the Tree Tensor Network-enhanced Quantum-Classical Neural Network (TTN-QNet), a hybrid architecture that leverages the hierarchical structure of Tree Tensor Networks for efficient parameter representation and Variational Quantum Circuits (VQC) for expressive modeling. Unlike Tensor Ring Networks, TTNs reduce parameter redundancy through a tree-based topology, enabling scalable and interpretable computation. The proposed TTN-QNet is evaluated on the Iris, MNIST, and CIFAR-10 datasets, achieving classification accuracies of 93.2%, 85.24%, and 81.67%, respectively, on binary classification tasks. TTN-QNet demonstrates rapid convergence and robustness against barren plateaus, offering a promising direction for deep quantum learning.
IMPROVING AWARENESS OF INTERNET SECURITY AND ETHICS AMONG STUDENTS AT SMA NEGERI 2 MRANGGEN Naufal, Muhammad; Hidayat, Novianto Nur; Trisnapradika, Gustina Alfa; Al Azies, Harun
Jurnal Layanan Masyarakat (Journal of Public Services) Vol. 9 No. 2 (2025): JURNAL LAYANAN MASYARAKAT
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/.v9i2.2025.204-214

Abstract

This community service initiative aimed to enhance the awareness of internet security and ethics among high school students at SMA Negeri 2 Mranggen, Demak Regency, Central Java. The program utilized a structured methodology consisting of outreach, training, and evaluation stages conducted in a hands-on environment within the school's computer laboratory. The training covered key topics such as data security, phishing attacks, malware, and ethical internet use. The sessions were held in the school’s computer laboratory to provide hands-on experience. Each training session had a duration of 3×45 minutes, attended by 31 students, allowing comprehensive exploration of the material. Pre- and post-tests were administered to assess the effectiveness of the training. The results demonstrated a significant improvement in students' knowledge, with average scores increasing from 49 in the pre-test to 72.67 in the post-test. A paired t-test analysis confirmed this improvement as statistically significant, with a T-statistic of -13.971 and a P-value of 2.07 × 10-14. The findings highlight the program's success in raising awareness and equipping students with the skills to navigate the digital world safely and responsibly. This initiative underscores the importance of educational programs in fostering internet literacy and security awareness among young users. To build on these findings, it is recommended that similar training sessions to be conducted regularly to reinforce the concepts learned. Additionally, a long-term plan is proposed as a form of sustainability of this community service program, namely by expanding the training targets not only to students but also to teachers, housewives and children who are already accustomed to gadgets.
Co-Authors Akrom, Muhamad Ayu Pertiwi Harun Al Azies Herowati, Wise Moch Anjas Aprihartha Muhammad Naufal, Muhammad Noor Ageng Setiyanto, Noor Ageng Prabowo, Wahyu Aji Eko Safitri, Aprilyani Nur Sudibyo, Usman T. Sutojo Trisnapradika, Gustina Alfa