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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Edutech Semantik Techno.Com: Jurnal Teknologi Informasi Jurnal Teknologi dan Manajemen Informatika Bulletin of Electrical Engineering and Informatics JSI: Jurnal Sistem Informasi (E-Journal) Jurnal Ilmiah Kursor Indonesian Green Technology Journal Jurnal Transformatika International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics JAIS (Journal of Applied Intelligent System) JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Tech-E Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control CogITo Smart Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING International Journal of New Media Technology MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Data Science: Journal of Computing and Applied Informatics JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science Indonesian Journal of Electrical Engineering and Computer Science International Journal of Advances in Data and Information Systems Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences JOURNAL SCIENTIFIC OF MANDALIKA (JSM) Jurnal Pendidikan dan Teknologi Indonesia Jurnal Teknologi Informasi Cyberku Studies in English Language and Education Moneter : Jurnal Keuangan dan Perbankan Scientific Journal of Informatics Journal on Pustaka Cendekia Informatika
Pulung Nurtantio Andono
Universitas Dian Nuswantoro
Aerospace Engineering Agriculture, Biological Sciences & Forestry 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 Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Menavigasi Dunia Digital dengan Meningkatkan Literasi Office, TI, dan Internet di Kalangan Siswa-Siswi Pondok Pesantren Raudhatul Qur'an Paramita, Cinantya; Andono, Pulung Nurtantio; Sudibyo, Usman; Rafrastara, Fauzi Adi; Supriyanto, Catur
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 6, No 2 (2023): Mei 2023
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/ja.v6i2.1338

Abstract

Peningkatan popularitas penggunaan perangkat komputer semakin berkembang di berbagai lapisan masyarakat. Pondok pesantren, yang sebelumnya dianggap sebagai tempat yang kurang produktif dan hanya diperuntukkan bagi mereka yang beragama, kini melakukan inovasi untuk meningkatkan peran dan potensi dalam mendukung kemaslahatan lingkungan sekitarnya. Pondok Pesantren Raudhatul Qur’an di Kauman Semarang telah banyak menciptakan siswa yang berhasil menghafal Al-Quran. Setelah menyelesaikan studi di pondok, banyak dari mereka yang melanjutkan pendidikan ke sekolah formal atau menjadi pemuka agama yang memberikan pengajaran dan bimbingan kepada masyarakat dalam memahami agama Islam di lingkungan mereka. Oleh karena itu, pelatihan teknologi komputer diperlukan untuk memberikan pengetahuan dan keterampilan bagi para santri agar dapat dimanfaatkan untuk membantu mengurus keperluan administrasi di pondok pesantren dan berguna bagi masa depan mereka. Sebanyak 53 santri diikutsertakan untuk mengikuti pelatihan yang mencakup pengenalan dasar teknologi informasi [1] seperti hardware, software, penggunaan aplikasi office seperti Word, Excel, dan PowerPoint, serta internet untuk komunikasi dan pengiriman data digital. Berdasarkan hasil pelatihan yang dilaksanakan, para santri memberikan respon positif seperti yang terlihat pada diagram 3 dan 4. Pada diagram 3 menunjukkan bahwa 81,4% dari para santri sangat tertarik dengan pelatihan tersebut, sementara hanya 13,9% yang merasa biasa-biasa saja dan 10,7% yang terpaksa mengikuti. Selain itu, hasil perbandingan pretest dan postest pada diagram 4 menunjukkan peningkatan yang signifikan setelah para santri mengikuti pelatihan tersebut.
Enhanced Classification of Lombok Pearl Quality Based on Shape and Size Using PSO-Optimized Artificial Neural Network Anshori, Muhammad Izzul; Andono, Pulung Nurtantio; Soeleman, Arief
International Journal of Advances in Data and Information Systems Vol. 6 No. 3 (2025): December 2025 - International Journal of Advances in Data and Information Syste
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i3.1434

