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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Sinergi Scientific Journal of Informatics JITK (Jurnal Ilmu Pengetahuan dan Komputer) Diglosia: Jurnal Kajian Bahasa, Sastra, dan Pengajarannya Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Pendidikan dan Kebudayaan Journal of Soft Computing Exploration Journal of Advances in Information Systems and Technology J-ABDIPAMAS (Jurnal Pengabdian Kepada Masyarakat) Jurnal Pendidikan IPA Indonesia Jurnal Abdi Negeri Recursive Journal of Informatics
Subhan Subhan
Universitas Negeri Semarang
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Penguatan Prestasi Mahasiswa Melalui Pendampingan dan Pembinaan Lembaga Kemahasiswaan di Jurusan Ilmu Komputer UNNES Subhan, Subhan; Jumanto; Hakim, M Faris Al; Ifriza, Yahya Nur; Prasetiyo, Budi
Jurnal Abdi Negeri Vol 1 No 1 (2023): Januari 2023
Publisher : Informa Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63350/jan.v1i1.2

Abstract

Prestasi mahasiswa menjadi bagian penting dari perguruan tinggi yang perlu dikuatkan. Pada kegiatan ini, penulis melakukan penguatan prestasi mahasiswa melalui pendampingan dan pembinaan lembaga kemahasiswaan. Permasalahan prioritas utama yang dihadapi lembaga kemahasiswaan adalah kurangnya pemanduan bakat mahasiswa dan kurangnya pembinaan bahasa inggris untuk presentasi dalam kompetisi. Sehingga solusi yang ditawarkan adalah peningkatan sikap sadar prestasi mahasiswa, pendampingan bakat mahasiswa, serta peningkatan kapasitas presentasi dan bahasa inggris. Solusi tersebut diwujudkan menggunakan model pembinaan sekolah prestasi yang terdiri dari 4 bentuk kegiatan. Metode pelaksanaan dengan pendekatan permasalahan yang melibatkan partisipasi aktif mitra. Bentuk kegiatan terdiri dari: (1) Pembentukan sekolah prestasi; 2) Workshop motivasi berprestasi; (3) Bimtek pembuatan media presentasi untuk kompetisi (4) Pelatihan presentasi bahasa inggris untuk kompetisi. Hasil kegiatan ini, lembaga kemahasiswaan sangat terbantu dengan penataan kegiatan kemahasiswaan. Mahasiswa lebih terarah dalam menargetkan prestasi yang ditargetkan.
Peningkatan Manajemen Ujian Online Bagi Guru di SMK Negeri 1 Karimunjawa Prasetiyo, Budi; Hakim, M. Faris Al; Purwinarko, Aji; Putra, Anggyi Trisnawan; Subhan, Subhan
Jurnal Abdi Negeri Vol 1 No 1 (2023): Januari 2023
Publisher : Informa Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63350/jan.v1i1.3

Abstract

Program Pembelajaran dan Penilaian online di era pandemi COVID-19 saat ini telah berlangsung selama satu tahun di SMK Negeri 1 Karimunjawa. Penerapan e-learning di sekolah ini berdampak pada bertambahnya tuntutan peningkatan kompetensi guru dalam melakukan penilaian secara online. Bagi siswa, tentu akan berdampak terhadap cara mereka mengikuti ujian di sekolah. Siswa harus membiasakan diri untuk menggunakan fitur-fitur yang terdapat pada aplikasi e-learning. Berdasarkan hasil komunikasi dan observasi dengan Kepala SMK Negeri 1 Karimunjawa, dibutuhkan aplikasi yang efektif untuk digunakan dalam penyelenggaraan penilaian atau ujian online untuk siswa. Aplikasi Ujian online juga diharapkan dapat digunakan untuk simulasi Asesmen Kompetensi Minimal (AKM) pada tahun pelajaran 2021/2022. Oleh karena itu, Jurusan Ilmu Komputer, FMIPA, UNNES menawarkan solusi berupa penerapan aplikasi e-ujian yang merupakan produk penelitian yang telah memiliki hak cipta. Metode yang digunakan dalam kegiatan pengabdian ini terdiri dari 3 tahap yaitu Analisis Kebutuhan, Perancangan Aplikasi, Pengembangan Aplikasi, Pelaksanaan, dan Evaluasi. Hasil dari kegiatan pengabdian masyarakat yang telah dilaksanakan adalah pengurus sekolah dan guru memahami potensi dari manajemen ujian berbasis daring untuk pembelajaran di masa pandemi sebagai upaya untuk menjaga standar proses pembelajaran.
Pemanfaatan Limbah Plastik dalam Bentuk Kerajinan Bunga sebagai Usaha Mengurangi Pencemaran Lingkungan di Desa Kalisalak Fajriani, Nurulia; Istiqomah, Rofita; Subhan, Subhan
Jurnal Abdi Negeri Vol 2 No 2 (2024): September 2024
Publisher : Informa Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63350/jan.v2i2.31

