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All Journal Jurnal Ilmu Pendidikan Tekno : Jurnal Teknologi Elektro dan Kejuruan Teknologi dan Kejuruan: Jurnal teknologi, Kejuruan dan Pengajarannya Cakrawala Pendidikan JPTK: Jurnal Pendidikan Teknologi dan Kejuruan ELINVO (Electronics, Informatics, and Vocational Education) Jurnal Pendidikan: Teori, Penelitian, dan Pengembangan JOIN (Jurnal Online Informatika) Jurnal Pendidikan (Teori dan Praktik) JOURNAL OF APPLIED INFORMATICS AND COMPUTING SENTIA 2016 Nazhruna: Jurnal Pendidikan Islam Jurnal Basicedu Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Journal of Computer Science and Informatics Engineering (J-Cosine) Gelar : Jurnal Seni Budaya JTP - Jurnal Teknologi Pendidikan Jurnal Karinov ILKOMNIKA: Journal of Computer Science and Applied Informatics TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Generation Journal Jurnal Teknodik JPP (Jurnal Pendidikan dan Pembelajaran) Discovery : Jurnal Ilmu Pengetahuan Belantika Pendidikan Letters in Information Technology Education (LITE) Indonesian Journal of Instructional Media and Model Jurnal Abdimas Berdaya : Jurnal Pembelajaran, Pemberdayaan dan Pengabdian Masyarakat Didaktika: Jurnal Kependidikan Journal of Applied Data Sciences International Journal of Engineering, Science and Information Technology Journal of Science and Education (JSE) IJORER : International Journal of Recent Educational Research Emerging Information Science and Technology International journal of education and learning Jurnal Integrasi dan Harmoni Inovatif Ilmu-ilmu Sosial Jurnal Basicedu JP (Jurnal Pendidikan) : Teori dan Praktik Jurnal Ilmiah Edutic : Pendidikan dan Informatika Reflection Journal Research and Development in Education (RaDEn) JUSIFOR : Jurnal Sistem Informasi dan Informatika Jurnal Riset Rumpun Agama dan Filsafat Jurnal Inovasi Teknologi dan Edukasi Teknik Journal of Embedded Systems, Security and Intelligent Systems Jurnal Pendidikan Islam IRDH International Journal of Technology, Agriculture and Natural Sciences (IRDH IJTANS)
Syaad Patmanthara
Universitas Negeri Malang
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy 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 Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Ontologi, Aksiologi, dan Epistemologi Energi Baru Terbarukan Terhadap Smart City: Tinjauan Literatur Sistematis Alfarid Hendro Yuwono; Syaad Patmanthara; Aripriharta Aripriharta; Triyanna Widiyaningtyas; Nafi Isbadrianingtyas; M Ibrahim Ashari
Jurnal Riset Rumpun Agama dan Filsafat Vol. 4 No. 3 (2025): Desember: Jurnal Riset Rumpun Agama dan Filsafat
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurrafi.v4i3.7273

Abstract

The development of digital technology and the Internet of Things (IoT) has transformed the paradigm of urban development towards the concept of a smart city based on data and connectivity. This study analyzes the nature of smart cities through three dimensions of the philosophy of science: ontology, epistemology, and axiology. From an ontological perspective, a smart city is understood as a complex entity consisting of physical, digital, social, and ecological systems that interact with each other to create efficient and adaptive urban governance. Epistemologically, knowledge in a smart city is obtained through the process of collecting, processing, and analyzing data from various IoT devices, sensors, and citizen participation, thereby producing new insights that support evidence-based decision-making (data-driven governance). From an axiological perspective, a smart city has ethical values and goals to improve the quality of life of its citizens, strengthen government transparency, maintain environmental sustainability, and promote inclusive social participation. Thus, this study asserts that the development of a smart city is not only technological but also has a philosophical foundation oriented towards a balance between efficiency, humanity, and sustainability.
A hermeneutic inquiry into musical meaning in AI-generated music: a case study of Suno AI’s text-to-music system Ratnasari, Novia; Wibawa, Aji Prasetya; Patmanthara, Syaad
Gelar: Jurnal Seni Budaya Vol. 23 No. 2 (2025)
Publisher : Institut Seni Indonesia Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33153/glr.v23i2.7763

