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All Journal Teknika Techno.Com: Jurnal Teknologi Informasi MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) TEKNOLOGI: Jurnal Ilmiah Sistem Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Prosiding SNATIKA Vol 01 (2011) Benefit: Jurnal Manajemen dan Bisnis Register: Jurnal Ilmiah Teknologi Sistem Informasi Dinamika Teknik Mesin : Jurnal Keilmuan dan Terapan Teknik Mesin Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Journal of Honai Math JURNAL INSTEK (Informatika Sains dan Teknologi) Jurnal RESISTOR (Rekayasa Sistem Komputer) Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika Jurnal Pengabdian Al-Ikhlas Jurnal Informatika dan Rekayasa Elektronik Jurnal Chart Datum Soeropati: Journal of Community Service IICS Jurnal Informatika Teknologi dan Sains (Jinteks) WELFARE Jurnal Ilmu Ekonomi AKSIOMA : Jurnal Manajemen Jurnal Inovasi Pengabdian dan Pemberdayaan Masyarakat Dedikasi Saintek Jurnal Pengabdian Masyarakat Jurnal Krisnadana Jurnal Manajemen Dan Bisnis Ekonomi Information Technology Education Journal Nusantara Journal of Computers and its Applications Jurnal Inovasi Teknologi Terapan Journal of Information Technology and Cyber Security Engagement: Jurnal Pengabdian Kepada Masyarakat CYBER-Techn(Jurnal Informatika dan Industri) DEDIKASI SAINTEK Jurnal Pengabdian Masyarakat Edcomtech: Jurnal Kajian Teknologi Pendidikan
Lukman Hakim
Universitas Yudharta Pasuruan
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Nursing Physics Public Health Social Sciences Other

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Hybrid PSO-XGBoost Model for Accurate Flood Risk Assessment Nabilah, Lailatun; Hakim, Lukman
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11094

Abstract

Flood risk prediction is a crucial step in disaster mitigation. This study optimizes the Extreme Gradient Boosting (XGBoost) algorithm using the Particle Swarm Optimization (PSO) method to improve prediction accuracy. The process includes data cleaning, normalization, and classification of risk levels into low, medium, and high. The XGBoost model is trained both before and after parameter optimization of n_estimators, max_depth, and learning_rate. Before optimization, the model achieved 93% accuracy but struggled to identify minority classes. After optimization with PSO, accuracy increased to 97%, with the recall for the low-risk class improving from 21% to 57%. The optimized model also demonstrated more stable performance compared to Support Vector Machine (SVM) and Random Forest. These findings indicate that the combination of XGBoost and PSO can provide more accurate and efficient flood risk predictions.
Water Quality Classification Using SVM with PSO-Based Parameter Optimization Trisna Seviya; Lukman Hakim
Information Technology Education Journal Vol. 4, No. 3, August (2025)
Publisher : Jurusan Teknik Informatika dan Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/intec.v4i3.9746

Abstract

This study investigates the use of Support Vector Machine (SVM) enhanced with Particle Swarm Optimization (PSO) for water quality classification. Conventional SVM models often underperform when parameters are selected manually, resulting in reduced predictive accuracy. To overcome this limitation, PSO was applied to automatically optimize the SVM kernel parameters, enabling more reliable and robust classification. The research employed a quantitative experimental framework consisting of data preprocessing, model training, optimization, and performance evaluation. The dataset included physical and chemical attributes of water quality, which were normalized and prepared before classification. Evaluation was based on standard metrics such as accuracy, precision, recall, and F1-score. The results show that the PSO-optimized SVM consistently outperformed the baseline SVM model, producing more accurate and stable classifications. This confirms the potential of metaheuristic optimization in strengthening machine learning approaches for environmental data analysis. The main contribution of this study lies in applying a PSO–SVM framework to water quality classification, a domain where such integration has been rarely explored despite its importance for sustainable resource management. The findings provide both theoretical implications for advancing metaheuristic applications in environmental informatics and practical benefits for improving decision support in water quality monitoring and management.
KLASIFIKASI SERANGAN DDOS MENGGUNAKAN REQURSIVE FEATURE ELIMINATION DAN GRADIENT BOOSTING Candra Adi Lesmana; Lukman Hakim
Jurnal Informatika dan Rekayasa Elektronik Vol. 8 No. 1 (2025): JIRE APRIL 2025
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v8i1.1396