Abstract

This study aims to develop an intelligent classification model for pearl quality assessment using an integrated approach combining Gray Level Co-occurrence Matrix (GLCM), Particle Swarm Optimization (PSO), and Artificial Neural Network (ANN). Sixteen texture features were extracted from four directional orientations using GLCM. PSO was employed as a feature selection algorithm to reduce dimensionality and enhance classification performance. Two ANN models were compared: a baseline model using all GLCM features and an optimized model utilizing only PSO-selected features. The models were trained and validated using 10-fold cross-validation. Results showed that the PSO-enhanced ANN achieved an accuracy of 94.72%, outperforming the baseline model which reached only 89.17%. Further evaluations using confusion matrix, Receiver Operating Characteristic (ROC) analysis, and Principal Component Analysis (PCA) confirmed the superior discriminative capability and improved class separability of the optimized model. These findings highlight the effectiveness of combining swarm intelligence with neural networks in texture-based classification tasks, offering a robust and scalable solution for automated quality inspection in the pearl industry and related domains.
Climate Change Utilization Strategies Through the Lens of Technology: A Scientific Review Suryawijaya, Tito Wira Eka; Andono, Pulung Nurtantio; Yusianto, Rindra
Indonesian Green Technology Journal Vol. 13 No. 2 (2024)
Publisher : Sekolah Pascasarjana, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.igtj.2024.013.02.02

Abstract

This study sheds light on the untapped potential of AI in addressing the complex climate change challenges, simultaneously promoting energy efficiency and sustainable development. Issues such as carbon emissions and global climate shifts demand sophisticated solutions, and AI emerges as a versatile tool across various domains, including industry, renewable energy, and meteorological predictions, offering promising resolutions. The research findings unequivocally demonstrate AI's ability to optimize energy consumption, simulate solar radiation, predict severe weather conditions, and contribute to overall sustainability efforts. Despite existing challenges, such as substantial costs and data shortages, the prospects presented by AI for improving energy efficiency and embracing renewable energy sources are notably promising. The novelty of this research lies in its emphasis on AI's pivotal role in energy, meteorology, and grid management, underscoring the imperative collaborative synergy among governmental bodies, industrial players, and research institutions to drive sustainable AI innovations. This study encourages a holistic approach to harnessing AI's potential for mitigating climate change impacts and fostering a more sustainable future.
Market Value Tier Classification of Indonesian Football Players using Ensemble Machine Learning and SHAP Analysis Paramita, Cinantya; Wildan Akhya, Malfino; Nurtantio Andono, Pulung
Jurnal Teknologi dan Manajemen Informatika Vol. 11 No. 2 (2025): Desember 2025
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v11i2.16399

Abstract

The persistent discrepancy between actual transfer fees and the theoretical market values of football players highlights the need for a more objective and data-driven framework for player valuation. This study aims to classify the market value tiers of Indonesian Liga 1 players in the 2024/2025 season using an ensemble-based machine learning approach integrated with SHAP interpretability analysis. The dataset comprises 226 players with 27 attributes encompassing demographic, career, performance, physiological, and socio-economic dimensions. The research process involved secondary data collection, preprocessing, feature engineering, and percentile-based label construction, followed by model training using Random Forest, XGBoost, CatBoost, and a Stacking Ensemble. Experimental results show that the CatBoost model achieved the best performance, attaining an accuracy of 89%, a Macro-F1 score of 0.85, and an F1(High-Tier) of 0.78, demonstrating its robustness in handling heterogeneous and imbalanced data. SHAP analysis identified minutes played, age, and social media exposure as the most influential variables determining market value tiers. These findings demonstrate that combining ensemble learning with model interpretability can yield a transparent, adaptive, and practical framework for data-driven player valuation. The proposed approach provides actionable insights for football clubs and analysts in optimising player recruitment and developing fairer, evidence-based transfer strategies.
Comparative Analysis of ResNet-Based Wagner-Scale Classification for Imbalanced DFU Data Ramadhan, Aditya Wahyu; Pulung Nurtantio Andono; M. Arief Soeleman
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 6 (2025): December 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i6.7016