Abstract

This study examines how generative artificial intelligence participates in the creation and interpretation of musical meaning, using Suno AI’s text-to-music system as a focused case. The research explores how machine-generated sound can be understood hermeneutically, particularly how linguistic prompts, probabilistic modeling, and audio generation processes shape meaning, emotion, and musical intention. The study aims to determine the extent to which generative AI functions as an epistemic collaborator rather than a passive tool and how its outputs align with or diverge from human interpretive expectations. Using a digital epistemological hermeneutic framework operationalized through prompt-based observation, semantic interpretation, and comparative listening, the study conducted controlled experiments varying genre, instrument, mood, and tempo. Each output was evaluated in terms of expressive quality, emotional valence, stylistic coherence, and prompt response fidelity. The findings indicate that generative AI constructs musical meaning through representational inference, producing sonic forms that partially reflect the semantic cues embedded in linguistic prompts. Although the system does not exhibit human-like intentionality, its probabilistic structures generate patterns that resonate with human affective and interpretive frameworks, creating a co-creative space where human prompts and machine inference jointly shape musical expression. These insights demonstrate the usefulness of hermeneutics as a methodological lens for understanding AI-mediated creativity and highlight the importance of prompt design, model transparency, and human-machine interpretive dynamics in future computational musicology and creative AI research.
Integrated Kinematic-Dynamic Modeling and Ontology-Based Design of a Two-Link Planar Robotic Manipulator Giri Wahyu Wiriasto; Patmanthara, Syaad; Sendari, Siti; Lestari, Dyah; Iqbal, Muhamad Syamsu
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 9 No 2 (2025): December 2025
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v9i2.695

Abstract

Integration of Social, Organizational, and Technological Factors to Improve the Effectiveness of Environmental Policies in Waste Management in Bima City Sri Sumanti, Endang; Prasetya, Didik Dwi; Patmanthara, Syaad
Emerging Information Science and Technology Vol. 6 No. 2 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v6i2.29171

Abstract

Bima City faces serious challenges in waste management, characterized by low service covera- ge (53.16%), limited processing facilities, and low public awareness and participation. This study aims to comprehensively evaluate the waste management system in Bima City and formulate sustainable strate- gies by integrating social, organizational, and technological factors. The research approach is quantitative with Structural Equation Modeling (SEM) analysis of 200 respondents from the community, sanitation workers, and environmental managers. The conceptual model was developed by adapting the Human–Or- ganization–Technology Fit (HOT-Fit) framework and Sustainability Metrics dimensions that include po- licy, participation, community behavior, and infrastructure technology. The results showed that organizational factors and public policy significantly influenced the effectiveness of waste management (β = 0.36; p < 0.001). Community participation was the dominant factor with a di- rect influence on management effectiveness (β = 0.45; p < 0.001), while community behavior acted as a mediator between technology and system effectiveness (β = 0.32; p < 0.001). The Goodness of Fit value showed a statistically appropriate model (CFI = 0.957; TLI = 0.951; RMSEA = 0.039). This study empha- sized the importance of synergy between policy support, social participation, and technological infrastruc- ture in building a sustainable waste management system.
Extracting Value from Minority Voices: Epistemic Validation of Naive Bayes and SMOTE Models for E-Commerce Review Sentiment Analysis Ibrahim, Firmansyah; Prasetya, Didik Dwi; Patmanthara, Syaad
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 4 (2025): Desember 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v6i4.10275

