Abstract:The assessment of student career readiness requires a systematic approach that considers multiple competencies and experiences relevant to workplace demands. This study develops an intelligent decision support system based…
ed on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to evaluate and map student career readiness. The study uses 20 student samples and five assessment criteria: field-specific competence (C1), internship experience (C2), communication skills (C3), digital literacy (C4), and English language proficiency (C5). Each criterion is assigned a weight based on its relative importance. The TOPSIS method involves decision matrix construction, normalization, weighted normalization, determination of positive and negative ideal solutions, distance calculation, and preference value calculation. The results show that Y11 achieved the highest preference value of 0.8296, followed by Y6 (0.7951), Y19 (0.7274), Y5 (0.7116), and Y2 (0.6999), while Y9 obtained the lowest preference value of 0.3112. Based on the classification results, 1 student (5%) was categorized as Highly Ready, 5 students (25%) as Ready, 12 students (60%) as Moderately Ready, and 2 students (10%) as Not Ready. These findings demonstrate that TOPSIS can effectively rank and classify student career readiness based on multiple assessment criteria. The proposed system can support higher education institutions in identifying students’ readiness levels and developing more objective, targeted, and data-driven career development strategies.
Abstract:Artificial intelligence is likely to have a significant impact on marketing strategies and customer behaviors in the years ahead. Research in this field has grown considerably, demonstrating AI's ability to simulate human…
n behavior and perform tasks intelligently. With growing interest among marketing researchers and practitioners, this research aims to provide an overview of the evolution of both marketing and AI research fields. This paper explores the emerging role of artificial intelligence in personalized engagement marketing, which focuses on creating, communicating, and delivering customized offerings to customers. Utilizing the Systematic Literature Review technique, we examined over 300 academic articles to uncover prevalent themes and gain a deeper understanding of current AI utilization in marketing. We then propose a plan for future research that examines potential changes in marketing strategies and customer behaviors while emphasizing critical policy considerations related to privacy, bias, and ethics. The implications for marketing managers are discussed along with predictions about how AI will impact branding and customer management practices going forward. Our research highlighted several benefits of integrating AI into marketing such as improved customer interactions, increased revenue, reduced expenses, and enhanced overall efficiency. However, this research also pointed out areas requiring further investigation including challenges posed by AI integration like shortage of skilled personnel and data privacy concerns.
Abstract:Penelitian ini bertujuan untuk mengetahui peningkatan motivasi belajar matematika melalui penerapan model Cooperative Learning tipe Teams Games Tournament (TGT) berbantuan Intelligent Feedback Board (IFB) pada siswa kelas…
s V SDN 04 Sungai Aro. Metode penelitian menggunakan pendekatan kuasi-eksperimen dengan desain pretest-posttest control group. Sampel penelitian terdiri dari 30 siswa yang dibagi secara acak ke dalam kelompok eksperimen dan kontrol. Instrumen yang digunakan adalah angket motivasi belajar dan tes matematika. Hasil menunjukkan adanya peningkatan signifikan motivasi belajar matematika pada kelompok eksperimen setelah perlakuan TGT berbantuan IFB. Penerapan model ini terbukti efektif untuk meningkatkan motivasi belajar matematika siswa kelas V SD.
Kata kunci: motivasi belajar matematika, Cooperative Learning, Teams Games Tournament, Intelligent Feedback Board.
Abstract:The digital technology revolution has catalyzed a fundamental paradigmatic transformation in the global education ecosystem, creating a new era where technology integration has become a strategic imperative in effective…
and sustainable learning management. One of the most disruptive technological innovations that has become the primary focus in educational transformation is Artificial Intelligence (AI), which has demonstrated extraordinary potential in revolutionizing various aspects of learning management through sophisticated adaptive capabilities, deep learning personalization, and comprehensive administrative automation. This research aims to comprehensively and systematically examine the multidimensional role of AI in enhancing the quality of learning management in the digital era, with in-depth analytical focus on three fundamental pillars: strategic learning planning, pedagogical process implementation, and learning outcome evaluation. The research methodology employs a rigorous Systematic Literature Review (SLR) approach, analyzing over 150 high-quality scientific articles from leading national and international journals published between 2014-2024, utilizing a thematic synthesis framework to identify emergent patterns and significant trends in AI implementation in education. Research findings reveal that AI implementation in learning management produces multifaceted transformative impacts, including significant improvements in pedagogical decision-making quality through predictive analytics and data-driven insights, strengthening the strategic role of teachers as adaptive and responsive learning facilitators, and expanding democratic learning accessibility through adaptive learning systems and intelligent tutoring systems technologies. AI has also proven effective in optimizing educational resource allocation, enhancing student engagement through intelligent gamification, and facilitating inclusive and equitable learning.
However, this research also identifies complex challenges that must be addressed in AI implementation, including significant technological infrastructure gaps particularly in remote areas, limitations in educators' digital literacy affecting technology adoption, and ethics and data privacy issues requiring comprehensive regulatory frameworks. The implications of this research emphasize the need for a holistic and structured approach in integrating AI into educational systems, considering technological, pedagogical, and socio-cultural aspects in a balanced manner to achieve sustainable and positively impactful educational transformation.
