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All Journal Information Technology and Telematics Dinamik Bulletin of Electrical Engineering and Informatics JUSIFO : Jurnal Sistem Informasi Suhuf Jurnal Teknoinfo Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknik Informatika UNIKA Santo Thomas KACANEGARA Jurnal Pengabdian pada Masyarakat J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Tekno Kompak Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Pengabdian Masyarakat Bumi Raflesia Jurnal Rekayasa Industri (JRI) Jurnal Tunas Infotek : Jurnal Informatika dan Teknologi Dinamika Informatika: Jurnal Ilmiah Teknologi Informasi J-SAKTI (Jurnal Sains Komputer dan Informatika) Bulletin of Information Technology (BIT) Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) NUSANTARA: Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat Intimas (Jurnal INTIMAS): Inovasi Teknologi Informasi Dan Komputer Untuk Masyarakat Duta Abdimas: Jurnal Pengabdian Masyarakat Jurnal Pengabdian Pada Masyarakat Information Technology International Journal (ITIJ) Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial semanTIK Servis : Jurnal Pengabdian dan Layanan kepada Masyarakat Jurnal Teknik Informatika dan Teknologi Informasi
Eko Nur Wahyudi
Universitas Stikubank
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Klasifikasi Dokumen Publik Berbasis NLP: Otomatisasi Proses Informasi Menuju Keterbukaan Data yang Adaptif dan Transparan Retnowati Retnowati; Veronica Lusiana; Eko Nur Wahyudi
Jurnal Teknik Informatika dan Teknologi Informasi Vol. 5 No. 2 (2025): Agustus: Jurnal Teknik Informatika dan Teknologi Informasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jutiti.v5i2.5693

Abstract

In the era of public information disclosure, digital documents have become strategic assets in supporting transparent, accountable, and participatory governance. Effective management of these documents is essential to ensure that public information services are responsive and accessible. However, document classification tasks carried out by Public Information and Documentation Officers (PPID) still rely heavily on manual processes, which are time-consuming, inefficient, and prone to human error. To address this challenge, this study aims to develop an intelligent classification model for public documents using Artificial Intelligence (AI) and Natural Language Processing (NLP), integrated within the Data Lifecycle Management (DLM) framework. The proposed solution was designed using the Design Science Research (DSR) methodology and implemented through Agile development practices. Evaluation was conducted in a simulated laboratory environment that mirrors real-world PPID operations.The developed model leverages transformer-based architectures, particularly BERT (Bidirectional Encoder Representations from Transformers), and is compared against traditional algorithms such as Naive Bayes and K-Nearest Neighbors (KNN). Experimental results show that the BERT model achieves superior performance, with an accuracy of 89%, precision of 0.88, recall of 0.89, and F1-score of 0.88. These metrics confirm that Transformer-based models are highly effective for classifying public documents into categories of information accessibility: available at all times, periodic, immediate, and exempted from disclosure.This research highlights the potential of AI-powered classification to streamline public information services, reduce workload, and enhance compliance with information disclosure laws. The findings support national development priorities such as RPJMN 2025 by contributing to digital transformation in the public sector. The study also provides a replicable framework for other government agencies aiming to implement adaptive and transparent document classification systems.
Analisis Komparatif Algoritma Infomap, Label Propagation, dan FluidC dalam Deteksi Komunitas Jaringan Undang-Undang Republik Indonesia Setyawan Wibisono; Herny Februariyanti; Eko Nur Wahyudi; Wiwien Hadikurniawati; Taufiq Dwi Cahyono
SemanTIK : Teknik Informasi Vol. 11 No. 2 (2025): SemanTIK : Teknik Informasi
Publisher : Informatics Engineering Department of Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55679/semantik.v11i2.150