Abstract

In the e-commerce ecosystem, negative customer reviews, despite often being a numerical minority, represent the most valuable (axiological) business asset for service improvement. However, this value is frequently obscured by the high volume of positive reviews, creating a significant imbalance in the data. This study aims to design and validate a text mining model that is axiologically focused on extracting critical insights from this "minority voice." We applied the Naive Bayes Classifier (NBC) algorithm, augmented with TF-IDF feature weighting, on a dataset of 6,000 reviews from the 'Famous Florist' store. The epistemic challenge of severe data imbalance (5,432 positive vs. 97 negative) was addressed through the methodological intervention of the Synthetic Minority Over-sampling Technique (SMOTE). The model's validity was assessed using 10-Fold Cross-Validation. The epistemic validation results demonstrated the model's validity, achieving an average accuracy of 90%. Crucially, the model achieved a 99% rate for the negative class. This affirms the model's axiological validity: its ability to reliably identify customer complaints (e.g., 'damaged,' 'packaging') and transform raw data into actionable recommendations for improvement.
Paradigma Epistemologis Kompresi Data Teks: Huffman, Arithmetic, dan Neural Language Model Affandi, Luqman; Prasetya, Didik Dwi; Patmanthara, Syaad
JUSIFOR : Jurnal Sistem Informasi dan Informatika Vol 4 No 2 (2025): JUSIFOR - Desember 2025
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/jusifor.v4i2.8384

Abstract

This study explores text data compression as an epistemological paradigm through a comparative analysis of three fundamental approaches: traditional methods (Huffman Coding + LZW), bit-based methods (Arithmetic Coding), and machine learning approaches (Neural Language Models). Using the Project Gutenberg dataset comprising 15,000 classical literary works with a total size of 8.5 GB and 2.1-billion-word tokens, the evaluation is conducted based on compression ratio, execution time, and memory usage. The results reveal fundamental trade-offs among the paradigms. Traditional methods achieve the fastest execution (8.3 seconds/GB, 482 MB/s, 52 MB) with a compression ratio of 3.2:1. Arithmetic coding attains near-optimal performance (99.5% of the Shannon bound) with a compression ratio of 3.8:1. Neural language models yield the highest compression ratio of 4.6:1 but require substantially higher execution time and memory. The epistemological analysis highlights distinct conceptions of information—mechanistic, mathematically optimal, and semantic-aware—and provides a conceptual framework for developing adaptive compression systems.
Integration of Knowledge-Based CNN Model for Breast Cancer Histopathology Image Classification Badri, Fawaidul; Patmanthara, Syaad; Zaeni, Ilham Ari Elbaith
ILKOMNIKA Vol 7 No 3 (2025): Volume 7, Number 3, December 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/ilkomnika.v7i3.801

Abstract

This study examines the integration of a knowledge-based Convolutional Neural Network (CNN) model for breast cancer histopathology image classification through ontological and epistemological perspectives. Ontologically, the research focuses on the digital representation of histopathological breast tissue images as entities representing benign and malignant conditions, establishing a stable and comprehensive mapping of tissue morphological characteristics. Epistemologically, the study employs a deep learning approach using a CNN model to acquire and validate knowledge about cancer cell morphology patterns from image data, constructing robust epistemic claims regarding tissue differentiation. The BreakHis dataset comprises 7,909 images resized to 224×224 pixels that underwent preprocessing normalization and image augmentation to enhance data quality. The CNN model was designed with Adam and SAM optimizers, learning rates of 0.0001 and 0.003, and a three-epoch warm-up phase to maintain training stability. Experimental results achieved training accuracy of 0.8432, testing accuracy of 0.8481, AUC of 0.8318, precision of 0.8124, and recall of 0.8966, demonstrating excellent model performance in recognizing cancer tissue patterns without overfitting. The integration of this knowledge-based CNN model contributes theoretically to the advancement of artificial intelligence and biomedical science, while demonstrating practical relevance as a reliable decision-support system for breast cancer diagnosis.
Epistemological and Axiological Analysis of ResNet18-Based Dysgraphia Classification Kirana, Kartika Candra; Handayani, Anik Nur; Patmanthara, Syaad; Eva, Nur
Generation Journal Vol 10 No 1 (2026): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/gj.v10i1.27419

