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All Journal Jurnal Ruas (Review of Urbanism and Architectural Studies) Celt: A Journal of Culture, English Language Teaching & Literature Sisforma: Journal of Information Systems PROXIES LANGKAU BETANG: JURNAL ARSITEKTUR Jurnal Riset Ekonomi dan Bisnis Journal of Architectural Design and Urbanism Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Arsitektur ZONASI EconBank : Journal Economics and Banking Journal of Information Systems and Informatics Neo Teknika: Jurnal Ilmiah Teknologi Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Journal of Architectural Research and Education Journal of Management and Business Environment (JMBE) Jurnal Teknik Informatika (JUTIF) Journal of Business and Technology Arsitekta IJEAS (International Journal of Environment, Architecture, and Societies) Elektriese: Jurnal Sains dan Teknologi Elektro Journal of Computing Theories and Applications Journal of Local Architecture and Civil Engineering
Ridwan Sanjaya
Department Of Information Systems, Soegijapranata Catholic University
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Social Sciences Other

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Efektivitas PECS untuk Meningkatkan Kemampuan Bahasa Reseptif Anak dengan Autism Spectrum Disorder Usia 4-5 Tahun: The Effectiveness of PECS in Improving Receptive Language Skills in Children with Autism Spectrum Disorder Aged 4-5 Years Sanjaya, Ridwan; Perdana Putra, Sinar; Nugroho, Setyadi
Elektriese: Jurnal Sains dan Teknologi Elektro Vol. 15 No. 02 (2025): Artikel Riset Edisi Oktober 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/elektriese.v15i02.6964

Abstract

The prevalence of Autism Spectrum Disorder (ASD) is increasing significantly in Indonesia, which affects children's communication skills and social-cognitive development. This study aims to test the effectiveness of the Picture Exchange Communication System (PECS) in improving receptive language skills in children with ASD aged 4–5 years at the Olan Development Center in Sragen. This quasi-experimental study, employing a one-group pretest–posttest design, involved five boys aged 4–5 years who were purposively selected. The PECS intervention consisted of 14 sessions, while receptive language skills were assessed using the Receptive Verbal Vocabulary Test (RVT) before and after the intervention. Data analysis included the Shapiro–Wilk normality test and a Paired Sample t-test to examine differences in pretest and posttest scores. The average receptive language score increased from 6.40 in the pretest to 14.20 in the posttest (mean difference = 7.80). The results of the Paired Sample t-test showed a significant increase (t = -4.033; df = 4; p = 0.016), indicating that the change in scores was not coincidental. Variations in responses between subjects were reflected in the posttest scores, which ranged from 4 to 26. PECS was effective in improving the receptive language skills of early childhood ASD children through a visual communication approach. It is recommended that PECS be implemented as part of speech intervention for children with ASD, as well as further research with larger samples, more extended follow-up periods, and control designs to strengthen the generalizability of the findings.
Sistem Deteksi Aktivitas Dan Sirkulasi Ruang Sebagai Upaya Efisiensi Ruang Dengan Menggunakan Pozyx Arinta, Rizka Tri; Purwanto, LMF; Saswitko, Prasasto; Sanjaya, Ridwan
Neo Teknika Vol 7, No 2 (2021): Vol 7 No 2 (2021) : Jurnal Neoteknika Volume 7 Nomer 2 Desember 2021
Publisher : Universitas Pandanaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37760/neoteknika.v7i2.1834