Abstract

Limbah sampah plastik merupakan masalah umum yang selalu dihadapi oleh masyarakat. Karena sifatnya yang sulit diuraikan di alam secara alami maka perlu adanya alternatif lain untuk mengatasi masalah tersebut. Pembuatan kerajinan ini bertujuan untuk mengurangi limbah plastik yang setiap hari semakin menumpuk. Meskipun belum dapat dirasakan dampaknya, tetapi di masa depan pengolahan limbah ini menjadi tindakan yang tidak bisa dianggap remeh. Pembuatan kerajian ini juga bermanfaat untuk mengurangi polusi udara akibat pembakaran sampah karena terdapat kandungan zat kimia dalam limbah plastik, mencegah timbulnya penyakit akibat menumpuknya limbah sampah. Dengan dibuatnya kerajian ini memberikan peluang bagi masyarakat untuk membuka usaha sehingga dapat menghasilkan uang dan meningkatkan pendapatan masyarakat. Metode yang digunakan adalah survey situasi dan proses pembuatan kerajinan bunga mulai dari pengumpulan limbah plastik hingga terbentuknya produk akhir. Produk ini diharapkan mampu memberikan manfaat bagi lingkungan maupun masyarakat sehingga di masa mendatang pencemaran lingkungan dapat berkurang dan dapat meningkatkan pendapatan masyarakat.
Strengthening Javanese literature material through the Novaja.id application as a form of Javanese cultural preservation Fateah, Nur; Subhan, Subhan; Ifriza, Yahya Nur; Ninsiana, Widhiya
Diglosia: Jurnal Kajian Bahasa, Sastra, dan Pengajarannya Vol 8 No 4 (2025)
Publisher : Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/diglosia.v8i4.1319

Abstract

The preservation of regional languages, including Javanese, increasingly requires digital innovations that can support literacy development and sustain readers’ engagement. However, existing digital platforms for Javanese literary access often lack systematic development frameworks and user-centered design features, limiting their effectiveness and long-term usability. Responding to this gap, this study develops the Novaja.id Javanese Novel Library application through the integration of the System Development Life Cycle (SDLC) and User-Centered Design (UCD) methodologies. The research began with a user needs analysis conducted through surveys and in-depth interviews, which informed the design of an intuitive interface and optimized user experience. A prototype was subsequently tested through usability evaluations, and user feedback was incorporated into iterative refinements. The findings show that the final application meets user needs effectively, demonstrating high navigation ease, satisfactory feature performance, and stable and secure functionality. These outcomes indicate that combining SDLC and UCD enhances application quality and usability. Overall, Novaja.id has strong potential to expand access to Javanese literary works and contribute to Javanese language literacy and cultural preservation.
Implementation of Content-Based Filtering in Book Recommender Systems Using K-Nearest Neighbor Model with Singular Value Decomposition and Word2Vec Naufal Afif Sadewa; Subhan Subhan
Recursive Journal of Informatics Vol. 4 No. 1 (2026): March 2026
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/rji.v4i1.21281