Abstract

Based on an ontological perspective, there is a gap in feature representation and in binary dysgraphia classification using ResNet18, an area that has not been explored simultaneously. Thus, our contribution is an analysis of research on dysgraphia classification using ResNet18 that employs epistemological and axiological approaches. ResNet18 was chosen as the backbone of the proposed framework because it has shortcut connections that can degrade residues into useless features. As a representation of new knowledge, ResNet18 was pre-trained on ImageNet. Classification was tested on challenging word assignments, comprising 145 dysgraphia images and 188 non-dysgraphia images. Epoch trials were conducted to find the best architecture. The results showed that ResNet18 at epoch 10 achieved the best performance in binary classification, with a recall of up to 93.55%. This indicates that ResNet18 is sensitive to recognizing dysgraphia classes. Challenges outlined in this study serve as a foundation for further research.
Development of a CNN-Based Knowledge System for Rupiah Currency Authenticity Detection and Nominal Classification Romadhon, Ahmad Sahru; Patmanthara, Syaad; Handayani, Anik Nur
Generation Journal Vol 10 No 1 (2026): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/gj.v10i1.27464

Abstract

The circulation of counterfeit money in Indonesia inflicts substantial losses on the public and financial institutions. Manual verification of money is inefficient and error-prone, especially during high transaction volumes, because counterfeit bills exhibit physical characteristics nearly identical to genuine currency. To uncover counterfeit notes, an ultraviolet lamp exposes invisible ink. This research employs the Convolutional Neural Network (CNN) to detect authenticity and classify Indonesian rupiah banknotes. The CNN is trained using images of authentic banknotes captured with a camera and ultraviolet light across various denominations. The system stores the images and trains the model to identify authenticity and denomination features. Experimental results demonstrate that the proposed approach achieves high classification accuracy in distinguishing genuine and counterfeit Rupiah banknotes, as well as in recognising their respective denominations. The testing phase introduces real notes exposed to ultraviolet light, producing images that reveal invisible ink patterns. The authenticity detection achieved a 100% success rate, while the denomination recognition rates were 70% for Rp. 5,000 notes, 80% for Rp. 10,000 and Rp. 20,000 notes, and 90% for Rp. 50,000 and Rp. 100,000 notes. The system’s overall success rate is 82%.
The Effect of Project-Based Learning in the IPAS Project Subject on Students’ Employability Skills at State Vocational High School 1 Pasuruan Taufik Hidayat; Tuwoso Tuwoso; Syaad Patmanthara
Didaktika: Jurnal Kependidikan Vol. 14 No. 4 Nopember (2025): Didaktika Jurnal Kependidikan
Publisher : South Sulawesi Education Development (SSED)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58230/27454312.3308

