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All Journal J@TI (TEKNIK INDUSTRI) Jurnal Ilmiah Teknologi dan Rekayasa Jurnal Ilmu Perpustakaan Techno.Com: Jurnal Teknologi Informasi MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Forum Ilmu Sosial Jurnal Adabiya Edulib Lentera Pustaka Jurnal Kajian Informasi & Perpustakaan JIPI (Jurnal Ilmu Perpustakaan dan Informasi) Jurnal Tamaddun Populis : Jurnal Sosial dan Humaniora Publication Library and Information Science Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Informatika Jurnal Khatulistiwa Informatika HIGIENE: Jurnal Kesehatan Lingkungan JBMP (Jurnal Bisnis, Manajemen dan Perbankan) Jurnal Pilar Nusa Mandiri Jurnal Penelitian Pendidikan IPA (JPPIPA) JURNAL YAQZHAN: Analisis Filsafat, Agama dan Kemanusiaan Indonesian Journal of Artificial Intelligence and Data Mining JRST (Jurnal Riset Sains dan Teknologi) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Management and Economics Journal (MEC-J) Jurnal Manajemen Kesehatan Yayasan RS.Dr. Soetomo Angkasa: Jurnal Ilmiah Bidang Teknologi Martabe : Jurnal Pengabdian Kepada Masyarakat International Journal of Community Service Learning JURNAL GOVERNANSI Cakrawala: Jurnal Litbang Kebijakan Tibanndaru : Jurnal Ilmu Perpustakaan dan Informasi JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Transparansi Jurnal Ilmiah Ilmu Administrasi Jurnal Kesehatan Medical Technology and Public Health Journal Applied Technology and Computing Science Journal Journal of Information Systems and Informatics Dinasti International Journal of Education Management and Social Science Journal of Economics, Business, and Government Challenges MUKADIMAH: Jurnal Pendidikan, Sejarah, dan Ilmu-ilmu Sosial Jurnal Informasi dan Teknologi Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jatilima : Jurnal Multimedia Dan Teknologi Informasi Responsive: Jurnal Pemikiran dan Penelitian Administrasi, Sosial, Humaniora dan Kebijakan Publik Bubungan Tinggi: Jurnal Pengabdian Masyarakat J-3P (Jurnal Pembangunan Pemberdayaan Pemerintahan) Info Bibliotheca: Jurnal perpustakaan dan ilmu Informasi Jurnal Penelitian Pendidikan, Psikologi Dan Kesehatan (J-P3K) Journal of Computer Networks, Architecture and High Performance Computing Unilib: Jurnal Perpustakaan Jurnal Teknik Informatika (JUTIF) Jurnal Pemerintahan dan Kebijakan (JPK) Dialogue: Jurnal Ilmu Administrasi Publik BIOLOVA Journal La Multiapp Journal of Technology and Informatics (JoTI) International Journal of Social Science, Educational, Economics, Agriculture Research, and Technology (IJSET) Az-Zahra: Journal of Gender and Family Studies Media Pustakawan Pustaka Karya : Jurnal Ilmiah Ilmu Perpustakaan dan Informasi Bidik : Jurnal Pengabdian kepada Masyarakat Journal of Law, Poliitic and Humanities Malcom: Indonesian Journal of Machine Learning and Computer Science Research and Development in Education (RaDEn) MIMBAR INTEGRITAS Journal of Governance and Social Policy Eduvest - Journal of Universal Studies SATIN - Sains dan Teknologi Informasi Journal of Economics and Management Scienties Riwayat: Educational Journal of History and Humanities (Journal of Environmental Sustainability Management) Indonesian Governance Journal : Kajian Politik-Pemerintahan Jurnal Wacana Kinerja: Kajian Praktis-Akademis Kinerja dan Administrasi Pelayanan Publik Al Maktabah Jurnal kajian Ilmu dan Perpustakaan Jurnal Informatika TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Imam Yuadi
Departemen Ilmu Informasi Dan Perpustakaan, Fakultas Ilmu Sosial Dan Ilmu Politik, Universitas Airlangga
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Other