Abstract

Keamanan internet menjadi tantangan penting seiring dengan pertumbuhan layanan teknologi informasi yang semakin pesat. Serangan Distributed Denial of Service (DDoS) merupakan salah satu ancaman serius yang dapat menyebabkan crash pada server dan sistem jaringan dengan cara membanjiri jaringan dengan paket atau permintaan yang berlebihan. Dalam penelitian ini, diterapkan metode seleksi fitur Recursive Feature Elimination (RFE) pada proses klasifikasi serangan DDoS menggunakan algoritma Gradient Boosting. Tujuan Penelitian ini untuk melakukan penerapan algoritma seleksi fitur Reqursive Feature Elimination (RFE) untuk mengurangi jumlah fitur yang ada dalam data. Hasil pengujian menunjukkan bahwa penggunaan Gradient Boosting dengan parameter terbaik menghasilkan kinerja yang sangat baik, dengan akurasi sebesar 99,9%, presisi 99,8%, recall 99,9%, dan nilai F1 sebesar 99,9%. Kombinasi metode Reqursive Feature Elimination (RFE) dengan Gradient Boosting, di mana 10 fitur terbaik dipilih, tidak mempengaruhi hasil kinerja model secara signifikan, tetapi penerapan seleksi fitur ini berhasil mengurangi waktu komputasi secara signifikan dari 5463,24 detik menjadi 1023,19 detik tanpa mengorbankan kinerja model. Hasil ini menunjukkan bahwa metode seleksi fitur yang tepat sangat penting dalam meningkatkan efisiensi komputasi tanpa mengorbankan performa model dalam deteksi serangan DDoS.
Design of Voice Translator Application for Multinational Sign Language: A Notion for Global Communication for People with Hearing Issues Murtiasih Murtiasih; Ediyanto Ediyanto; Lukman Hakim
Edcomtech: Jurnal Kajian Teknologi Pendidikan Vol. 9 No. 2 (2024)
Publisher : Universitas Negeri Malang in collaboration with APSTPI and IPTPI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um039v9i22024p79-85

Abstract

Communication involves conveying information through the exchange of thoughts, messages, or information via speech, visuals, signals, writing, or behavior. Four central communication categories include written, visual, verbal, and nonverbal. Among those categories, sign language is a crucial form of nonverbal communication, serving as the primary language for people with hearing impairment. Communication between hearing individuals and those with hearing issues is not always straightforward. Accordingly, it is essential to establish a clear understanding of the sign language to avoid misinterpretation of the conveyed information. To address these challenges, this study designs a translator application, similar to Google Translate, that facilitates communication between individuals who speak different sign languages. By using this application, individuals can input the original message, then the application will translate the message into the desired language, thereby enabling better understanding and communication.
Identification of paleographic curvature using skeletonization and key point detection Fadhilatul Fitriyah; Dian Andriana; Muhammad Zulhaj Aliansyah; Lukman Hakim; Muhammad Faishol Amrulloh
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 2: April 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i2.27502