Abstract

Diabetic Foot Ulcers (DFU) are a serious complication of diabetes mellitus and carry a high risk of lower extremity amputation if not treated in a timely manner. The conventional classification process, which relies on visual inspection by clinicians, tends to be subjective and inconsistent. Therefore, this study proposes a multiclass classification model for DFU based on the Wagner Scale (Grades 0–5) using the ResNet-50 architecture with a transfer learning approach as the core machine learning method. The dataset used in this study consists of 1,415 clinical wound images that were annotated and verified by medical professionals. The dataset is highly imbalanced, with 543 images in Grade 0, 110 in Grade 1, 252 in Grade 2, 145 in Grade 3, 293 in Grade 4, and only 72 images in Grade 5. To address this imbalance, random oversampling (ROS) was applied, in addition to standard preprocessing techniques such as normalization and data augmentation to increase training data diversity.Experimental results demonstrate that the proposed model achieves high classification performance based on accuracy, precision, recall, and F1-score. Specifically, the model obtained a precision of 0.96, recall of 0.95, and F1-score of 0.95, indicating consistent and robust classification performance across all Wagner grades. The best configuration (ResNet-50 + ROS) successfully improved the classification performance across minority grades (e.g., Grade 1 and Grade 5). Moreover, the model consistently identifies minority classes and does not exhibit signs of overfitting. Model optimization using the Adam optimizer and data balancing strategies significantly improves the generalization capability of the classifier. These findings indicate that the proposed model is not only effective for automatic DFU classification, but also has great potential to support objective clinical decision making and accelerate diagnosis, particularly in healthcare facilities with limited resources.
Perspektif Baru Enterprise Architecture Pemerintahan Kota Mataram Berbasis TOGAF ADM Husain Husain; Pulung Nurtantio Andono; M. Arif Soeleman
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 16 No. 2 (2017)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v16i2.6

Abstract

TIK salah satu penentu keberhasilan sebuah organisasi dalam mencapai visi dan misinya. Terpilihnya pemimpin yang baru, terbentuknya SKPD baru dengan visi misi baru sehingga master plan yang lama di anggap sudah tidak relevan lagi, sehingga persoalan yang muncul diselesaikan dengan cara reaktif dan memungkinkan persoalan yang sama akan muncul kembali pada masa yang akan datang. Arsitektur enterprise adalah cara untuk membangun arsitektur TIK dari sebuah organisasi yang berfokus pada arsitektur bisnis, arsitektur data, arsitektur aplikasi dan arsitektur teknologi. Penelitian ini merupakan penelitian deskriptif kualitatif dengan pendekatan studi kasus. Metodologi yang digunakan adalah Enterprise Architecture TOGAF ADM sebagai kerangka acuan untuk perencanaan strategis TIK Pemerintahan Kota Mataram. Subyek pada penelitian ini adalah responden yang memiliki kewenangan dalam pengambilan keputusan terkait TIK dan pengguna TIK di Dinas Komunikasi dan Informatika (DISKOMINFO). Kebutuhan bisnis yang terdiri dari Arsitektur Data, Aplikasi dan Teknologi diidentifikasi dan diusulkan untuk mendukung aktivitas bisnis demi pencapaian tujuan organisasi. Hasil dari penelitian ini dengan menganalisa penggunaan penerapan teknologi informasi dan komunikasi(TIK) Seperti Sumber daya Manusia yang terlibat, kebutuhan aplikasi dan infrastruktur jaringan komputer dalam untuk mendukung proses bisnis dalam pelaksanaan roda pemerintahan Kota Mataram, dengan menggunakan metode scorecard uji kelayakan dengan rata-rata perolehan 76%.
Underwater image enhancement with fuzzy histogram equalization and adaptive color correction Suharyanto, Suharyanto; Andono, Pulung Nurtantio; Fanani, Ahmad Zainul; Pujiono, Pujiono
International Journal of Advances in Intelligent Informatics Vol 12, No 1 (2026): February 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v12i1.2174