Abstract:The development of artificial intelligence (AI) technology, especially deep learning, has made significant contributions in various fields, including the world of education. In the context of Islamic Religious Education…
(PAI), the biggest challenge today is how to deliver teaching materials effectively, adaptively, and relevant to the development of the times and the characteristics of the digital generation. Deep learning implementations offer a variety of opportunities to support a more personalized, interactive, and efficient learning process. Through an algorithm-based approach, deep learning is able to process student learning data to provide a learning experience tailored to individual learning styles. The application of this technology also allows for automatic assessment of students' understanding through text, voice, and expression analysis, so that teachers can focus more on providing character development and spiritual values. On the other hand, the use of AI-based chatbots and intelligent assistants can facilitate discussions and consultations about Islamic teachings instantly and factually. The methodology used in this study is a descriptive qualitative study with a literature study and case study approach. Data were collected through a review of national and international scientific literature and focused observations on the practice of AI implementation in several madrassas and Islamic schools in Indonesia. The analysis was carried out thematically by identifying patterns, opportunities, and challenges of applying deep learning in PAI learning. The results of this study are expected to make a scientific contribution to the development of technology-based Islamic education in the digital era.
Abstract:This study aims to investigate the integration of Artificial Intelligence (AI)-based learning media to enhance reading literacy among elementary school students. Using a descriptive qualitative approach through case study…
y and literature analysis, the research was conducted at SDN No. 100311 Palsabolas, involving teachers and students who utilized adaptive reading applications, text-to-speech tools, and intelligent learning platforms. Data were collected through observation, semi-structured interviews, and document analysis, and validated by triangulation techniques. The findings reveal that AI-assisted media significantly improve students’ reading motivation, comprehension, and fluency. Quantitative comparison between pretest and posttest results showed notable progress, with the average literacy score increasing by 16–27 points across different indicators. Students demonstrated greater engagement and independence, while teachers benefited from automated performance analytics and personalized feedback tools. However, challenges emerged related to device limitations, technical competence, and overreliance on automated features. The study concludes that AI-based learning media serve not only as technological tools but also as pedagogical instruments that personalize instruction, foster digital literacy, and transform reading classrooms into more adaptive, interactive, and student-centered environments.
Abstract:The rapid advancement of Artificial Intelligence (AI) presents both opportunities and challenges for elementary education. Teachers play a strategic role in preparing young learners to understand and adapt to technology…
critically, creatively, and ethically. This study aims to analyze the role of elementary school teachers in integrating AI concepts through simple coding activities, as well as to identify the strategies and challenges encountered during implementation. The research employed a qualitative descriptive approach, using interviews, classroom observations, and document analysis as data collection techniques.
The findings reveal that teachers serve as digital learning facilitators, innovators in designing coding-based learning activities, and ethical guides who help students use technology responsibly. Simple coding activities effectively foster students’ logical thinking, creativity, and digital collaboration skills. However, limited technological infrastructure and insufficient teacher training remain major obstacles to sustainable implementation. Therefore, systemic support through educational policy, professional development, and adaptive curriculum design is essential.
Integrating AI concepts through simple coding in elementary schools not only enhances digital literacy but also cultivates ethical awareness and social responsibility toward technology. With collaborative support from educators, institutions, and policymakers, elementary education can become a foundational stage for shaping a generation that is intelligent, creative, and morally grounded in the era of artificial intelligence
Abstract:This study proposes a linear regression-based intelligent calibration approach to improve the accuracy of water turbidity sensor readings in an Arduino microcontroller-based embedded system. The primary objective of this…
research is to develop a mathematical model capable of converting analog values from the Analog-to-Digital Converter (ADC) into a numerical representation that reflects the actual water turbidity level in Nephelometric Turbidity Units (NTU). The calibration process was performed using a standard Hanna Turbidity Meter with water samples ranging from 0.56 NTU to 500 NTU. Measurement results demonstrated a strong linear relationship between the ADC value (495–686) and NTU, with an average system accuracy level above 90%. Comparison of sensor measurements with the standard instrument showed an error margin below 5%, confirming the reliability of the linear regression model in compensating for optical sensor nonlinearities.
Abstract:A fuzzy logic-based control system in household split-type air conditioners (AC) offers an alternative approach to reducing excess energy consumption without compromising thermal comfort. This study aims to test the effectiveness…
ctiveness of three types of membership functions (MF), namely triangular, trapezoidal, and Gaussian, in improving energy efficiency and the stability of room temperature and humidity control. Simulations were performed using MATLAB software with the Mamdani fuzzy inference method and centroid defuzzification technique. The three MF were tested using 30 sets of temperature and humidity data to analyze their effect on fan speed and power consumption. The simulation results show that the trapezoidal MF provides the highest energy efficiency of 57.24%, followed by the Gaussian MF at 56.80% and the triangular MF at 53.71%. These findings indicate that fuzzy systems can significantly reduce energy consumption compared to conventional air conditioner controllers. This research is expected to serve as a reference in the development of more energy-efficient intelligent control systems.
Abstract:Education is the backbone and main tool for a country’s development, because it emphasizes the quality of human resources (HR). Education aims to brighten the nation’s future with an intelligent and characterful generation.…
ration. Learning, as an interaction between teachers, students, and learning resources, is a systematic process involving interrelated components to achieve optimal results. This literature review aims to provide a comprehensive understanding of learning theory and learning in educational practice. In this research, the researcher used a literature review method which aims to identify, find and analyze documents related to the research problem. The results of the research show that this consistency has a crucial role in creating a predictive learning environment, facilitating the continuity of curriculum and strategy development. teaching, facilitates the transfer of learning, and forms a strong foundation for an effective and sustainable learning experience for students. Consistency in applying learning and learning theories, such as behaviorism, cognitivism, constructivism, and humanism, helps educators in designing structured and directed learning. This allows students to develop a deep understanding of the subject matter and skills that are important for learning. In conclusion, the consistency of learning and learning theories in education is an important factor for achieving educational goals. By consistently applying learning theories, an intelligent and characterful generation can be created that is ready to build a brighter future for the nation.