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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 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 JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) 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 Jurnal Pendidikan Islam Jurnal Pengabdian Masyarakat dan Riset Pendidikan IRDH International Journal of Technology, Agriculture and Natural Sciences (IRDH IJTANS) Energy: Jurnal Ilmiah Ilmu-ilmu Teknik

Syaad Patmanthara

Universitas Negeri Malang

Author-ID : 2590732

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Perbedaan Kemampuan Berpikir Kritis dan Hasil Belajar Kognitif Sistem Komputer antara Model CTL dengan Model Examples Non Examples Kurniawan, Singgih Adie; Patmanthara, Syaad; Soraya, Dila Umnia
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 4 No. 2 (2019): November 2019
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Penelitian ini bertujuan untuk mengetahui perbedaan pada kemampuan berpikir kritis dan hasil belajar kognitif mata pelajaran sistem komputer, antara kelas eksperimen menggunakan model contextual teaching and learning dan kelas kontrol menggunakan model examples non examples di SMKN 11 Malang. Penelitian ini merupakan penelitian experimental semu (Quasy Experimental Design) dengan pola posttest only control design. Sampel yang dipilih adalah kelas X TKJ 1 sebagai kelas eksperimen dan X TKJ 4 sebagai kelas kontrol. Rata-rata hasil kemampuan akhir siswa di kedua kelas setelah mendapat perlakuan yaitu, kelas TKJ 1 sebesar 89,16 dan kelas TKJ 4 sebesar 83,90. terdapat selisih rata-rata sebesar 5,26 antara kedua kelas. Hasil kemampuan berpikir kritis pada kelas eksperimen menunjukkan 20% kemampuan sangat tinggi, 10% kemampuan tinggi, 42% kemampuan sedang, 6% kemampuan rendah dan 13% kemampuan sangat rendah. Sedangkan untuk kelas kontrol presentase yang didapat 7% memiliki kemampuan sangat tinggi, 20% kemampuan tinggi, 23% kemampuan sedang, 20% kemampuan rendah dan 30% kemampuan sangat rendah. Hasil uji-t juga menunjukkan nilai 0,002 (dimana nilai 0,002 < 0,05). Maka dapat disimpulkan terdapat perbedaan signifikan kemampuan berpikir kritis dan hasil belajar kognitif antara kelas eksperimen dan kelas kontrol.

Strategic Resource Relationship Model, Adaptability to Environmental Dynamics, Implementation of School-Based Management and Vocational School Competitiveness Jamil, Amidatus Sholihat; Kamdi, Waras; Hadi, Syamsul; Patmanthara, Syaad
JTP - Jurnal Teknologi Pendidikan Vol. 25 No. 3 (2023): Jurnal Teknologi Pendidikan
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat, Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/jtp.v25i3.48677

The aim of this research is to obtain the best relationship model between strategic resources, adaptability to environmental dynamics, and the implementation of school-based management on competitiveness in vocational schools which is thought to have an indirect relationship through existing mediating variables, without ignoring the direct relationship of each variable. This research is included in explanatory research with the statistical analysis technique used, namely Structural Equation Modeling (SEM). The population and sample in this study were 397 public and private vocational school teachers in East Java Province. Research data was collected through the distribution of questionnaires conducted online and offline. The results of hypothesis testing show that: (1) strategic resources have a positive and significant effect on environmental dynamics; (2) strategic resources have a positive and significant effect on the implementation of SBM; (3) adaptability to environmental dynamics has a positive and significant effect on SBM implementation; (4) strategic resources have a positive and significant effect on competitiveness; (5) SBM implementation has a positive and significant effect on competitiveness; (6) environmental dynamics have a positive and significant effect on competitiveness through the implementation of SBM; (7) strategic resources have a positive and significant effect on competitiveness through environmental dynamics and SBM implementation; (8) strategic resources have a positive and significant effect on competitiveness through the implementation of MBS; and (9) strategic resources have a positive and significant effect on the implementation of SBM through environmental dynamics.

AI, Agriculture, and Decolonial Perspectives: Recognizing Local Knowledge for Sustainability Julfikar Mawansyah; Mokh. Sholihul Hadi; Syaad Patmanthara
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.v4i3.7250

This study explores the intersection of Artificial Intelligence (AI), agriculture, and decolonial philosophy, emphasizing the role of local knowledge as the foundation for sustainable agricultural technology in Indonesia. The research investigates how AI can be developed not as a tool of technological domination but as a dialogical partner that recognizes the epistemic value of indigenous wisdom. Using a mixed-method approach, the study combines algorithmic experiments applying lightweight Convolutional Neural Networks (CNN) with Explainable AI (XAI) methods such as SHAP and LIME with participatory interviews involving farmers in Bima District. Empirical findings show that models integrated with localized visualization and community-based interpretability improved user trust by 84% and reduced computational energy by 28% without compromising accuracy. More importantly, the interaction between AI and farmers revealed a form of epistemic integration where algorithmic logic aligns with traditional indicators, such as soil texture, humidity, and seasonal signs known to local farmers. Philosophically, this research asserts that sustainable AI should emerge from ecological and cultural contexts rather than imposing external frameworks. In the decolonial sense, it positions local farmers not as passive users but as active epistemic agents shaping the meaning of technology. Thus, AI becomes not only a technical instrument but a site of ethical and epistemic liberation that reaffirms human responsibility toward knowledge, culture, and the earth.