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Classification of Roronoa Zoro Anime, Cosplay, and Action Figure Images Using VGG16 and Inception V3 with Logistic Regression and Support Vector Machine to Improve Popular Culture Object Recognition Noor Rizki, Denaldy Oktavian; Yuadi, Imam
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 3 (2026): JUTIF Volume 7, Number 3, June 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.3.5516

Abstract

The diversity of visual representations of anime characters across anime scenes, cosplay photographs, and action figure images poses challenges for automated image classification due to variations in pose, lighting, background, and visual style. This study aims to develop a robust image classification system for the character Roronoa Zoro using deep learning–based feature extraction combined with classical classification algorithms. The method employs VGG16 and Inception V3 as feature extractors, followed by classification using Logistic Regression and Support Vector Machine. The dataset comprises three classes (anime, cosplay, and action figure), processed through image resizing, normalization, and data augmentation. Performance was evaluated using accuracy, F1-score, Area Under Curve (AUC), Matthews Correlation Coefficient (MCC), confusion matrix, silhouette plot, and multidimensional scaling. The experimental results show that Inception V3 combined with Logistic Regression achieved the best performance, with an AUC of 0.993, accuracy of 95.7%, F1-score of 0.957, and MCC of 0.935, outperforming VGG16 with Logistic Regression, which achieved 91.7% accuracy and an AUC of 0.986. Visualization-based evaluation indicates that Inception V3 produces more separable feature representations, particularly in distinguishing cosplay images from anime and action figure categories. This research demonstrates the effectiveness of multi-model feature extraction and classification for improving recognition performance in character-based image classification tasks and contributes empirically to the application of hybrid deep feature–machine learning approaches in computer vision.
Cyberloafing Analytics: Predicting Causes Using Machine Learning Models Gilang Ferdiansah; Imam Yuadi
JRST (Jurnal Riset Sains dan Teknologi) Volume 10 No. 1, March 2026: JRST
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/jrst.v10i1.25997

Abstract

Cyberloafing refers to the practice of employees utilizing internet access for non-job-related activities during work hours. Cyberloafing poses a dilemma for organizations, as it is deemed aberrant conduct that might impact overall performance. Consequently, organizations must ascertain the determinants of cyberloafing. This study seeks to identify a suitable predictive model for the determinants of cyberloafing behavior in the workplace using a machine learning methodology. The employed methodology utilizes the conventional data mining cycle, namely the Cross-Industry Standard Process for Data Mining (CRISP-DM), with Orange Data Mining as the application tool. The findings indicate that Logistic Regression is the most effective model for forecasting cyberloafing. Logistic Regression yields performance scores of 90.5% Precision and 88.9% Recall. Conversely, the Naïve Bayes model had the lowest metrics, with a Precision of 64.8% and a Recall of 51.9%. This study serves as a reference demonstrating that Logistic Regression effectively predicts cyberloafing. This study enables firms to examine the factors contributing to cyberloafing, facilitating the development of policies aimed at mitigating its adverse effects.
Device-Based Majapahit Inscription Classification with Multi-Filter Enhancement Muhammad Rafi Raihan; Imam Yuadi
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 04 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i04.1792

Abstract

The preservation of cultural heritage through digitalization has become increasingly essential in modern archaeological and information technology research. This study focuses on classifying Majapahit inscription images based on the recording device using machine learning approaches enhanced by multiple image filtering techniques. A dataset comprising seven inscriptions photographed with seven different devices was used to evaluate the performance of three classification models: Logistic Regression, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN). Four preprocessing filters Grayscale, Sobel, Histogram Equalization, and Canny Edge Detection were applied to assess their effects on model accuracy. The results revealed that the SVM consistently achieved the highest accuracy and robustness, particularly under Sobel and Histogram Equalization filters, confirming its superior ability to capture discriminative texture and edge-based features. In contrast, KNN showed unstable results due to its sensitivity to noise and intensity variations, while Logistic Regression performed moderately well in linearly separable data conditions. Paired t-test analysis further validated that SVM’s performance advantage was statistically significant. These findings highlight that edge-preserving preprocessing techniques can substantially enhance the accuracy of device-based image classification and provide a computational framework that supports digital preservation efforts in cultural heritage research.
Multi-Device Image Dataset With Manual And Python-Based Augmentations For Cross-Device Robustness In Image Classification Research Erika Putri; Imam Yuadi
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 04 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i04.1887

