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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Pengajaran MIPA TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmu Komputer (JIK) Indonesian Journal of Disability Studies Journal of Engineering and Technological Sciences ELINVO (Electronics, Informatics, and Vocational Education) Jurnal Penelitian dan Pembelajaran IPA Indonesian Journal of Science and Technology Pedagogia: Jurnal Pendidikan QUANTUM: Jurnal Inovasi Pendidikan Sains JOIV : International Journal on Informatics Visualization Al Ishlah Jurnal Pendidikan Knowledge Engineering and Data Science Jurnal Penelitian Pendidikan IPA (JPPIPA) Momentum: Physics Education Journal MUST: Journal of Mathematics Education, Science and Technology Journal of Natural Science and Integration JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURNAL PENDIDIKAN TAMBUSAI Journal of Education Technology Jurnal Tekno Insentif Jurnal Sains Dirgantara Education and Human Development Journal Jurnal Paedagogy Cendikia : Media Jurnal Ilmiah Pendidikan Journal Evaluation in Education (JEE) Brilliance: Research of Artificial Intelligence Jurnal Pengabdian Masyarakat untuk Negeri (UN-PENMAS) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Digital Transformation Technology (Digitech) Journal of Coaching and Sports Science IJOEM: Indonesian Journal of Elearning and Multimedia Finger : Jurnal Ilmiah Teknologi Pendidikan Bulletin of Social Informatics Theory and Application Jurnal Guru Komputer Jurnal Pendidikan Teknologi Informasi dan Komunikasi Journal of Computers for Society Cadika Journal.
Lala Septem Riza
Universitas Pendidikan Indonesia, Bandung, Indonesia
Agriculture, Biological Sciences & Forestry Humanities 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 Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Physics Social Sciences Other

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Development of Virtual Reality Media for Earthquake Simulation Ulum, Muhammad Bahrul; Prasetyaningsih, Prasetyaningsih; Akbar, Anthonio; Hamzah, Raseeda; Wahyudin, Wahyudin; Riza, Lala Septem
FINGER : Jurnal Ilmiah Teknologi Pendidikan Vol. 4 No. 3 (2025): Finger : Jurnal Ilmiah Teknologi Pendidikan
Publisher : CV. Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/finger.v4i3.460

Abstract

Background: Indonesia has a high risk of earthquakes, necessitating innovative approaches to disaster mitigation education.Aims: This study aims to develop Virtual Reality (VR)-based learning media to enhance students’ understanding and preparedness, particularly among students, in facing earthquake scenarios.Methods: The development process comprises four main stages: identifying educational content, designing interactive scenarios, creating 3D assets and interactive elements, and developing the virtual reality application using Unity.Results: The developed interactive VR media includes a tutorial feature, selectable earthquake location scenario (classroom, library, laboratory), and adjustable earthquake magnitude settings. It enables users to experience immersive and safe earthquake simulations while actively practicing appropriate  emergency response procedures.Conclusion: The application of VR-based learning media offers substantial potential to enhance disaster literacy, increase student engagement, and create more meaningful learning experiences. The implementation of this media in educational settings is expected not only to strengthen a culture of disaster awareness but also to contribute to reducing casualties and losses caused by earthquakes in the future.
The Best Malaysian Airline Companies Visualization through Bilingual Twitter Sentiment Analysis: A Machine Learning Classification Abu Samah, Khyrina Airin Fariza; Amirah Misdan, Nur Farhanah; Hasrol Jono, Mohd Nor Hajar; Riza, Lala Septem
JOIV : International Journal on Informatics Visualization Vol 6, No 1 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.1.879