Abstract Syntax Tree Model for Minimizing False Negative in Semantic Evaluation of Python Fill-in-the-Blank Nurhasan, Usman; Prasetya, Didik Dwi; Patmanthara, Syaad
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.v9i6.11090

This study develops and evaluates an automated assessment model using Abstract Syntax Trees (AST) with a view to overcoming the limitations of string-matching techniques in the assessment of Fill-in-the-Blank (FIB) programming answers. Traditional string-matching techniques have a relatively high False Negative Rate (FNR) of 21.5% within the context of detecting semantic equivalence. The current model uses semantic structural triangulation to ascertain the semantic similarity of student answers. Technical assessment shows that the AST approach markedly reduces the FNR to 4.5%. The model demonstrates high reliability (ϰ = 0.83) with high classification accuracy (F1 Score = 0.966) which attests to its inferential validity. From a pedagogical perspective, system implementation leads to substantial learning gains, evidenced by a large effect size (Cohen’s d = 1.82) and a high normalized gain (Normalized Gain = 0.90). Multiple regression analysis confirms that semantic accuracy is the primary causal factor driving improved student comprehension. Ontologically, while AST is valid as a partial representation, its limitations—particularly tree isomorphism in recursive structures—highlight the need for further exploration of graph isomorphism approaches. Control Flow Graphs (CFG) and Data Flow Graphs (DFG) offer more expressive relational models for capturing control and data dependencies. The model demonstrates functional feasibility with a System Usability Scale (SUS) score of 76.47. Overall, the AST Triangulation Model is validated as pedagogically effective, inferentially robust, and supportive of evaluative transparency. Future research recommends validating the model on more complex tasks and releasing it as open-source to support reproducibility.

Ontology-Based Recommender Systems for E-Learning and Multimedia: A Systematic Literature Review Across Domains Riska, Suastika Yulia; Patmanthara, Syaad; Widiyaningtyas, Triyanna
Indonesian Journal of Instructional Media and Model Vol 7 No 2 (2025): Indonesian Journal of Instructional Media and Model
Publisher : Universitas Veteran Bangun Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32585/ijimm.v7i2.7405

The rapid expansion of digital content across various sectors has led to an overwhelming influx of data, highlighting the need for advanced recommendation systems. Traditional methods such as Collaborative Filtering (CF) and Content-Based Filtering (CBF) face limitations like data sparsity and the Cold Start problem, which affect the accuracy of recommendations. This study explores the use of ontologies in enhancing recommendation systems, aiming to overcome these challenges by providing a semantic framework for better item and user representation. A Systematic Literature Review (SLR) methodology was employed to analyze research from 2021 to 2025, focusing on the application of ontologies in e-commerce, healthcare, education, and employment. The findings demonstrate that ontologies improve recommendation relevance, diversity, and explainability, especially in addressing the Cold Start problem. However, challenges in implementation and interpretation remain. This research contributes to the field by emphasizing the potential of integrating ontologies with Knowledge Graphs (KG) and Graph Neural Networks (GNN) to create hybrid models that enhance the accuracy and transparency of recommendations, guiding future advancements in recommendation systems.

Towards Intelligent Performance Monitoring for Blockchain-Based Learning Systems: A Multi-Class Classification Approach Sulaksono, Aditya Galih; Patmanthara, Syaad; Rosyid, Harits Ar
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1138

This study proposes a multi-class classification framework for monitoring blockchain system performance as a step toward integration within blockchain-based learning management systems (LMS). Reliable performance monitoring is essential because smart contracts in educational settings depend on timely and accurate system responses to ensure valid grading and credential issuance. A dataset of 3,081 transactional logs was generated from simulated blockchain testbed, capturing throughput, latency, block size, and send rate. Throughput values were discretized into seven qualitative categories ranging from “Very Poor” to “Very Good” using quantile-based binning. Preprocessing involved data cleaning, categorical encoding, Z-score normalization, and label encoding to ensure model compatibility. Five algorithms: Logistic Regression, Decision Tree, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) were trained and evaluated using stratified 80–20 partitioning and 5-fold cross-validation with grid search for hyperparameter tuning. Performance metrics included accuracy, macro precision, recall, and F1-score. Random Forest achieved the best results with 91.35% accuracy, 0.910 macro precision, 0.911 recall, and 0.910 F1-score, outperforming other models by handling complex feature interactions and reducing variance. Decision Tree offered strong interpretability (88.32% accuracy), while Logistic Regression (84.97%) and SVM (84.86%) provided stable performance. KNN showed balanced results (87.78%) but incurred high computational costs. The findings demonstrate that multi-class stratification provides more actionable insights than binary methods, supporting low-latency decision-making for smart contract execution in decentralized LMS ecosystems. The novelty of this research lies in applying multi-class classification instead of binary methods, enabling nuanced monitoring. Future work will validate the framework in real blockchain-LMS deployments.

