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All Journal Teknotan: Jurnal Industri Teknologi Pertanian Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Ilmiah Kursor Jurnal Teknologi Informasi dan Ilmu Komputer JURNAL KESEHATAN LINGKUNGAN (Journal of Environmental Health) Edu Komputika Journal Jurnal Teknologi dan Sistem Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Teknologi Informasi dan Multimedia Jurnal Eduscience (JES) Jurnal Abdi Insani Jurnal Bumigora Information Technology (BITe) Journal of Applied Data Sciences Journal of Community Development Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Bakti Sekawan : Jurnal Pengabdian Masyarakat Paradharma: Jurnal Aplikasi IPTEK Jurnal INFOTEL Edu Komputika Journal International Journal Research on Metaverse Indenesian Journal of Tropical Biology Indenesian Journal of Tropical Biology Journal of Biology, Environment, and Edu-Tourism Jurnal Elektronika dan Telekomunikasi
Syahroni Hidayat
Universitas Negeri Semarang
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Implementasi SMARCOS: Smart Water Conditioning System Berbasis Web-IoT di Balai Benih Ikan Kecamatan Mijen Semarang Anan Nugroho; Mona Subagja; Syahroni Hidayat; Agung Budiwirawan; Ledi Diyanasari; Jhonatur Stheven Simanjuntak; Tri Agus Wahyudi; Akmal Fikri
Journal of Community Development Vol. 6 No. 1 (2025): August
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/comdev.v6i1.1459

Abstract

Effective water quality management is crucial for fish hatcheries to ensure survival and productivity. At the Fish Hatchery Center (BBI) Cangkiran Mijen, water quality monitoring is still conducted manually, leading to unstable pond conditions. To improve monitoring efficiency, SMARCOS (Smart Water Conditioning System) was developed as a Web-IoT-based system for automated monitoring of water parameters such as pH, oxygen, and temperature. The program involved pond data collection, expert consultation, system design, testing, implementation, and partner training. Evaluation was conducted through satisfaction surveys and system performance monitoring. Results showed that SMARCOS effectively corrected water quality parameters automatically, enhanced monitoring efficiency, and provided easy access to information via an IoT-based website. Surveys indicated that partners were satisfied with the system’s usability. The adoption of IoT for water quality monitoring significantly improved the efficiency and accuracy of hatchery pond management. Training sessions also increased partner understanding of IoT technology. The success of SMARCOS demonstrates that IoT can be an innovative solution for fisheries modernization, with potential replication in other hatcheries to enhance productivity and efficiency in aquaculture.
Acoustic Analysis on Cleft Lip Speech Signal Sitti Agripina Alodia Yusuf; Nani Sulistianingsih; Muhammad Imam Dinata; Syahroni Hidayat; Joelianto Darmawan
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 4 (2025): November
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i4.766

Abstract

Cleft conditions significantly disrupt phonetic articulation, leading to hypernasality and irregular resonance characteristics. In this study, the formant analysis of normal and cleft speech is presented, with the aim of investigating acoustic differences in formant frequencies between cleft and normal speech using real-word utterances, focusing on the articulation of plosive consonants and resonance variability.  The dataset consisted of 280 speech signals (140 cleft and 140 normal) uttering word /paku/. The speech signals were resampled to 16kHz and the silence in the speech was removed, next stage was followed by extracting the first three formants using the Burg algorithm. Statistical analysis revealed that the value of F1 and F2 in cleft speech were higher, alongside greater variability in formant distribution. Further analysis of plosive articulation highlighted irregular formant transition in cleft speech, indicating compromised intraoral pressure control. Additionally, a moderate negative correlation (r = -0.423, p<0.001) between F1 and F3 suggests a spectral pattern indicative of hypernasality. This finding underscores the potential of formant-based acoustic features as objective markers for early clinical assessment and provides a foundation for the development of diagnostic models in cleft speech research.
Assessing Generative AI with Context-Augmented Zero-Shot Prompting for HOTS Question Generation Aligned with Bloom’s Taxonomy Saiful Ridlo; Ahmad Sehabuddin; Syahroni Hidayat; Taofan Ali Achmadi; Uswatun Hasanah; Indah Indi Afifah; Haikal Abror
Edu Komputika Journal Vol. 12 No. 2 (2025): Edu Komputika Journal
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/edukom.v12i2.34437