Abstract

Marine exploration continues to increase as new technologies, such as computer vision implemented in underwater vehicles and robots, develop. Identifying underwater objects is challenging due to environmental conditions, including poor lighting and color absorption in the viewed image. Underwater image enhancement has been widely applied to overcome these obstacles. Therefore, this study presents a new workflow for improving the quality of underwater images. A combination of the fuzzy histogram equalization (FHE) and adaptive color correction (ACC) methods is used to increase contrast and restore absorbed colors. This study proposes combining FHE and ACC to improve underwater image quality, using the FHE method with the FHEACC method. The results of the UIQM and ENTROPY metrics obtained the highest values, while UCIQE ranked third. This shows that the image quality improved using the FHEACC combination method is objectively better than that achieved with the HE, AHE, CLAHE, FHE, IBLA, RCP, and UDCP methods, especially in maintaining color balance. This research can introduce a new workflow to improve the quality of underwater images by combining Fuzzy Histogram Equalization and Adaptive Color Correction methods, thereby supporting the optimization of underwater image identification systems in wild environments using computer vision technology.
Co-Authors Abdussalam Abdussalam, Abdussalam Achmad Ridwan Affandy Agus Winarno, Agus Ahmad Zainul Fanani Al zami, Farrikh Al-Fatih, Gilang Fajar Alzami, Farrikh Anshori, Muhammad Izzul Aria Hendrawan, Aria Arry Maulana Syarif, Arry Maulana Asih Rohmani Asih Rohmani, Asih Bastiaans, Jessica Carmelita Budi Harjo Cahaya Jatmoko Candhy Fadhila Arsyad Catur Supriyanto Catur Supriyanto Catur Supriyanto Catur Supriyanto Catur Supriyanto Catur Supriyanto Chaerul Umam Christy Atika Sari D, Ishak Bintang Dalimarta, Fahmy Ferdian Danang Bagus Chandra Prasetiyo Darmawan, Aditya Aqil Denny Senata Dito, Aliffia Putri Doheir, Mohamed Dwi Eko Waluyo Dwi Puji Prabowo, Dwi Puji Dwiza Riana Edi Noersasongko Edi Noersasongko Edi Noersasongko Egia Rosi Subhiyakto, Egia Rosi Ekaprana Wijaya Eko Hari Rachmawanto Elkaf Rahmawan Pramudya Erna Zuni Astuti Fajrian Nur Adnan Fauzi Adi Rafrastara Firman Wahyudi, Firman Fitri Yakub Guruh Fajar Shidik Hamir, Mun Hanny Haryanto Hartojo, James Harun Al Azies Heru Lestiawan Hidayat, Sholeh Hisyam Syarif Husain Husain I Ketut Eddy Purnama Ibnu Utomo Wahyu Mulyono, Ibnu Utomo Irwan, Rhedy Islam, Hussain Md Mehedul Ivan Maulana Jumanto Jumanto, Jumanto Junta Zeniarja Karis Widyatmoko Khafiizh Hastuti Kiat, Ng Poh Kunio Kondo L. Budi Handoko M Arief Soeleman M. Arief Soeleman M. Arif Soeleman Maria Goretti Catur Yuantari Megantara, Rama Aria Mila Sartika, Mila Minghat, Asnul Dahar Bin Moch Arief Soeleman Moch Arief Soeleman Moch Arief Soeleman, Moch Arief Mochamad Hariadi Mochammad Arief Soeleman Muhammad Munsarif Muhammad Naufal, Muhammad Muljono Muljono Nanna Suryana Herman Ningrum, Novita Kurnia Nita Merlina Noor Ageng Setiyanto, Noor Ageng Nur Azise Ocky Saputra, Filmada Panca Hutama Caniago Paramita, Cinantya Pergiwati, Dewi Pramitasari, Ratih Prasetyoningrum, Devi Puji Purwatiningsih, Aris Pujiono Pujiono Purwanto Purwanto Putra, Angga Permana Raden Arief Nugroho Rafsanjani, Muhammad Ivan Rahmatullah, Muhammad Rifqi Fadhlan Ramadhan Rakhmat Sani Ramadhan, Aditya Wahyu ramayanti, ismarita Ricardus Anggi P Ricardus Anggi Pramunendar Rohman, Muhammad Syaifur Ruri Suko Basuki Saputra, Filmada Ocky Saputri, Pungky Nabella Saputro, Wicaksono Agung Saraswati, Galuh Wilujeng Sari Ayu Wulandari Sarker, Md. Kamruzzaman Satriyawibawa, Muhammad Yiko Savicevic, Anamarija Jurcev Senata, Denny Sendi Novianto Shafa, Raihanaldy Ash Shier Nee Saw Sinaga, Daurat Sindhu Rakasiwi Siti Hadiati Nugraini Soeleman, Arief Soeleman, M Arief Soeleman, M. Arief Soeleman, Moch. Arief Soong, Lim Way Sri Winarno Sri Winarno Steven, Alvin Sudibyo, Usman Suharyanto Sukmawati Anggraeni Putri, Sukmawati Anggraeni Sukmono, Indriyo K. Supriyono Asfawi Suryawijaya, Tito Wira Eka Susanto Susanto Tendi Tri Wiyanto, Tendi Tri Tengku Riza Zarzani N Thifaal, Nisrina Salwa Torhino, Rizal Wellia Shinta Sari Wildan Akhya, Malfino Yaacob, Noorayisahbe Mohd Yusianto Rindra Zahrotul Umami, Zahrotul Zainal Arifin Hasibuan