Abstract

Seperti tali yang tidak terputus, begitulah prinsip programan ruang dalam perancangan desain arsitektur. Aktivitas dan sirkulasi merupakan bagian dari pemrograman yang sangat penting dalam organisasi ruang. Indonesia harus melakukan upaya untuk menentukan standar besaran ruang yang efektif dan efisien, karena dalam catatan jejak ekologisnya, Indonesia membutuhkan 0,06 lahan untuk tempat tinggal dan infrastruktur lainnya lebih banyak dari lahan yang tersedia saat ini. Angka ini dapat ditekan dengan upaya menciptakan satu efisiensi ruang, dengan efisiensi ini ini diharapkan mampu menentukan standar minimal besaran ruang yang sesuai dengan karakteristik masyarakat di Indonesia. Penelitian ini dilakukan dengan metode analisis deskriptif, dengan melihat penggambaran yang dilakukan melalui pengamatan studi preseden untuk mendeteksi aktivitas dan pola sirkulasi yang terbentuk. Studi ini lakukan agar dalam penelitian berikutnya mampu menjadi sebuah alat dalam merekam karaktistik aktivitas dan pola sirkulasi yang dibentuk oleh masyarakat Indonesia. Hasil dari membandingkan data yang telah dilakukan oleh pozyx ini, aktivitas yang terekam dapat membentuk semua pola sirkulasi ruang, dengan demikian perangkat ini mampu dijadikan sebagai alat yang digunakan untuk menganalisa efisiensi ruang. Ruang yang efisian adalah ruang yang ketepatan dan kedaya gunaan yang tinggi, untuk itu dibutuhkan satu perancangan yang tepat guna sesuai dengan karakteristik masyarakat di Indonesia. Jika efiensi ruang tercapai maka standar dimensi ruang juga dapat di efektifkan, dengan demikian Indonesia mampu menekan angka kebutuhan lahan yang diperuntukkan untuk hunian dan pembangunan. Kata kunci : Sistem Deteksi, Aktifitas, Sirkulasi Ruang, Efisiensi Ruang, Pozyx
Adaptasi Kinerja Bangunan Rumah Tinggal dengan Ventilasi Atap Responsif Mufidah, Mufidah; Purwanto, LMF.; Sanjaya, Ridwan
RUAS Vol. 19 No. 1 (2021)
Publisher : Departemen Arsitektur Fakultas Teknik Universitas Brawijaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.ruas.2021.019.01.7

Abstract

Thermal comfort is a condition where occupants can feel comfortable doing activities in the building. One of the ways to get comfort is done by passive design, in which the building is designed to adapt weather change outside the building. Because the weather outside is always changing, the planned building design must be responsive to these weather changes. This study uses a responsive roof ventilation model, that the movement of the roof vent covering grille, which serves as an attempt to regulate the exit of wind from the inlet. This study method begins with a literature review on the thermal comfort of residential building in the humid tropics,  as a study of the application of passive design principles as building adaptation to weather changes. Furthermore, an analysis of the ventilation area is made based on the need for thermal comfort in the building. Finally, the planning of building performance systems automatically using the Arduino temperature and humidity sensors. The result is the concept of a framework as applying automation to responsive roof ventilation. This preliminary study is still basic and it is hoped that can be continued in research with the application and experimentation of the roofs in small building
Google Maps API as a Tool for Detecting Urban Density Levels Ara Kian, Donatus; Sanjaya, Ridwan; Rejeki, V. G. Sri
Local Engineering Vol. 4 No. 1 (2026): June
Publisher : CV. Gio Architect

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59810/lejlace.v4i1.231

Abstract

The development of geospatial technology has enabled more efficient analyses of urban density. Google Maps API provides location data, traffic information, and user activity patterns that can be utilized to detect density levels in urban areas. This study aims to explore the potential of the Google Maps API as a tool for identifying urban density by integrating traffic data (Traffic Layer), business location datasets, and user movement patterns. The findings indicate that data obtained from the Google Maps API can be used to map high-density zones in both real-time and historical contexts. These insights have significant implications for urban planning, congestion mitigation, and smart city development.
Multimodal Implicit Sentiment Analysis for Tourism Development: A Systematic Literature Review Yoannes Romando Sipayung; Mochamad Agung Wibowo; Ridwan Sanjaya
Journal of Information System and Informatics Vol 8 No 1 (2026): February
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i1.1436