Abstract

This study presents a multi-device image collection and a reproducible VSCode/Python pipeline for analyzing image classification and the effects of data augmentation under real hardware variation. Images were captured at the Galeri Inovasi Institut Teknologi Sepuluh Nopember (GRITS) using four devices Infinix Note 4, LG G6, Samsung S23+, and Xiaomi Pad 6s Pro with 31 images per device. We applied manual and Python-based augmentations (rotation, flips, brightness, sharpening, contrast) and organized outputs by device and augmentation type for controlled comparisons. Using stratified 80:20 splits, we evaluated Logistic Regression (LR), SVM (RBF), and KNN. Results: LR reached accuracy 0.90 (macro-F1 0.88; weighted-F1 0.90), SVM 0.89 (macro-F1 0.88; weighted-F1 0.89), and KNN 0.67 (macro-F1 0.65; weighted-F1 0.68). Augmentation enhanced robustness and cross-device generalization, though Xiaomi Pad 6s Pro remained the most challenging class, indicating a persistent device-specific shift. The dataset and scripts provide a transparent, baseline-ready testbed for research on image classification, cross-device variability, and the impact of augmentation.
IMPLEMENTATION OF MACHINE LEARNING IN IMPROVING WEBSITE USER EXPERIENCE AND SATISFACTION Shiefti Dyah Alyusi; Imam Yuadi
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 1 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i1.7439

Abstract

This research aims to analyze user satisfaction in accessing the Airlangga University library website through the application of machine learning algorithms. The benefit of this research is that it provides insight into improving the quality of digital library services based on data-based analysis. The methods used include user surveys, data preprocessing, and application of the Orange Data Mining with models Support Vector Machine (SVM) and K-Nearest Neighbor (kNN) algorithms to classify user satisfaction levels, as well as comparing the results of the two models. The results show that the SVM model is able to achieve a Recall accuracy of 0.587 in identifying user satisfaction, but the precision metric is greater in SVM and the AUC is greater in kNN so it still requires optimization. This research concludes that the application of machine learning, especially SVM, can be an effective tool for improving user experience and providing more precise recommendations for improving library services.
MEMBANGUN KESADARAN TENTANG POTENSI TANAMAN OBAT LOKAL DI MASYARAKAT PEDESAAN: PENDEKATAN ETNO WELLNES Imam Yuadi; Yuniawan Heru Santoso; Lucy Dyah Hendrawati; Nisak Ummi Nazikhah
MIMBAR INTEGRITAS : Jurnal Pengabdian Vol 4 No 1 (2025): JANUARI 2025
Publisher : Biro Administrasi dan Akademik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36841/mimbarintegritas.v4i1.5828