Abstract

Setiap undang-undang di Indonesia pada bagian “Mengingat” dalam konsiderans memuat rujukan terhadap undang undang sebelumnya. Seiring dengan terbitnya undang-undang baru setiap tahun, jaringan keterkaitan antar undang-undang menjadi semakin kompleks dan sulit ditelusuri. Untuk itu, diperlukan pendekatan berbasis social network analysis, khususnya deteksi komunitas, guna memetakan dan mengidentifikasi pola keterkaitan tersebut. Penelitian ini mengevaluasi kinerja tiga algoritma deteksi komunitas, yaitu: Infomap, Label Propagation, dan Fluid Communities (FluidC), dalam mengidentifikasi komunitas pada jaringan undang-undang Indonesia periode 2019–2024. Dataset yang digunakan berbentuk graf berarah, di mana simpul merepresentasikan undang-undang dan sisi menunjukkan hubungan rujukan antar undang-undang. Evaluasi algoritma dilakukan menggunakan empat metrik: modularity, coverage, conductance, dan inter-cluster density. Hasil analisis menunjukkan bahwa Label Propagation unggul pada coverage (0,890), conductance (0,331), dan density (0,498), sehingga lebih efektif dalam menangkap kohesi tematik pada jaringan hukum. Infomap dan FluidC mencatat modularity tertinggi (0,433), tetapi menghasilkan komunitas dengan kepadatan internal yang lebih rendah. Berdasarkan temuan tersebut, Label Propagation direkomendasikan sebagai pendekatan yang lebih tepat untuk analisis jaringan undang-undang di Indonesia. In Indonesian legislation, the “Considering” section of each law’s preamble frequently contains references to preceding laws. As new laws are enacted each year, the network of interconnections among these legal documents has grown increasingly complex, making it difficult to trace and analyze their relationships. To address this challenge, a social network analysis (SNA) approach, particularly community detection, is required to map and identify the underlying patterns of legal interrelations. This study evaluates the performance of three community detection algorithms—Infomap, Label Propagation, and Fluid Communities (FluidC)—in identifying communities within the Indonesian legislative network for the period 2019–2024. The dataset is modeled as a directed graph, where nodes represent individual laws and edges indicate citations between them. Algorithm performance was assessed using four metrics: modularity, coverage, conductance, and inter-cluster density. The analysis results show that Label Propagation outperformed the others in terms of coverage (0.890), conductance (0.331), and density (0.498), demonstrating its effectiveness in capturing thematic cohesion within the legal network. In contrast, Infomap and FluidC achieved the highest modularity scores (0.433) but produced communities with lower internal density. Based on these findings, Label Propagation is recommended as a more suitable approach for analyzing Indonesia’s legislative networks.
Mengukur E-Participation Masyarakat di Era Transformasi Digital dengan Metode Multi Factor Evaluation Process (MFEP) Retnowati Retnowati; Eko Nur Wahyudi; Yunus Anis
JUSIFO : Jurnal Sistem Informasi Vol 8 No 2 (2022): December
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/jusifo.v8i2.13774

Abstract

The digital transformation era provides an opportunity for the public to exercise their right to information, where public agency is required to provide documents and information through Pejabat Pengelola Informasi dan Dokumen (PPID). This openness promises an important role for public participation through electronic access to information (E-Information), access to electronic consultations (E-Consultation), and participation in electronic decision-making (E-Decision Making). These three indicators are referred to as E-Participation. However, their implementation has encountered obstacles, leading to the need for research on E-Participation in the current community environment. This study employs a Soft System Methodology approach, specifically the Multi-Factor Evaluation Process (MFEP) method. The objective is to identify the indicators and criteria used in E-Participation, and to determine the level of E-Participation usage in Central Java based on the indicators used. The criteria used in this study pertain to the willingness of both the government and society, as well as the availability of infrastructure and information. The ranking results of the level of E-Participation indicate that public E-Participation is at an average level, where E-Information is the highest strengthening indicator, followed by E-Consultation, and E-Decision Making is the lowest.
Peningkatan Sensitivitas Model Boosting untuk Deteksi Diabetes Menggunakan SMOTE pada Imbalanced Dataset Setyawan Wibisono; Eko Nur Wahyudi; Imam Husni Al Amin
Dinamik Vol 31 No 2 (2026)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v31i2.10606

Abstract

This study aims to analyze the effect of SMOTE on the sensitivity of boosting models for diabetes detection using the BRFSS 2015 dataset. The dataset consists of 253,680 instances with 21 features and a binary target, namely diabetes and non-diabetes. The primary issue in the dataset is class imbalance, causing the models to be more biased toward recognizing the non-diabetes class. The algorithms employed in this study include AdaBoost, XGBoost, and Gradient Boosting, evaluated under two scenarios: without SMOTE and with SMOTE. Model performance was assessed using accuracy, precision, recall, F1-score, ROC-AUC, confusion matrix, and 10-fold cross validation. The results demonstrate that SMOTE improves recall across all models. The most significant improvement occurred in AdaBoost, where recall increased from 0.016551 to 0.711840. The cross-validation results also showed that AdaBoost + SMOTE achieved a recall value of 0.721384. Although accuracy and precision decreased, AdaBoost + SMOTE became the most sensitive model for detecting diabetes. Therefore, this model has potential to be utilized as an early diabetes screening support tool.
Ensemble Learning untuk Klasifikasi Penyakit Kardiovaskuler dengan Optimasi Hyperparameter menggunakan Grid Search Eko Nur Wahyudi; Setyawan Wibisono
Dinamik Vol 31 No 2 (2026)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v31i2.10608