Abstract

This study aims to examine the application of multimodal approaches in implicit sentiment detection within the tourism sector to support data-driven digital development strategies. This review identifies prevailing trends, methodologies, datasets, and scientific novelties in multimodal sentiment analysis capable of capturing hidden emotions, such as sarcasm and ambiguity, in tourist reviews. Using a systematic literature review approach, ten core studies published between 2020 and 2025 were analyzed to identify prevailing research trends, dominant methodological frameworks, commonly used datasets, and emerging scientific contributions. Results demonstrate that multimodal deep learning models—particularly those employing attention-based fusion and contrastive learning—consistently outperform unimodal approaches in recognizing nuanced tourist emotions that are not explicitly stated in text. Despite these advances, the review reveals a significant gap in tourism-specific and Indonesian-context studies, as well as an overreliance on general-purpose social media datasets. This review provides a conceptual and methodological foundation for implementing multimodal implicit sentiment analysis in tourism decision-making systems, enabling destination managers and policymakers to develop early warning mechanisms for tourist dissatisfaction, enhance destination quality assessment, and support more targeted and sustainable tourism development strategies.
Real-Time Explainable Concept Drift Detection for Eco-Driving in Mining Trucks using KSWIN and Event-Triggered SHAP Kusnawi; Mochamad Agung Wibowo; Ridwan Sanjaya
Journal of Information System and Informatics Vol 8 No 2 (2026): April
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i2.1551

Abstract

Fuel consumption represents a significant operational cost in mining, where real-time eco-driving optimization is hindered by dynamic and non-stationary operating conditions. Variations in operator behavior and environmental factors often induce concept drift, which diminishes the reliability of static machine learning models and constrains the effectiveness of conventional drift detection methods. This study proposes a distribution-aware, event-triggered Explainable Artificial Intelligence (XAI) framework for detecting and diagnosing fuel consumption anomalies in streaming telematics data. A Hoeffding Tree Regressor was evaluated using a prequential scheme on 1,927,867 real-world observations, achieving a Mean Absolute Error (MAE) of 19.43 under non-stationary conditions. Concept drift was monitored using the Kolmogorov–Smirnov Windowing (KSWIN) algorithm, which detected 1,874 drift events. Upon detection, an event-triggered SHAP module identified contributing factors, indicating that behavioral features such as engine speed and accelerator position were dominant contributors in early drift events. The primary contribution of this study is the integration of distribution-based drift detection with event-triggered explainability within a unified streaming framework, facilitating both anomaly detection and interpretable root-cause analysis.
A Systematic Literature Review of Robustness-Aware Batik Motif Classification: Acquisition Variability, Feature Representation, and Learning Models Aji Priyambodo; R. Rizal Isnanto; Ridwan Sanjaya
Journal of Computing Theories and Applications Vol. 4 No. 1 (2026): JCTA 4(1) 2026
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.16074

Abstract

Batik motif classification has attracted growing attention in visual computing due to its role in cultural heritage preservation, textile informatics, museum documentation, and automated cataloging. Although many studies report high classification accuracy, robustness under real-world acquisition conditions remains insufficiently understood. Batik images are frequently affected by illumination variation, blur, folds, watermark overlays, wearable deformation, scale inconsistency, and background clutter, creating challenges that extend beyond conventional image-noise assumptions. Existing studies largely focus on improving classification performance, while the interactions among acquisition variability, feature representation, evaluation practice, and deployment constraints remain fragmented. This systematic literature review addresses this gap by synthesizing batik classification research through a robustness-aware perspective. Using query expansion, backward and forward citation chaining, relevance screening, and thematic coding, 116 candidate records were identified, resulting in 50 highly relevant studies for detailed analysis. The review reveals that robustness is shaped less by denoising alone than by the combined effects of acquisition conditions, representation design, evaluation realism, and deployment context. Handcrafted descriptors remain competitive for small datasets and structured motifs due to their data efficiency and interpretability, whereas deep learning models achieve the highest reported accuracy when supported by sufficient data diversity and realistic augmentation. Hybrid representations emerge as the most consistently balanced approach, combining local texture stability with higher-level abstraction across heterogeneous acquisition settings. The review further identifies recurring robustness failure patterns, including background dependency, illumination instability, motif-scale inconsistency, wearable deformation, and source-shift vulnerability. Based on these findings, a robustness-oriented research agenda is proposed, emphasizing cross-acquisition evaluation, representation-stability analysis, batik-specific robustness benchmarks, acquisition-aware augmentation, and deployable lightweight or hybrid architectures. The study contributes a domain-specific synthesis that reframes batik motif classification from an accuracy-centric task toward a robustness-aware visual recognition problem.
Artificial Intelligence and Machine Learning for SDG-Oriented Decision Making in Public Governance: A Bibliometric Analysis and Systematic Literature Review Lorensius Anang Setiyo Waluyo; Mochamad Agung Wibowo; Ridwan Sanjaya
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 2 (2026): August
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i2.4021