Abstract

Degradasi pengetahuan tradisional tentang tanaman obat di masyarakat pedesaan menimbulkan tantangan signifikan terhadap konservasi keanekaragaman hayati, pelestarian budaya, dan kemandirian dalam perawatan kesehatan. Banyak penduduk pedesaan kurang menyadari manfaat ekonomi, ekologi, dan kesehatan dari tanaman obat lokal, yang memperburuk ketergantungan mereka pada sistem perawatan kesehatan eksternal. Penelitian ini bertujuan untuk mengeksplorasi potensi tanaman obat di Desa Ngadiwono, Jawa Timur, melalui pendekatan etnowellness yang memadukan pengetahuan tradisional dengan praktik kesehatan holistik modern. Penelitian ini menggunakan metode kualitatif, termasuk wawancara mendalam, observasi partisipan, dan diskusi kelompok terfokus, untuk mendokumentasikan perspektif masyarakat dan mengidentifikasi strategi untuk mengembangkan wisata etnowellness. Hasilnya menunjukkan peningkatan kesadaran publik tentang nilai tanaman obat dan meningkatnya minat untuk memanfaatkan sumber daya ini untuk pariwisata dan pembangunan ekonomi. Kebaruan penelitian ini terletak pada penerapan kerangka etnowellness untuk memberdayakan masyarakat pedesaan, menggabungkan pelestarian budaya dengan keberlanjutan ekonomi. Temuan ini menyoroti pentingnya pendidikan partisipatif dan upaya kolaboratif dalam mempromosikan pembangunan pedesaan yang berkelanjutan.
Co-Authors AA Sudharmawan, AA Achmad Djunawan Aditya Cahya Saputra Albigaeri, Syahruly Nizar Alifka Cellina Velby Anastasya, Diva Berta Andini, Aulia Rizqi Anggraini, Pramudya Galuh Suci Ardian Mohib Artha Rachma Widiastuti Arum Karisma Nadya Lashita Azmi, Muhammad Izharul Baihaqie, Owen Berliani, Kezia Putri Bondan Ari Wijaya Cahyani, Retno Tri Christia, Tifani Dewi Chyntia Shafa Condro Rahino Mustikaning Pawestri Dama Putri, Kania Dea Roseliana Putri Dewanty, Alifia Kaltsum Dwiky Rahardian Endang Gunarti Enny Mar’atus Sholihah Erika Putri Erika Putri Fadilia Rinarwastu Fadilia Rinarwastu, Fadilia Fairus Faqih Febri Ari Wicaksono Febriano, Rizki Dwi Ferdiansah, Gilang Fitri Mutia, Fitri Gilang Ferdiansah Gunarti, Endang Halim, Yunus Abdul Handari Niken Anggraini Hapsari, Ratih Addina Hardevianty, Melissa Yunda Hary Supriyatno Hasna, Dhia Alifia Izdihar Hendro Margono Ira Puspitasari Ira Puspitasari Ira Puspitasari Irvan Zidny Ismi Choirunnisa Prihatini Kartika Sari, Della Kezia Rahmawati Santosa Koko Srimulyo Lathifah, Lathifah Lestari, Santi Dwi Desy Lifindra, Stevanie Aurelia Lucy Dyah Hendrawati M Kafi Maulana M. Fariz Fadillah Mardianto Mahardika, Synthia Amelia Putri Marsaa Salsabiila Martina Fitria Wulandari Maulidah, Nofiyah Mayasari, Sentri Indah Melati Purba Bestari, Melati Purba Mochammad Edris Effendi Muhammad Rafi Raihan Muhammad Rafi Raihan Muthia Andriana Putri Nabilla Salsabil Damayanti Zahraa Nainunis, Mas Akhmad Nawwaf Faruq Adina Putra Niken Ayu Pratiwi, Bertha Nisak Ummi Nazikhah Noor Rizki, Denaldy Oktavian Novia, Asradiani Noviana Wahyu Basuki Nur Muhammad, Rizqi Nurahman, Yeni Fitria Nurul Firdausy Palupi, Inggrid Nindia Aprila Parenda Rizkya Permata Pradhana, Andrea Thrisiawan Prasetya Triputra Nugraha Prasetyo Yuwinanto, Helmy Prasyesti Kurniasari, Meinia Purba, Trie Dinda Maharani Purwaningtyas, Aris Putra, Dwi Permana Putri Kinanti, Novrianti Putri, Selviana Azzira Ragil Tri Atmi, Ragil Tri Rahmadani, Sinta Raihanzaki, Raka Gading Ratih Addina Hapsari Rosiana, Lidya Rosyani, Widha Sabayu, Brian Sabrina Hartianingrum, Hikmah Sabrina Nur Amalia Safina Innaf Mia Ardelia Salsabiila, Marsaa Salsabila, Chyntia Shafa Sari, Tri Kartika Setiadi, Yusuf Sherly Deasy Anjuwita Gultom Sheva Alana Brilianty Shiefti Dyah Alyusi Sinta Rahmadani Siswahyudianto Soesantari, Tri Sonia Tikamidia Sugihartati, Rahma Suhada, Hofur Sukma Sufryanto Tikamidia, Sonia Toetik Koesbardiati Tri Hadi Wicaksono Triandari, Ayu Ullin Nihaya Unas, Frisca Maria Vilosa, Bias Vivia Adriyanti, Elvetta Wardani, Hesti Ari Wettebossy, Anita Elizabeth Wildan Habibi Yuniawan Heru Santoso Yusi Dyah Patriani Yuwinanto, Helmy Prasetyo