Abstract

Online reviews are crucial for business growth and customer satisfaction. There is no exception for the airlines’ company, which places third as the biggest contributor to Malaysia’s Gross Domestic Product. Customer opinions play an important role in maintaining the reputation and improving the quality of service of the airlines. However, there is no specific platform for online review. Most online ratings obtain English, leading to inaccurate results as not all reviews regarding different languages are considered. Airlines currently have no specific platform for online reviews despite being critical for business growth, performance, and customer experience improvement. Hence, this paper proposed implementing a web-based dashboard to visualize the best Malaysian airline companies. The airline companies involved are AirAsia, Malaysia Airlines, and Malindo Air. We designed and developed the proposed study through the bilingual analysis of Twitter sentiment using the Naïve Bayes algorithm. Naïve Bayes algorithm is a machine learning approach to do classification. The tweets extracted were analyzed as metrics that advance airline companies’ online presence. Testing phases have shown that the classifier successfully classified tweets’ sentiment with 93% accuracy for English and 91% for Bahasa. Every feature in the web-based dashboard functions correctly and visualizes a detailed analysis of sentiment. We applied the System Usability Scale to test the study’s usability and managed to get a score of 94.7%. The acceptability score ‘acceptable’ result concluded that the study reflects a good solution and can assist anyone in understanding the public views on airline companies in Malaysia.
Application of Programming Algorithms to Support Computational Thinking in Children with Autism Spectrum Disorder Zsalzsa Puspa Alivia; Jaja Kustija; Lala Septem Riza; Anne Hafina; Munir Munir; Wahyudin Wahyudin
AL-ISHLAH: Jurnal Pendidikan Vol 17, No 4 (2025): DECEMBER 2025
Publisher : STAI Hubbulwathan Duri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35445/alishlah.v17i4.8489

Abstract

Children with Autism Spectrum Disorder (ASD) often experience challenges in logical reasoning and problem-solving, which can hinder their computational thinking (CT) development. This study aimed to examine the effectiveness of programming algorithm-based learning media in enhancing CT skills among children with ASD during Phase C informatics learning. A mixed-method approach combining Design-Based Research (DBR) and Single Subject Research (SSR) was employed. The study involved three children with ASD enrolled at SD BPI Bandung. The DBR process consisted of four stages: needs analysis, media design, development, and implementation. The intervention was conducted through an SSR design with three phases—Baseline 1 (A1), Intervention (B), and Baseline 2 (A2)—to assess changes in CT performance. All participants demonstrated notable improvements in CT skills following the intervention. For example, Participant KA’s score increased from 20% to 60%, KZ’s from 30% to 60%, and SB’s from 20% to 45%. The results indicated consistent upward trends and stable retention during the post-intervention baseline phase, suggesting that the programming algorithm learning media effectively enhanced computational thinking abilities. The findings support the use of structured, technology-assisted learning to promote CT in children with ASD. However, the small sample size limits generalizability, and future studies should include larger, more diverse participants. The study underscores the importance of developing adaptive, inclusive learning media that accommodate individual cognitive and sensory needs.
School Feasibility Analysis and Grade Improvement Strategies Using the Random Forest Algorithm Aliyya, Farrel Rahma; Farizi, Syahandhika Naufal; Riza, Lala Septem; Megasari, Rani; Nugraha, Eki; Wahyudin, Asep
JENTIK : Jurnal Pendidikan Teknologi Informasi dan Komunikasi Vol. 4 No. 2 (2025): Jurnal Pendidikan Teknologi Informasi dan Komunikasi
Publisher : CV Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/jentik.v4i2.475

Abstract

Background of Study: Educational disparities across Indonesian provinces persist, particularly in infrastructure, teacher quality, and dropout rates, necessitating data-driven analysis for equitable improvements.Aims: This study investigates school feasibility and proposes strategies to enhance provincial education performance using the Random Forest algorithm.Methods: Aggregated provincial education data covering student numbers, dropout rates, teacher qualifications, and classroom conditions were transformed into derivative indicators. A binary classification (Feasible/Not Feasible) based on national dropout median was applied. The model was developed using R with six systematic steps, including training and evaluation of a Random Forest model (ntree = 100, mtry = 3) using accuracy, sensitivity, and specificity.Result: The model accurately classified school feasibility. Key predictors included teacher quality, student-teacher ratios, and classroom conditions. Several provinces were identified as “Not Feasible.”Conclusion: Machine learning proves effective for education policy support. The study offers targeted recommendations such as improving infrastructure, enhancing teacher training, and reducing dropouts to promote equitable education in Indonesia.
Implementing the rasch model to assess the level of students' critical and reflective thinking skills on the photoelectric effect Juandi, Tarpin; Kaniawati, Ida; Samsudin, Achmad; Riza, Lala Septem
Momentum: Physics Education Journal Vol. 7 No. 2 (2023)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/mpej.v7i2.8252