Abstract

This study maps the development of literature on artificial intelligence (AI) and machine learning (ML) in public decision-making oriented toward achieving the Sustainable Development Goals (SDGs). A bibliometric analysis was conducted on 380 Scopus-indexed documents published between 2017 and 2026, while a focused systematic literature review was performed on 17 studies selected through PRISMA-based screening. Data were cleaned using OpenRefine and analyzed with VOSviewer and Bibliometrix to identify keyword networks, thematic trends, author productivity, country collaboration, and scientific development structures. The findings show that AI and ML are central themes in SDG-oriented decision-making research, strongly connected to decision support systems, public policy, sustainability, climate change, environmental sustainability, smart cities, energy, health, and public governance. Publication growth accelerated markedly after 2023, with India and China as dominant contributors, although international collaboration remains limited. The review also reveals major challenges related to explainability, including black-box algorithms, data bias, low transparency, weak data governance, limited institutional capacity, and unclear legal and ethical accountability. This study argues that AI/ML for SDGs must move beyond accuracy and efficiency toward explainable, auditable, trustworthy, and socially accountable decision support systems globally.
Handcrafted Feature Ablation for Batik Nitik Classification Under Provenance-Aware Evaluation Aji Priyambodo; Rizal Isnanto; Ridwan Sanjaya
Journal of Information System and Informatics Vol 8 No 3 (2026): June
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i3.1679

Abstract

This study re-examines Batik Nitik classification using a leakage-safe provenance-aware evaluation protocol to determine which handcrafted descriptors make a substantive contribution to performance and whether saturated results persist after provenance-based partitioning. Batik Nitik 960 was represented using Histogram of Oriented Gradients (HOG), Local Binary Patterns (LBP), Gray-Level Co-occurrence Matrix (GLCM) descriptors, and grayscale intensity moments. Descriptor ablation, classifier benchmarking, cosine-similarity baselines, four-setting leave-one-provenance-group-out sensitivity analysis, and a supplementary image-level split comparison were evaluated using in-pipeline preprocessing. All HOG-containing feature sets achieved 0.9833 cross-validation accuracy and 1.0000 hold-out accuracy. On fused features, SVM, KNN (Euclidean), and KNN (cosine) achieved 1.0000 hold-out accuracy, while Random Forest reached 0.9958. Raw-pixel, HOG-only, and fused-feature cosine baselines also reached 1.0000 hold-out accuracy. A supplementary image-level HOG-SVM split also produced 1.0000 accuracy. This study contributes a provenance-aware benchmark diagnosis for Batik Nitik classification by identifying HOG as the strongest standalone handcrafted descriptor and by cautioning against deployment-ready interpretation of saturated closed-set accuracy.
Harnessing Remote Sensing for Soil Erosion Prediction: A Bibliometric Review of RUSLE Applications Adi Fajaryanto Cobantoro; Mochamad Agung Wibowo; Ridwan Sanjaya
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 1 (2026): JANUARY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v15i01.2533