Abstract

Jawi script represents a vital component of the Islamic intellectual heritage of the Nusantara, preserved across numerous classical manuscripts. A primary challenge in digitizing these documents is character segmentation, particularly where handwritten characters connect without distinct boundaries. This research proposes a skeletonization-based segmentation method to address this issue, utilizing a dataset from 17 pages of the “Kitab Syair Perahu” manuscript containing 269 test characters. The pre-processing stage involves grayscale conversion, binarization, and noise removal through connected component analysis (CCA). The segmentation process then integrates skeleton structures, centroid positioning, intersection points, and loop detection. Evaluation results show the system successfully identified 187 out of 269 characters, achieving an accuracy of 0.801, a precision of 0.895, a recall of 86.38%, and an F1-score of 88.91%. While these results demonstrate the method’s effectiveness, the small dataset from a single manuscript limits its generalizability. Nevertheless, this study establishes a foundational step toward an automated Jawi image-processing system and the digital preservation of Islamic Nusantara literacy, contributing a tailored skeletonization-based approach for Jawi script.
Application of the traveling salesman problem to optimize skeletonization and stroke reconstruction Alifah Alifah; Dian Andriana; Muhammad Zulhaj Aliansyah; Lukman Hakim; Kholid Murtadlo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 2: April 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i2.27504

Abstract

The preservation of Turots Nusantara manuscripts written in Pegon script faces significant challenges due to physical deterioration and the complexity of handwritten styles. This study proposes a novel digitization approach based on image processing to extract and reconstruct handwriting strokes by combining skeletonization and the travelling salesman problem (TSP) algorithm. The novelty of this research lies in the application of a modified Greedy TSP algorithm capable of recognizing branching and cyclic structures typical of Arabic–Pegon characters, enabling accurate reconstruction of handwritten stroke sequences. The process involves preprocessing (grayscale, thresholding, and morphological operations), skeleton extraction using a thinning method, and weighted graph construction based on Euclidean distance between skeleton points. The proposed system achieved an average precision of 0.552, recall of 0.815, F1-score of 0.657, and accuracy of 0.82. These results demonstrate the method’s effectiveness in detecting and reconstructing character shapes from Pegon manuscripts. Practically, this approach offers potential applications in the automatic digitization, preservation, and analysis of Pegon script, contributing to the conservation of Indonesia’s Islamic intellectual and cultural heritage.
Co-Authors Achmad Afifuddin Adrianto, Dian Agus Prianto Ahfa, Mokhamad Isna Marzuki Ahwan, Zainul Ainiyah, Roisatul Aliansyah, Zulhaj Alifah Alifah Amang Fathurrohman Amelia, Resti Aminatuz Zuhriyah Aminatuz Zuhriyah As'idah, Fizriyatul Awang Rivaldo Bachtiar, Mochammad Alvin Tri Bagus Hari Sugiharto Bagus Hari Sugiharto Baroah, Hamida Maulana Lailatal Cahya Bagus Sanjaya Candra Adi Lesmana Deby Rizky Prihatini Dian Andriana E Ernawati, E Ediyanto Ernawati Evy Kamilah Ratnasari Fadhilatul Fitriyah Fafit Rahmat Aji Firda Nur Aisyah Firdaus, Lukman Fitrianawati, Meita Hapsari Titi Palupi Imam Syafi’i Imam Wahyudi Farid Irwan Abdullah Khoilil Fitria Kholid Murtadlo Lilis Trisnawati M Dayat M. Daimul Abror M. Ikmal Farih Miftahul Huda Miftahul Huda Misbach Munir Moch. Lutfi Mochamad Hasyim Mohamad Zein Saleh Muh. Aniar Hari Swasono Muhammad Fahmy Mayadi Muhammad Faishol Amrulloh Muhammad Imron Rosadi Muhammad Imron Rosadi Muhammad Zulhaj Aliansyah Mulyono Wobisono Murtiasih Murtiasih Nabilah, Lailatun Novitasari, Tri Wahyu Nur Aisyah, Firda Nur Robiah Nofikusumawati Peni Nurus Sa'adah Okariawan, I.D.K. Prayoga, Resdi Hadi Prayoga, Resdi Hadi Rahayu, Silvia Indah Ramli Ramli Resdi Hadi Prayoga Ridha, Faishal Ananta Roisatul Ainiyah Siti Mutrofin Sugiyarto Sugiyarto Sujita, Sujita Sulhan, M. Syarwani, Muhammad Syukur Sugeng Apriwiyanto Tiara Meylinda S Trisna Seviya Widodo S Pranowo Yusebla, Agil