Abstract

This study aims to determine the level of students’ critical and reflective thinking skills on the topic of photoelectric effects. In this study, the cross-sectional survey approach was employed in conjunction with purposive sampling techniques.  The data collection instruments are questionnaires for critical thinking and reflective thinking skills, with 20 critical thinking items and 24 reflective thinking items. A total of 35 students, 6 males and 29 females, with an average age of 20 years, agreed to fill out the questionnaire that was distributed. The acquired quantitative data were evaluated using the Rasch model, with critical thinking skills showing that 11% of students were at a very low level, 49% were at a low level, 26% were at a high level, and 14% were at a very high level. Meanwhile, data analysis of reflective thinking skills revealed that 20% of pupils had low levels, 63% had moderate levels, and 17% had high levels. As a result, it is suggested that critical thinking and reflective thinking skills be continuously debriefed.
Comprehensive Review: Transforming Self-Education through Automatic Question Generation Technology Erry Fuadillah; Lala Septem Riza; Rani Megasari
Master Journal of Future Education Vol. 2 No. 1 (2025): Oktober
Publisher : CV. Master Literasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63461/cadikajournal.v21.296

Abstract

Automatic question generator (AQG) technology is a system developed to create questions automatically from input in the form of text, images, and videos. AQG has been developed using various approaches such as natural language processing (NLP), statistical approaches, and other machine approaches. AQG has a very important role in the world of education, especially in independent education, because it can be used as a good evaluation medium for students. Utilizing AQG in independent education gives students full control to determine their learning. AQG turns learning into a more interactive experience by generating questions that can trigger critical thinking and problem-solving skills. AQG technology developed in independent learning will encourage students to respond actively to the material and understand concepts more deeply. Approximately 60% of research related to AQG has been conducted for assessment, 18% for knowledge acquisition, and the remainder for validation and other purposes. This research was conducted by conducting a comprehensive review of 63 articles related to AQG in education.
Evaluating Research Trends and Gaps in Disaster Literacy within Science Education: A Bibliometric Perspective Prasetyaningsih Prasetyaningsih; Ida Kaniawati; Lala Septem Riza; Judhistira Aria Utama
Journal Evaluation in Education (JEE) Vol 6 No 1 (2025): January
Publisher : Cahaya Ilmu Cendekia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37251/jee.v6i1.1248

Abstract

Purpose of the study: This study aims to evaluate research trends, gaps, and global patterns in disaster literacy within science education to identify areas for improvement and provide actionable recommendations for enhancing education strategies in disaster-prone regions. Methodology: A bibliometric analysis was conducted using data from the Scopus database (2000-2024). Tools used include R Studio with the Bibliometrix package for generating visualizations such as co-occurrence networks, word clouds, and trend analyses. The dataset comprises 315 articles selected using “disaster literacy” and "science education". Main Findings: Findings indicate an increasing focus on disaster literacy research, with eminent themes such as technology integration and project-based learning. However, significant gaps remain in contributions from developing nations and the long-term evaluation of disaster literacy programs. Collaborative international research has been identified as a growing trend. Novelty/Originality of this study: This study uniquely combines bibliometric analysis with an evaluative approach to highlight disparities in disaster literacy research and propose strategies for improving curriculum integration and global collaboration. It advances understanding by identifying underexplored areas and providing a foundation for targeted educational interventions.
Stock Price Prediction Using the ETSFormer Model Case Study: PTBA Muhammad Azka Atqiya; Lala Septem Riza; Ani Anisyah
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.6729

Abstract

The capital market in Indonesia is currently experiencing very rapid development. This growth is significantly evidenced by the increasing number of investors, especially from the millennial and Gen Z demographics. However, this growing investor base also faces a major challenge: high stock price volatility. These fluctuations are triggered by various factors, ranging from domestic economic policies and global geopolitical conditions to rapidly changing market sentiment. This research aims to build a stock price prediction model for PT Bukit Asam Tbk (PTBA) using the ETSFormer architecture, a modern Transformer-based method designed for time-series data. The historical stock price data used in this study covers a five-year period from 2020 to 2025. To ensure optimal model performance, the best model was identified using the Grid Search technique to find the most effective combination of hyperparameters. The results of this study determined that the best model was achieved with the hyperparameters model dimension = 16, batch size = 16, and a learning rate = 0.01, which yielded a validation loss of 0.0074. In the evaluation phase, this model demonstrated solid performance with a MAPE score of 3.28%, an MAE of 86.76, and an RMSE of 117.2. Although the resulting model is quite good at reading long-term trend directions, observations indicate limitations in capturing short-term price volatility. This implies that the model is more suitable for strategic trend analysis than for predicting daily fluctuations.
Differentiated Problem Based Learning Elevates Vocational Student Collaboration Skills: Pembelajaran Berbasis Masalah Berdiferensiasi Meningkatkan Kolaborasi Siswa Vokasi Al Husaeni, Dwi Fitria; Rahman, Eka Fitrajaya; Mulyanti, Budi; Riza, Lala Septem; Sulistiyono, Yakub Eriyanto; Pratiwi, Pratiwi
Pedagogia : Jurnal Pendidikan Vol. 15 No. 2 (2026): August
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/pedagogia.v15i2.1886