Abstract

This study examines recent advancements in soil erosion modeling using the Revised Universal Soil Loss Equation (RUSLE), integrated with remote sensing and artificial intelligence techniques. Adopting a Systematic Literature Review (SLR) and bibliometric analysis via Bibliometrix in R, 63 articles were analyzed from an initial 359 based on strict selection criteria. Findings reveal a sharp rise in publications since 2017, especially involving machine learning and Google Earth Engine (GEE) platforms. Co-authorship analysis highlights significant international collaboration, particularly between Asia and Europe. Concept maps and co-word analyses show a shift from traditional RUSLE applications toward AI and big data approaches. Thematic evolution further indicates a growing focus on climate change and the Sustainable Development Goals (SDGs). The review's primary contribution lies in its explicit identification of critical research priorities by pinpointing key gaps: the limited use of field validation, weak SDG integration, and fragmented international research networks. By highlighting these deficiencies, this study provides a clear roadmap for future investigations, steering the field toward more inclusive, data-driven, and validated approaches to address global land degradation and climate resilience. Overall, the study contributes to the development of more effective erosion mitigation models through technological integration and international collaboration.
Co-Authors Adi Fajaryanto Cobantoro Adiseputra, Nicholaus Agus Cahyo Nugroho Aji Priyambodo Aji Priyambodo Alb. Dwi Yoga Widiantoro Alb. Dwiyoga Widiantoro Albertus Dwi Yoga W Albertus Dwiyoga Widiantoro Alexandra Adriani Widjaja andadari, tri susetyo Andre Kurniawan Pamudji Andru Deva Lukito Aprilia Ratna Christanti Baskara Arya Pranata Benedicta Nathania Nugroho Bernadinus Harnadi Bernardinus Harnadi Cecilia Titiek Murniati Celvin Laviano Chandrawati, T. Brenda Christine Wibhowo, Christine Dharmawan, Jovita Dwiyoga Widyarto Ekawati Marhaenny Dukut, Ekawati Marhaenny Elisa Purnamasari Elisa Purnamasari, Elisa Elizabeth Kurniawan Ardianto Erdhi Widyarto Evangeline Eunike Fajar As'ari Fajar As'ari Felicia Kusuma Fiolita, Cindy FX Hendra Prasetya FX Hendra Prasetya Graciela, Cindy Fiolita Gregorius Alvin Raditya Santoso Hendra Prasetya Hendra Prasetya Hendra Prasetya Hendra Prasetya Hening Artdias Hermawan Hermawan Inggrit Swastini Dewi Isidorus Ivan Kalya Wasistha Koeswoyo, Freddy Koeswoyo, G. Freddy Kusnawi Kusnawi L.M.F. Purwanto Leocadia Desy Pranatalisa LMF. Purwanto Lorensius Anang Setiyo Waluyo Lysbeth Venella Oey Margareta Ernanda Rahardani Meissy Lengmas Congdinata Michael Christano Suryopranoto Mochamad Agung Wibowo Mochamad Agung Wibowo Mufidah Mufidah Muhamad Sandy Saputra Muljanto, Yehuda Joy Nugraha, Johanes Arya Pramesta Nugroho, Agus Cahyo Nugroho, Setyadi Nur Yanti Nuryanti Nuryanti P., Angelicdolly Palgunadi, Petrus Pamudji, Andre Kurniawan Perdana Putra, Sinar Pramuditya, Reza Santika Prasasto Satwiko Priatko, Albertus Aditya Purwanto, LMF R Rizal Isnanto Rahardjo, Ervina Febriani Ramli, Justine Hezekiel Rejeki, V. G. Sri Retang Wohangara, Retang Rio Wiranto Risa Farrid Farrid Christanti, Risa Farrid Rizal Isnanto Santi Widiastuti Santosa, Daniel Saswitko, Prasasto Setiyanto, Benny D. Sindi Budi Emilia Soetomo, Greg. Stephani Inggrit Swastini Stephen Jonathan Gustav Sulastri, Augustina T Brenda Chandrawati T. Brenda Ch Ch Tri Arinta, Rizka veinta sonrizky mayo Wahyuningrum, Shinta Estri Wibowo , Mochamad Agung Widianto, Daniel Prasetya Widjaja, Robert Rianto Widyarto, Erdhi Yoannes Romando Sipayung Yonathan Aditya Wijaya Yulianto, Felix Wiranata