Abstract

This study aims to optimize ensemble learning models for cardiovascular disease classification based on patients’ clinical data using the Grid Search method. The dataset used consists of 70,000 patient records with clinical attributes such as age, gender, height, weight, blood pressure, cholesterol, glucose, smoking habits, alcohol consumption, physical activity, and cardiovascular disease status. After preprocessing, 68,606 records were utilized, with a relatively balanced class distribution. The algorithms employed in this study include LightGBM, AdaBoost, and Gradient Boosting. Model evaluation was conducted using accuracy, precision, recall, F1-score, ROC-AUC, confusion matrix, and 10-fold cross validation. The results indicate that Gradient Boosting achieved the best performance with a ROC-AUC score of 0.804400 on the testing data and 0.801757 on cross validation. This model also produced the highest recall and F1-score values. Therefore, Gradient Boosting optimized with Grid Search is considered suitable for cardiovascular disease classification based on clinical data.
PELATIHAN FOTOGRAFI SEKOLAH GUNA PELATIHAN FOTOGRAFI SEKOLAH GUNA MENCIPTAKAN KARYA VISUAL YANG MENGINSPIRASI BAGI GURU DAN SISWA SMK/SMA DI SEMARANG: PELATIHAN FOTOGRAFI SEKOLAH GUNA MENCIPTAKAN KARYA VISUAL YANG MENGINSPIRASI BAGI GURU DAN SISWA SMK/SMA DI SEMARANG Eko Nur Wahyudi; Yunus Anis; Sri Mulyani
Jurnal Pengabdian Masyarakat Bumi Rafflesia Vol. 7 No. 3 (2024): Desember: Jurnal Pengabdian Kepada Masyarakat Bumi Raflesia
Publisher : Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Pelatihan fotografi di lingkungan sekolah memiliki peran penting dalam mengembangkan kreativitas visual dan keterampilan teknologi bagi guru dan siswa. Artikel ini membahas kegiatan pengabdian kepada masyarakat yang berjudul "Pelatihan Fotografi Sekolah Guna Menciptakan Karya Visual yang Menginspirasi bagi Guru dan Siswa SMK/SMA di Semarang". Tujuan utama dari pelatihan ini adalah untuk memperkenalkan teknik dasar fotografi serta cara memanfaatkan kamera digital atau smartphone dalam menciptakan karya visual yang menarik dan bermakna. Melalui pelatihan ini, guru diharapkan mampu menggunakan fotografi sebagai media pembelajaran interaktif di kelas, sementara siswa dapat mengekspresikan kreativitas mereka melalui gambar yang memiliki nilai estetika dan edukasi. Kegiatan ini dilaksanakan dalam bentuk workshop yang melibatkan teori dan praktik langsung. Hasil dari pelatihan menunjukkan peningkatan pemahaman peserta terhadap teknik dasar fotografi, komposisi gambar, dan editing sederhana. Dampaknya terhadap masyarakat, khususnya lingkungan sekolah, terlihat dari meningkatnya kemampuan guru dan siswa dalam menghasilkan karya visual yang dapat digunakan sebagai media informasi dan promosi sekolah, sehingga menginspirasi dan mempererat hubungan dengan komunitas sekitar. Dengan demikian, program ini tidak hanya membantu meningkatkan keterampilan fotografi di kalangan guru dan siswa, tetapi juga berkontribusi pada pengembangan pembelajaran berbasis visual di sekolah.
Co-Authors . Narwati Adi Suryanto Adi, Triatmojo Agus Prasetyo Utomo Ali Maskur Andreantoni, Jefry Arief Jananto Arief Susanto Artin Bayu Mukti Azhari, Andi Budi Hartono budi hartono Cahyono, Taufik Dwi Cici Suhartini Dwi Agus Diartono Dwi Budi Santoso Edy Supriyanto Edy Supriyanto Edy Supriyanto Eka Ardhianto Endang Lestariningsih Fatkhul Amin Fitika Andraini Hari Murti Hari Murti Heribertus Yulianton Herny Februariyanti Herny Februariyanti Hersatoto Listiyono Imam Husni Al Amin Jati Sasongko Wibowo Kristophorus Hadiono Kurniawan, Harnanda Cahya LUKITO, ADAM Mardi Siswo Utomo Muhammad A.R. Hidayat Muhammad Ali Novita Mariana P Purwatiningtyas Purwatiningtyas Purwatiningtyas Purwatiningtyas Purwatiningtyas Purwatiningtyas Purwatiningtyas, P R. Soelistijadi Radyanto, Mohammad Riza Rara Sri Artati Redjeki Retnowati Retnowati Retnowati Retnowati Retnowati Retnowati Retnowati Reza Haris Alfikri Rizal, Ansar Sariyun Naja Anwar Setyawan Wibisono Sri Mulyani Sri Mulyani Sugiyamto Sugiyamto, Sugiyamto Sulastri Sunardi Sunardi Suparmanto, Lulut Taufiq Dwi Cahyono Teguh Khristianto Theresi Dwiati Wismarini Theresia Dwiati Wismarini Veronica Lusiana Wahrudin, Wahrudin Widianto Tri Handoko Widiyanto Tri Handoko Wismarini, Th Dwiati Wiwien Hadikurniawati Yohanes Suhari Yunus Anis Yunus Anis Yunus Anis, Yunus Ziana, Liana Rahma Zuly Budiarso