Human Computer Interaction dalam Sistem Pendataan Pasien: Berdasarkan Perspektif Ontologi, Epistemologi, dan Aksiologi Karaman, Jamilah; Patmanthara, Syaad
Reflection Journal Vol. 5 No. 2 (2025): Desember
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/rj.v5i2.3794

Human Computer Interaction (HCI) adalah bidang multi disiplin ilmu yang berfokus pada interaksi antara manusia dan sistem komputer, khususnya dalam sistem informasi kesehatan seperti sistem pendataan pasien. Artikel ini mengkaji HCI dalam konteks sistem pendataan pasien melalui pendekatan filsafat ilmu, yang meliputi 3 pendekatan yakni ontologi, epistemologi, dan aksiologi. Metode yang digunakan yaitu studi pustaka dengan menelaah literatur jurnal nasional dan internasional terkait HCI, sistem informasi kesehatan, dan filsafat ilmu. Hasil kajian menunjukkan bahwa secara ontologi, sistem pendataan pasien terdiri dari entitas pengguna, perangkat keras, perangkat lunak, antarmuka, serta data medis. Secara epistemologi, pengetahuan diperoleh melalui usability testing dan validasi data. Secara aksiologi, HCI memberikan manfaat berupa peningkatan efisiensi layanan, akurasi data, dan perlindungan privasi pasien. Dengan pendekatan filsafat ini, HCI dalam sistem pendataan pasien dipahami sebagai suatu sistem yang tidak hanya teknis, tetapi juga bermakna dan etis. Human-Computer Interaction in Patient Data Management Systems: An Ontological, Epistemological, and Axiological Perspective Human-Computer Interaction (HCI) is a multidisciplinary field focused on the interaction between humans and computer systems, especially in health information systems such as patient data management systems. This paper examines HCI within the context of patient data management systems through a philosophical framework that includes ontology, epistemology, and axiology. The methodology employed is a literature review, analyzing relevant national and international journals related to HCI, health information systems, and the philosophy of science. The findings indicate that, from an ontological perspective, a patient data management system consists of entities such as users, hardware, software, interfaces, and medical data. From an epistemological viewpoint, knowledge is acquired through usability testing and data validation. From an axiological standpoint, HCI brings benefits in terms of enhanced service efficiency, data accuracy, and patient privacy protection. With this philosophical approach, HCI in patient data management systems is understood not only as a technical phenomenon but also as a meaningful, valuable, and ethical system.

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

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

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

Co-Authors A.N. Afandi Achadiyah, Ana Nuril 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 Carolina Sisca Djunaidi Ciptaningrum, Mega Satya Daniar Wahyu Akbar Oktaviando Dendy Dewa Widjaya Putra Dhega Febiharsa Didik Dwi Prasetya Didik Nurhadi Dila Umnia Soraya Djoko Kustono 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 Hanifah, Nida 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 Ikhwan Arif Ilmam, Thirafi Imam Alfianto Indraswari, Martha Devi Isnandar Jayadi, Puguh Joumil Aidil Saifuddin Julfikar Mawansyah Karaman, Jamilah Kartika Candra Kirana Kholiqin, Sabrina Nabila Khusnul Hidayat Kurniawan, Rivan Adi Kurniawan, Singgih Adie Kurubacak, Gulsun Lokapitasari Belluano, Poetri Lestari Luqman Affandi M Ibrahim Ashari M. Djunaidi Ghony M. Zainal Arifin M. Zainal Arifin Mahali, Mahali Marji Marji Maskur Maskur Massitta, Massitta Masyfa, Faiz Hilmawan MAULA, PUTRINDA INAYATUL Meidy, Ria Devita Meidy, Ria Devita Mentari, Febiana Putri Merinda Lestandy 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 Nunung Nurjanah 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 Putri Alivia Nabila R. Mahmud Sugandi Rachman Kurniawan Rachman, Tegar Fatur Rahajeng Kartika Sari Rahmawati, Chusnia Ramadiani, Nanda Resta Rasif Nidaan Khofia Ahmadah Ratnasari, Novia Resti Pranata Putri Ria Devita Meidy Riyanto, Didik Rizal, Muhammad Fatkhur Rokhimatul Wakhidah Sakkinah, Intan Sulistyaningrum Sari, Heni Vidia Sari, Rahajeng Kartika Setyawan Aji Samudra Shofiyah Al Idrus Siti Munawaroh Siti Sendari Slamet Wibawanto Soenar Soekopitojo Sri Farida Utami Sri Sumanti, Endang Suastika Yulia Riska Suci Lestari Sunu Jatmika, Sunu Suparji Suparji Sutapa, Yohanes Gatot Syamsul Hadi Syeh Umar Anggana 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

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