Abstract

General Background Collaboration skills are essential competencies in contemporary education, particularly within problem-based and interactive learning environments. Specific Background Problem-Based Learning integrated with deep learning and differentiated approaches has been proposed to support meaningful engagement and teamwork among vocational students. Knowledge Gap However, empirical evidence on how differentiated PBL combined with deep learning systematically strengthens collaboration skills in formal vocational education remains limited. Aims This study aims to examine the application of differentiated PBL with deep learning to strengthen students’ collaboration skills through iterative classroom action cycles. Results The findings show a progressive increase in collaboration skills from 30.22% in the first cycle to 87.21% in the third cycle, accompanied by improved teaching quality from 46% to 87%, indicating a strong positive relationship between instructional quality and collaborative performance. Novelty The study introduces the integration of differentiation across material, process, and product within PBL and combines qualitative and quantitative observations in a vocational classroom context. Implications These results highlight the importance of adaptive instructional design, learning style mapping, and structured group interaction to foster inclusive, collaborative learning aligned with 21st-century competencies. Highlights• Progressive cycles demonstrate substantial growth in cooperative performance indicators• Adaptive grouping and varied learning products support inclusive participation dynamics• Instructional quality aligns consistently with improved teamwork engagement KeywordsCollaboration Skills; Problem Based Learning; Differentiated Learning; Deep Learning; Vocational Education
Comparative analysis of ensemble learning algorithms in enhanced confidence-based assessments Azharludin, Nur Maisarah Nor; Samah, Khyrina Airin Fariza Abu; Dzulkalnine, Mohamad Faiz; Fadzil, Ahmad Firdaus Ahmad; Jono, Mohd Nor Hajar Hasrol; Riza, Lala Septem
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.9935