Abstract

Abstract. Books are a medium for understanding various topics, such as science, history, and culture. With the development of digital technology, accessing books has become easier, but choosing the right book among thousands of choices is a challenge. Book recommender systems are an efficient solution to help users find relevant books. One approach that can be used in book recommender systems is Content-Based Filtering, which utilizes content information in books to provide recommendations. Purpose: This research aims to develop a book recommender system by implementing Content-Based Filtering using K-Nearest Neighbor model with a combination of Singular Value Decomposition and Word2Vec in recommending relevant books according to each preference. Methods/Study design/approach: The method used involves several stages. First, data preprocessing is carried out to remove noise so as to retain important information. After data preprocessing, feature extraction uses the Term Frequency-Inverse Document Frequency method to represent book features through vectors. The result of this vector is then reduced in dimension using Singular Value Decomposition to reduce complexity and capture the most significant data structures. At another stage, book features are extracted using Word2Vec, which produces a semantic representation of the word in vector form. Next, the vector results from Singular Value Decomposition and Word2Vec are combined to form more informative features. Finally, the K-Nearest Neighbor model using the cosine similarity distance metric is used to calculate the similarity between books based on the combined features, so as to generate relevant book recommendations. Tests were conducted on the GoodReads Best Books dataset taken from Kaggle. Result/Findings: The evaluation results show that the proposed model is able to provide recommendations with good relevance values, measured using evaluation metrics such as Mean Average Precision and Normalized Discounted Cumulative Gain with the scores obtained respectively, namely 0.9637 and 0.9515 at parameter  is 5. Novelty/Originality/Value: The novelty in this research is the combination of Singular Value Decomposition vectors and Word2Vec vectors to produce a more informative feature representation, by utilizing statistical relationships between words and capturing the semantic meaning of words.
Optimizing Javanese script recognition using fine-tuned ResNet-18 and transfer learning Nur Fateah; Subhan Subhan; Yahya Nur Ifriza
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i1.pp443-453

Abstract

Javanese script, known as Aksara Jawa, is an ancient script used in historical and cultural texts. However, its complex character structure poses challenges for accurate recognition in modern digital applications. This study proposes an optimized classification approach for Aksara Jawa using a fine-tuned ResNet-18 model combined with the Adam optimization algorithm and transfer learning on the Hanacaraka image dataset. By leveraging the residual learning framework of ResNet-18, the model effectively captures deep spatial features of the script while reducing vanishing gradient issues. Fine-tuning is applied to enhance model adaptability, ensuring robust feature extraction specific to Javanese characters. Experimental results demonstrate that the fine-tuned ResNet-18 outperforms conventional deep learning architectures in recognizing Aksara Jawa characters, achieving 93% precision, 91% recall, 91% F1-score, and 91% accuracy. The study further explores the impact of hyperparameter tuning, data augmentation, and dropout regularization on model performance. The findings highlight the effectiveness of transfer learning in resource-limited scenarios, making it a feasible solution for optical character recognition (OCR) applications in Javanese script digitization. This research contributes to the preservation of cultural heritage through advancements in deep learning-based script recognition.
Analysis of Pre-Service Teachers' ICT Competencies in Indonesia and Japan Zaenuri Zaenuri; Arif Widiyatmoko; Subhan Subhan; Daiki Nakamura
Jurnal Pendidikan IPA Indonesia Vol. 15 No. 2 (2026): June 2026
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jpii.v15i2.26537

