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All Journal SCHOOL EDUCATION JOURNAL PGSD FIP UNIMED Aptisi Transactions on Management Journal of Computer Science and Technology Application
Yulina Ismiyanti
Sultan Agung Islamic University
Computer Science & IT Decision Sciences, Operations Research & Management Languange, Linguistic, Communication & Media Other

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PENGARUH MODEL MAKE A MATCH BERBANTU MEDIA FLASH CARD MAPU TERHADAP HOTS IPAS SISWA KELAS V SD Silvi Yunita Wulandari; Yulina Ismiyanti
SCHOOL EDUCATION JOURNAL PGSD FIP UNIMED Vol. 16 No. 1 (2026): SCHOOL EDUCATION JOURNAL PGSD FIP UNIMED
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/sejpgsd.v16i1.73716

Abstract

The Higher Order Thinking Skills (HOTS) of elementary school students still need to be improved because the learning tends to be teacher-centered and does not actively involve the students. This study aims to determine the effect of the Make a Match learning model assisted by MAPU Flash Card media on HOTS abilities in fifth-grade elementary school IPAS learning. The research uses a quantitative approach with a One Group Pretest-Posttest design involving 24 fifth-grade students. Data were obtained thru descriptive tests before and after the treatment, and then analyzed using validity, reliability, normality tests, and the Paired Sample T-Test. The research results show an increase in the average score from 71.57 in the pretest to 85.42 in the posttest with a significance value < 0.05. Based on these results, it can be concluded that the Make a Match learning model assisted by MAPU Flash Card media has a positive effect on improving the HOTS IPAS abilities of fifth-grade elementary school students.
PENGARUH MODEL PROBLEM BASED LEARNING BERBANTUAN MEDIA PICTURE QUESTION CARD TERHADAP KEMAMPUAN BERPIKIR KRITIS PADA PEMBELAJARAN IPAS SISWA KELAS III SD Ainur Lailatul Hamidah; Yulina Ismiyanti
SCHOOL EDUCATION JOURNAL PGSD FIP UNIMED Vol. 16 No. 1 (2026): SCHOOL EDUCATION JOURNAL PGSD FIP UNIMED
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/sejpgsd.v16i1.73690

Abstract

This research aims to analyze the effectiveness of the Problem Based Learning (PBL) model combined with Picture Question Card (PQC) media in improving the critical thinking skills of class III students in IPAS learning. The research uses a quantitative approach with one group pretest-posttest pre-experimental design. The research subject consists of 28 students of SD Negeri Karangroto 04. Critical thinking ability is measured through a description test based on critical thinking indicators. The data obtained was analyzed using the Wilcoxon Signed Rank test to determine the differences before and after treatment. The research results show that there is a significant improvement after the implementation of the PBL model with the help of PQC media. The average student score increased from 68 during the pretest to 82 during the posttest. The results of statistical analysis showed a significance value of less than 0.05 which identified a meaningful influence. This finding shows that the integration of PBL with visual media based on question cards is effective in developing critical thinking skills of elementary school students in IPAS learning.
PENGARUH MODEL PEMBELAJARAN TEAMS GAMES TOURNAMENT BERBANTUAN FLASH CARD BHINNEKA TERHADAP MINAT BELAJAR IPAS SISWA KELAS IV SEKOLAH DASAR Shova Anggriani; Yulina Ismiyanti
SCHOOL EDUCATION JOURNAL PGSD FIP UNIMED Vol. 16 No. 1 (2026): SCHOOL EDUCATION JOURNAL PGSD FIP UNIMED
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/sejpgsd.v16i1.73692

Abstract

This research is focused on examining the extent to which the application of the Teams Games Tournament (TGT) learning model assisted by Bhinneka Flash Card media influences the interest in learning science in grade IV elementary school students. This study employed a quantitative pre-experimental One Group Pretest Posttest method. The population consisted of 28 students, with a saturated sampling technique, using the entire population as the sample. Data collection included a learning interest questionnaire. Based on the pretest and posttest normality tests the average student interest in learning (pretest) was 47.86, and after treatment, the average posttest score was 60.18. the results showed a paired sample t-test with a Sig. (2-tailed) of 0.000 <0.005. This indicates that H0 is rejected and H1 is accepted. It can be concluded that the implementation of the TGT model, using Bhinneka Flash Cards, can influence the interest in learning science in fourth-grade elementary school students.
Digital Maturity and Transformation Readiness Across Indonesian Industries Yane Devi Anna; Yulina Ismiyanti; Richard Evans
APTISI Transactions on Management (ATM) Vol 10 No 1 (2026): ATM (APTISI Transactions on Management: January)
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/d53ekp67

Abstract

Indonesia is experiencing a rapid digital transformation driven by national initiatives such as Making Indonesia 4.0 and the Digital Economy Roadmap 2030. However, prior studies consistently report uneven digital maturity across industries due to disparities in infrastructure, digital skills, leadership commitment, and strategic alignment. This study adopts a Systematic Literature Review (SLR) to synthesize empirical and conceptual evidence on digital maturity and digital transformation readiness across industries in Indonesia and comparable emerging economies. The review focuses on six dominant dimensions identified across prior studies, namely digital strategy alignment, IT infrastructure, data analytics capability, leadership commitment, employee capability, and innovation culture. The synthesis reveals that banking and financial services exhibit the highest level of digital maturity, followed by manufacturing and logistics. At the same time, MSMEs, education, and healthcare remain in early to developing stages. Leadership commitment, workforce digital skills, and data analytics capability consistently emerge as the most critical drivers of transformation readiness. This study contributes theoretically by integrating fragmented findings on digital maturity into a coherent conceptual framework relevant to emerging economies. Practically, the results support national digital policy development and align with SDG 4 (Quality Education), SDG 8 (Decent Work and Economic Growth), and SDG 9 (Industry, Innovation, and Infrastructure) by emphasizing inclusive digital capability development.
Machine Learning Enabled Social Media Competitive Intelligence System Hendri Handoko; Yulina Ismiyanti; Omar Arif Al-Kamari
CORISINTA Vol 3 No 1 (2026): February
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/480er062

Abstract

Social media platforms generate massive volumes of publicly accessible digital data that reflect organizational competitive strategies, yet most existing competitor analyses remain manual, descriptive, and limited to surface-level engagement metrics, resulting in low scalability and weak strategic intelligence. This study proposes a Machine Learning Enabled Social Media Competitive Intelligence System designed to automate competitor strategy extraction through artificial intelligence and big data analytics. The objective is to develop a computational framework capable of identifying strategic content patterns, communication objectives, audience positioning, and paid advertising behaviors using data-driven techniques. Large-scale public data from social media posts, engagement indicators, and advertising transparency libraries are collected and processed through data preprocessing pipelines, including text normalization, tokenization, and feature extraction using TF-IDF and word embedding representations. Supervised machine learning algorithms are implemented to classify content themes, detect strategic clusters, and model competitive positioning patterns, while performance evaluation is conducted using accuracy, precision, recall, and F1-score metrics to ensure robustness and reliability. Experimental findings demonstrate that the proposed system significantly enhances analytical consistency, scalability, and strategic insight generation compared to traditional mixed method approaches. This research contributes to the advancement of AI-driven social media analytics and establishes a computational foundation for scalable big data-based competitive intelligence systems aligned with Artificial Intelligence and Big Data domains.
Co-Authors Ainur Lailatul Hamidah Hendri Handoko Omar Arif Al-Kamari Richard Evans Shova Anggriani Silvi Yunita Wulandari Yane Devi Anna