Abstract

This paper provides a comparative analysis of ensemble learning (EL)algorithms to enhance the confidence-based assessment (CBA) in evaluating student performance. Traditional CBA often suffers from misclassification caused by overconfidence and underconfidence, limiting its accuracy and fairness. To address these challenges, an enhanced CBA-EL model integrating bagging and boosting ensemble algorithms is proposed. Five bagging algorithms, which are random forest (RF), decision tree (DT)support vector machine (SVM), K-nearest neighbors (KNN), Naïve Bayes(NB), and four boosting algorithms, which are adaptive boosting(AdaBoost), eXtreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and categorical boosting (CatBoost), were evaluated using a dataset of 276 responses collected from Pre- and Post-Quiz CBA in a discrete structures course. Algorithm performance was evaluated using accuracy, correlation, weighted mean precision (WMP), and weighted mean recall (WMR). RF achieved 73.19% accuracy, 0.725 correlation, 0.751 WMP, and 0.766 WMR, while CatBoost outperformed all with 86.23% accuracy and the highest correlation, WMP, and WMR values, with 0.842, 0.843, and 0.862, respectively. The findings indicate that integrating EL into CBA improves prediction accuracy and supports bias-aware student evaluation. This research advances reliable assessment practices and informs the development of adaptive learning systems.
Co-Authors Abdullah, Cep Ubad Abu Samah, Khyrina Airin Fariza Achmad Samsudin Ade Gafar Abdullah, Ade Gafar Ade Rohayati Ade Sobandi, Ade Adedokun-Shittu, Nafisat Afolake Adi Rahmat Ahmad Zainal Abidin Akbar, Anthonio Al Husaeni, Dwi Fitria Al Husaeni, Dwi Novia Aldi Zainafif Alejandro Rosales Pérez Alejandro Rosales-Pérez Alfitri, Latifahny Aridia Aliyya, Farrel Rahma Amay Suherman Amirah Misdan, Nur Farhanah Ani Anisyah Ani Anisyah anne Hafina, anne Aqhbar Habib Arianti, Andini Setya Asep Bayu Dani Nandiyanto Asep Wahyudin Asep Wahyudin AZ Pranata Azharludin, Nur Maisarah Nor Budi Mulyanti Budiana, Dian Cep Ubad Abdullah Dadang Lukman Hakim Destian, Rangga Dewini Dewini Didin Wahyudin Dzulkalnine, Mohamad Faiz Edy Soewono Edy Soewono Eka Fitrajaya Rahman Eki Nugraha Eliyawati Eliyawati Enjang Ali Nurdin Enjun Junaeti Erlangga, E. Erna Piantari Erry Fuadillah Fadzil, Ahmad Firdaus Ahmad Faisal Syaiful Anwar Farhan Dhiyaa Pratama Farizi, Syahandhika Naufal Fathimah, Nusuki Syari'ati Fatimah, Nusuki Syariati Ferry Mukharradi Simatupang Fidela Zhafirah Gerraldi, Alief Gintara, Andre Rangga Gunarso Hamzah, Raseeda Hasanah , Lilik Nur Hasrol Jono, Mohd Nor Hajar Hayati , Nurlaila Herbert Siregar Homdijah, Oom Siti Huda, Kirana Syafa Husni Firmansyah Ida Kaniawati ISKANDAR, AYSHA ALIA Isma Widiaty Jaja Kustija Jono, Mohd Nor Hajar Hasrol Judhistira Aria Utama Kafilli, Muhammad Fikri Kenny David Kenny David Khyrina Airin Fariza Abu Samah Kuntjoro Adji Sidarto Kuntjoro Adji Sidarto Liliasari Mahmoud Fahsi Masnur Ali Mediayani, Melani Mega Fatimah Rosana Mohd Nor Hajar Hasrol Jono Muhammad Afif Auliya Muhammad Alam Basallamah Muhammad Aziz Muhammad Azka Atqiya Muhammad Bahrul Ulum Muhammad Hazmi Zuhdi Muhammad Irfan Firmansyah Muhammad Ramdan Pamungkas Muhammad Syafri Syamsudin Mumu Komaro Munir Munir Munir Munir, Munir N. Nurjanah Nanang Dwi Ardi Naufal Rabah Wahidin Nazir, Shah Nor Aiza Moketar Novi Sofia Fitriasari Novitasari , Eka Fitri Novri Asri Nur Maisarah Nor Azharludin Nuraulia, Anti Nurhayati, Ai Siti Nurqueen Sayang Dinnie Wirakarnain Nursalman, Muhammad Nusratullo, Samialloi Olyan, Warzuqni Parlindungan Sinaga Pérez, Alejandro Rosales Pertiwi, Anita Dyah Piantari, Erna Prabawa, Harsa Wara Prasetyaningsih Prasetyaningsih prasetyaningsih prasetyaningsih Prasetyaningsih, Prasetyaningsih Pratiwi Pratiwi Pudjo Sukarno Pudjo Sukarno Putri , Ananda Hafizhah Putri , Liandha Arieska Putri Amelia Solihah Putri, Iffa Ichwani Qobus, Muhammad Shofwan Rahman, M Ammar Fadhlur Rambari Apandi, Anjar Rani Megasari Raseeda Hamzah Rasim, Rasim Rena Zaen Rendi Adistya Rosdiyana Riandi Riandi Riezqa Andika Rika Rafikah Agustin Rizky Rachman Judie Rooseno Rahman Dewanto Rosa, Elisa Rosi Oktiani Rosyda, Miftahurrahma Safitri, Fibriyana Sahidin, M. Zaenal Iskandar Samah, Khyrina Airin Fariza Abu Sapiruddin, Sapiruddin Selvi Marcellia Shah Nazir Shah Nazir Sigit Nugroho Siregar, Herbert Siregar, Nofi Marlina Solihat, Syifa Sonjaya, Rebina Putri Sugeng Rifqi Mubaroq Sulistiyono, Yakub Eriyanto Suratno Susilawati - Tarpin Juandi Tarpin Juandi Taufiq Hidayat Topik Hidayat Tutuka Ariadji Tyas Farrah Dhiba Wahyudin Wahyudin - Wahyudin Wahyudin Sanusi Rosada Wahyudin Wahyudin Wahyudin, W. Wawan Setiawan Wibisono, Yudi Wihardi, Yaya Yudi Prasetyo Zain, Muhammad Iqbal Zainab Othman Zsalzsa Puspa Alivia