Abstract

The development of Information and Communication Technology (ICT) has an impact on education 5.0, improving educators' competence in using technology to support learning. The purpose of this study is to analyze the ICT competence of pre-service teachers in Indonesia and Japan. The research method used in this study is a survey to obtain information about the ICT competence of pre-service teachers in Indonesia. The research sample comprised 317 teacher study program students from two universities. The research instrument was a 30-item questionnaire administered via Google Forms to assess pre-service teachers' ICT competence. The results showed differences in the ICT competencies of pre-service teachers in Indonesia and Japan. Indonesian and Japanese pre-service teachers differ in their abilities in aspects such as understanding, technical skills, and teacher professional development. The average results of pre-service teachers' ICT competence in Indonesia and Japan, by aspect, show differences. All averages for aspects of ICT competence are 3-5, indicating good or very good criteria. Based on the study's results, it can be concluded that the ICT competence of pre-service teachers in Indonesia and Japan falls into the good category.
SQL Injection Detection Using Character-Level Embedding with Convolutional Neural Network and Gated Recurrent Unit Ahmad Andri Alfian; Subhan Subhan
Recursive Journal of Informatics Vol. 4 No. 2 (2026): September 2026
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/rji.v4i2.62096

Abstract

Abstract. SQL Injection is one of the most common cyberattacks targeting web applications by exploiting malicious SQL queries to gain unauthorized access to database systems. Conventional SQL Injection detection methods generally rely on manually engineered features or word-level representations, which may overlook fine-grained syntactic characteristics contained in SQL queries. Purpose: This study aims to develop and evaluate a SQL Injection detection model based on Character-level Embedding, Convolutional Neural Network (CNN), and Gated Recurrent Unit (GRU). The proposed model is expected to preserve character-level information while improving the capability to distinguish legitimate SQL queries from SQL Injection attacks. Methods/Study design/approach: The proposed model combines Character-Level Embedding, CNN, and GRU for binary classification of SQL queries. The dataset used is the SQL Injection Dataset obtained from the Kaggle website, consisting of 30,907 SQL queries with 19,529 legitimate queries and 11,378 SQL Injection queries. Before model training, the dataset was preprocessed using character-level tokenization, sequence padding, and dataset splitting with a ratio of 80:10:10 for training, validation, and testing. The model was implemented using TensorFlow and Keras, trained with the Adam optimizer and Binary Cross-entropy loss function, and evaluated using Accuracy, Precision, Recall, F1-score, and Confusion Matrix. Result/Findings: The proposed CNN-GRU model achieved an Accuracy of 99.64%, Precision of 100%, Recall of 99.03%, and F1-score of 99.51% indicating that the model effectively classifies legitimate SQL queries and SQL Injection attacks with high performance. Novelty/Originality/Value: It can be concluded that integrating Character-Level Embedding with hybrid CNN-GRU architecture enables the proposed model to learn both local character patterns and long-term sequential dependencies without requiring manual feature engineering. Therefore, the proposed approach provides an effective alternative for SQL Injection detection and has the potential to improve web application security.
Co-Authors Adam Satrio Kanza Ahmad Andri Alfian Ahmad Raihan Aji Purwinarko, Aji Anggyi Trisnawan Putra Apri Dwi Lestari Arif Widiyatmoko, Arif Budi Prasetio Budi Prasetiyo, Budi Budiman, Kholiq Cecep Bagus Surya Karta Atmaja Daiki Nakamura Damayanti, Dela Rista Efrilianda, Devi Ajeng Fajriani, Nurulia Fateah, Nur Fidya Nur Styaningsih Gading Nur Salmi Hakim, M Faris Al Hakim, M. Faris Al Istiqomah Istiqomah Istiqomah, Rofita Jumanto Jumanto Jumanto, Jumanto Listiaji, Prasetyo Muhammad Daffa Izzuddin Muhammad Iqhbal Abdillah Muhammad Syauqi Al-Haqqi Naufal Afif Sadewa Nur Afan syarifudin Nur Fateah Pamungkas, Dimas Hardi Rafael Vito Adrian Rakainsa, Senda Kartika Rini Muzayanah Riza Arifudin Sam'an, Muhammad Syarif, Deny Lukman Wicaksono, Suntoro Widhihastuti, Endah Widhiya Ninsiana Wiyan Herra Herviana Yahya Nur Ifriza Yuliana Putri Setyowati Zaenuri Mastur