Abstract

This study investigates the use of HOTS-GenAI, a generative AI system employing context-augmented zero-shot prompting, to automatically generate multiple-choice questions aligned with higher-order thinking skills (HOTS) in Bloom’s taxonomy.  A dataset of 200 items for vocational high schools was validated by three experts. The ground truth data demonstrated good quality with an inter-rater reliability of 0.75 (Gregory’s Index). System performance across analysis (C4), evaluation (C5), and creation (C6) levels was evaluated using Content Validity Index (CVI), gap analysis, and confusion-matrix-based metrics. The findings revealed that HOTS-GenAI performed relatively well at the analytical level, where 70% of items met the HOTS threshold, supported by higher expert consensus. However, only 10% of items achieved the threshold for evaluation, and none for creation. CVI results indicated moderate validity overall, with stronger agreement for C4 than for C5 or C6. Confusion matrix analysis further confirmed this imbalance: accuracy and F1-scores were highest for analysis items but dropped sharply for evaluation and creation, where recall and precision were near zero. These results suggest that while HOTS-GenAI has potential in generating analytical questions, its capacity to model evaluative and creative tasks remains underdeveloped. Future research should involve larger datasets, refined prompt design, and more operational rubrics to enhance both validity and reliability in AI-generated HOTS assessments.
THE EFFECTIVENESS OF VIRTUAL REALITY IN VOCATIONAL EDUCATION FOR FASHION DESIGN AND PRODUCTION Irmayanti Irmayanti; Syahroni Hidayat; Heri Tri Luqman Budisantoso; Ahmad Mustamil Khoiron; Taofan Ali Achmadi
JURNAL EDUSCIENCE Vol 13, No 2 (2026): Jurnal Eduscience (JES), (Authors from Malaysia and Indonesia)
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jes.v13i2.8267

Abstract

Purpose – The fashion industry must master the practical skills needed today to employ immersive technology like VR in Vocational Education and Training. Due to the cost and hazard of hands-on instruction, Indonesian vocational high schools have a skill gap. In order to deal with this problem, this study talks about the real-life outcomes of "Fashion Tech Edu-VR," an immersive learning tool that fits perfectly with the Indonesian national curriculum.Methodology – This study employs a quasi-experimental research approach with a pre-test and post-test Control Group Design. The research subjects consist of 90 grade XI (Phase F) students from the Fashion Design and Production expertise program at a Vocational High School (SMK) in Semarang City. The data collection techniques used were threefold: tests, observation, and questionnaires. To test the hypotheses in this study, a t-test (paired sample t-test) was utilized with the assistance of IBM SPSS Statistics 26, comparing the post-test scores between the control group and the experimental group.Findings – The findings show a statistically significant difference in learning outcomes between the control and experimental classes (t = -27.935). Student engagement in the control group was 3.31, compared to 4.62 in the experimental class after the Fashion Tech Edu-VR intervention. This study found that students who used 'Fashion Tech Edu-VR' achieved significantly higher learning gains compared to the control group. The platform also received excellent usability ratings and fostered much higher levels of student engagement, confirming its effectiveness as an educational tool.Contribution – The study concludes that "Fashion Tech Edu-VR" is a useful educational tool that solves real-world training problems and is a very effective teaching example
CVI-Validated Indo-Transformer Framework for Intelligent Cooperative Supervision Syahroni Hidayat; Afriani Fajar Navissaturrisqi; Feddy Setio Pribadi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 4 (2026): August 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i4.7606