Abstract

This study investigates the effect of Project-Based Learning (PjBL) in the IPAS Project Subject on the employability skills of students at State Vocational High School 1 Pasuruan. The research was conducted to address the growing demand for vocational graduates who possess not only technical competencies but also essential employability skills such as communication, teamwork, problem-solving, critical thinking, adaptability, responsibility, and time management. A quasi-experimental one-group pre-test–post-test design was employed, involving 30 students selected through purposive sampling. Data were collected using an employability skills questionnaire, observation sheets, and a project assessment rubric. The results revealed a significant improvement in students’ employability skills after the implementation of PjBL. The mean pre-test score of 66.47, which indicated a moderate level of employability skills, increased to 82.63 in the post-test, placing students in the high category. Statistical analysis using a paired-sample t-test showed a significant difference between the pre-test and post-test scores (t = –14.872, p < 0.05), and the effect size calculation (Cohen’s d = 2.86) indicated a very large impact of the intervention. These findings demonstrate that Project-Based Learning is an effective pedagogical approach for enhancing employability skills in vocational education, particularly when integrated into interdisciplinary subjects such as IPAS within the Kurikulum Merdeka framework. Despite limitations related to the absence of a control group, the small sample size, and the short duration of implementation, this study provides empirical evidence supporting the integration of PjBL as a strategic method to strengthen students’ readiness for the world of work.
Co-Authors Achmad Imam Agung Aditya Galih Sulaksono, Aditya Galih Agung Bella Putra Utama Ahmad Sahru Romadhon Aji Prasetya Wibawa Al Mukafi, Muhammad Hamdan Alfarid Hendro Yuwono Amidatus Sholihat jamil Amrullah, Ahmad Khakim Angga Achmad Cholid Anik Nur Handayani Anwar, Akhmad Syaiful Arie Wardhono Aripriharta - Arizia Aulia Aziiza Arsyillah, Nazhiroh Tahta Asfani, Khoirudin Ashar, Muhammad Ashar, Muhammad Asih Setiani Aya Sofia Mufti Ayuningtyas Kurniawati Azhar Ahmad Smaragdina Benti Gandisa Bramastya, Rista Daniar Wahyu Akbar Oktaviando Dendy Dewa Widjaya Putra Dhega Febiharsa Didik Dwi Prasetya Didik Nurhadi Dila Umnia Soraya Djoko Kustono Djunaidi Ghany Dyah Lestari Eddy Sutadji Eddy Triswanto Setyoadi Eddy Triswanto Setyoadi Ega Putriatama Eko Setiawan Eko Setiawan Ekohariadi Ekohariadi Elfia Najib Kholifiatin Eva, Nur Evania Kurniawati Fachrul Kurniawan Fadli Hidayat, M. Noer Fahmi Efendi Yusuf Fandi Akhmad Kurniawan Fatmawati, Hefi Fawaidul Badri Ferdiansyah, Dodik Septian Fikha Rizky Aullia Firman Syahputra, Yohanes Dhimas Giri Wahyu Wiriasto Gülsün Kurubacak Hakkun Elmunsyah Hanna Zakiyya Hari Putranto Harits Ar Rosyid Harmanto Harmanto Hartarto Junaedi Hary Suswanto Hermansyah, Winda Adelia Heru Wahyu Herwanto Hidayat, Manik I Made Sudana I Made Wirawan Ibrahim, Firmansyah Ikhwan Arif Ilmam, Thirafi Indraswari, Martha Devi Isnandar Jayadi, Puguh Joumil Aidil Saifuddin Julfikar Mawansyah Karaman, Jamilah Kartika Candra Kirana Kholiqin, Sabrina Nabila Kurniawan, Rivan Adi Kurniawan, Singgih Adie Kurubacak, Gulsun Lokapitasari Belluano, Poetri Lestari Luqman Affandi M Ibrahim Ashari M. Zainal Arifin M. Zainal Arifin Mahali, Mahali Marji Marji Maskur Maskur MAULA, PUTRINDA INAYATUL Meidy, Ria Devita Meidy, Ria Devita Mentari, Febiana Putri Moh. Afifullah Mokh Sholihul Hadi Mubarok, Sulton Muhamad Syamsu Iqbal Muhammad Auva Romadhon Muhammad Hamdan Al Mukafi Muhammad Hudan Rahmat Mukhamad Angga Gumilang Muladi Nafi Isbadrianingtyas Naurah Septi Anggraini Nia Arlika Nidhom, Ahmad Mursyidun Ningrum, Gres Dyah Kusuma Nur Aini Susanti Nur Hidayat, Wahyu Nur Hikmah Nurul Hidayati Odhitya Desta Oki Dwi Yuliana Perdana Putra, Muhammad Ricky Prasetyo, Wiji Dwi Prayoga, Adie Purnomo, Purnomo R. Mahmud Sugandi Rahajeng Kartika Sari Rahmawati, Chusnia Ramadiani, Nanda Resta Ratnasari, Novia Resti Pranata Putri Ria Devita Meidy Rizal, Muhammad Fatkhur Rokhimatul Wakhidah Sakkinah, Intan Sulistyaningrum Sari, Rahajeng Kartika Shofiyah Al Idrus Siti Munawaroh Siti Sendari Slamet Wibawanto Soenar Soekopitojo Sri Sumanti, Endang Suastika Yulia Riska Suci Lestari Sunu Jatmika, Sunu Suparji Suparji Sutapa, Yohanes Gatot Syamsul Hadi Taufik Hidayat Titasari Rahmawati Tiya Nurul Khusna Tri Atmadji Sutikno Tri Wrahatnolo Triyana Widiyaningtyas Triyanna Widiyaningtyas Triyanna Widiyaningtyas Tuwoso Usman Nurhasan Wahyu Sakti Gunawan Irianto Waras Waras Yuli Sutoto Nugroho Yuliana, Oki Dwi Yuniardi, Gigih Dwi Yussi Anggraini Zaeni, Ilham Ari Elbaith Zulfikar, Nizam Muchammad