Abstract

Cooperative supervision reports contain complex narrative structures and overlapping administrative terminology, complicating automatic classification into governance, risk profile, financial performance, and capital adequacy. Reliable automation is particularly important for accelerating the analysis of supervisory findings while addressing limited labeled data and imbalanced categories. This study aimed to develop and externally evaluate a text-classification framework combining quantitatively validated Generative Artificial Intelligence (GenAI) labeling with conventional and Transformer-based models. Data comprised 294 preprocessed sentences collected from the Department of Cooperatives, Small and Medium Enterprises, Industry, and Trade of Semarang Regency during 2023–2025. Few-shot annotations were generated using ChatGPT, Gemini, Perplexity, and DeepSeek, and three-model combinations were evaluated using the Content Validity Index (CVI); majority voting from the best combination established ground truth. TF-IDF with Logistic Regression and Support Vector Machine served as baselines, whereas IndoBERT and IndoRoBERTa represented contextual models. Performance was assessed through stratified five-fold cross-validation and external testing on 58 unseen sentences. ChatGPT–Gemini–Perplexity achieved the highest Scale-Level CVI of 0.898. IndoBERT obtained the best cross-validated F1-score of 0.9099, exceeding IndoRoBERTa (0.8217), Logistic Regression (0.8004), and SVM (0.7863). On unseen data, IndoBERT retained an F1-score of 0.862, compared with 0.759 for IndoRoBERTa. These findings demonstrate that CVI-validated ensemble GenAI can construct consistent labels for low-resource administrative texts and that IndoBERT provides the strongest and most stable generalization for cooperative supervision classification. The framework offers a practical basis for scalable annotation and reliable automated support for evidence-based supervisory decision-making.
Co-Authors Abdulloh Abdulloh Abdurahim, Abdurahim Adam Bachtiar Maulachela Afriani Fajar Navissaturrisqi Agung Budiwirawan Agus Ardiyanto Ahmad Sehabuddin Ahmad Zuli Amrullah Ahmat Adil Akbar Juliansyah Akmal Fikri Amrullah Anan Nugroho Anan Nugroho Ananda, Briska Putra Andi Sofyan Anas Ansar Ansar Ardiansyah, Muhammad Irfan Astri Iga Siska Ayu, Hanifah Baroroh, Luluk Taufiqul Budi Sunarko Budiarto, Jian Danang Tejo Kumoro Danang Tejo Kumoro Dian Syafitri Chani Saputri Esa Apriaskar Febry Putra Rochim Feddy Setio Pribadi Feddy Setio Pribadi Habib Ratu Perwira Negara Haikal Abror Haikal Abror Hakiki, Muhammad Khikam Hanif Ardhiansyah Hanif Hidayat Heri Tri luqman Budisantoso Ida Ayu Widhiantari Indah Indi Afifah Intan Ermawati Irmayanti Irmayanti Ismarmiaty Ismarmiaty, Ismarmiaty Jhonatur Stheven Simanjuntak Joelianto Darmawan Joko Sumarsono Khoiron, Ahmad Mustamil Khoirudin Fathoni, Khoirudin Kumoro, Danang Tejo Ledi Diyanasari Mahendra Adiastoro Mona Subagja Mona Subagja Muhammad Fathurrahman Muhammad Hilmy Herdiansyah Muhammad Imam Dinata Muhammad Muhammad MUHAMMAD TAJUDDIN Muhammad, Naufal Murad Murad Murad, Murad Nani Sulistianingsih Ni Luh Putu Merawati Nur Azis Salim Nur Iksan Qudsi, Jihadil R Fanny Priniti Raden Fanny Printi Ardi Rahmat Sabani Rezky Ramdhaningsih Ria Rismayati Rian Febriyanto Rifki Lukman Satria Rina Rachmawati Risanuri Hidayat Rismayati, Ria Rizal, Ahmad Ashril Saiful Ridlo Salim, Nur Azis Sandi Justitia Putra Satria, Rifki Lukman Sitti Agripina Alodia Yusuf Sukmawaty Sukmawaty Sukmawaty Sukmawaty Sulistyawan, Vera Noviana Tajuddin, Muhammad Taofan Ali Achmadi Taofan Ali Achmadi Taofan Ali Achmadi Teguh Bharata Adji Tri Agus Wahyudi Uswatun Hasanah Uswatun Hasanah USWATUN HASANAH Uswatun Hasanah Vera Noviana Sulistyawan Wafi, Ahmad Zein Al Wardatullatifah S, Ince Siti Yusuf, Siti Agrippina Alodia Zaenal Abidin Zaurarista Dyarbirru Zidan Vieri Wijaya