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Arfak Chem: Chemistry Education Journal
Published by Universitas Papua
ISSN : 2615627X     EISSN : 26156288     DOI : https://doi.org/10.30862/accej.v5i1.368
Core Subject : Humanities, Science, Education, Social,
Humanities Chemistry Education Social Sciences
Arfak Chem: Chemistry Education Journal is a scientific journal, published by Chemistry Education Department, University of Papua. This journal is published 2 times in a year, June and December. This journal contains research results relating to the topic of education and chemistry teaching.
Arjuna Subject : Kimia(semua kategori) - Kimia (Lain-Lain)
Articles 93 Documents
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Qualitative analysis of cyclamate in iced tea using varying BaCl2 concentrations: A descriptive study in sekaran raya Aryati, Nur Indah; Ariyanti, Diva Fitria; Yolanda, Helen; Sa’diyah, Chalimatus; Amelia, Rizki Nor
Arfak Chem: Chemistry Education Journal Vol. 8 No. 1 (2025): Arfak Chem
Publisher : Universitas Papua, Manokwari, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30862/accej.v8i1.930

Abstract

Cyclamate is one type of artificial sweetener that is widely used in beverages. However, excessive consumption can hurt health. This study aims to determine the presence of cyclamate content in iced tea products sold in the Sekaran Raya area around the campus of Semarang State University. The method used was descriptive research through qualitative analysis in the Integrated Science Laboratory with the precipitation technique. Three samples of iced tea drinks and one positive control sample (with cyclamate added) were analyzed by adding barium chloride (BaCl2) reagent in an acidic atmosphere, with concentrations of 10% and 30%, respectively. The test results showed that one of the samples, iced tea sample RY, formed a white precipitate, indicating the presence of cyclamates, where 30% BaCl₂ produced more precipitate than 10% BaCl₂. This finding suggests that precipitation techniques with higher concentrations of BaCl₂ can improve the visibility of cyclamate detection. However, it should be noted that increasing the concentration of BaCl₂ is not always directly proportional to the identification quality because too high a concentration can cause interference and interfere with the clarity of the observation results.
Exploring the impact of artificial intelligence in chemistry teaching: A systematic review of empirical research Sari, Nur Indah; Ahmad, Fandi
Arfak Chem: Chemistry Education Journal Vol. 8 No. 2 (2025): Arfak Chem
Publisher : Universitas Papua, Manokwari, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30862/accej.v8i2.1083

Abstract

Chemistry education frequently struggles to foster a comprehensive understanding, often because it focuses too narrowly on macroscopic, submicroscopic, or symbolic representations. While Artificial Intelligence offers considerable potential to enhance learning, research specifically examining its impact on chemistry teaching remains scarce. This study aimed to identify, evaluate, and synthesize empirical literature on the effects of AI in chemistry teaching. This study was conducted in accordance with the PRISMA three sequential stages: 1) a comprehensive literature search in scientific databases utilizing keywords such as Artificial Intelligence, Chemistry Teaching, and Empirical Study/Research; 2) a selection process based on the inclusion and exclusion criteria; and 3) systematic data extraction. The literature review incorporated 13 empirical research articles published in Scopus- and Sinta-indexed journals. Findings consistently indicate that AI integration significantly impacts learner performance and instructional effectiveness by facilitating just-in-time, automated, and individualized feedback. Specific AI applications identified include generative tools for conceptual problem-solving, the utilization of ChatGPT/Bing Chat, gamified learning approaches, and AI assistants within remote laboratory settings. Nevertheless, this study highlights the inherent limitations of AI in addressing complex chemical content, alongside prevalent student concerns about AI accuracy, plagiarism, data privacy, and the potential for over-reliance on this technology.
The role of augmented reality in supporting deep learning within the merdeka curriculum: A systematic literature review in chemistry education Agussalim, Hastuti
Arfak Chem: Chemistry Education Journal Vol. 8 No. 2 (2025): Arfak Chem
Publisher : Universitas Papua, Manokwari, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30862/accej.v8i2.1111

Abstract

Chemistry education frequently faces challenges due to the abstract nature of chemical concepts, limited visual media, and insufficient student engagement. In contrast, the Merdeka Curriculum highlights the importance of deep learning, emphasizing conceptual understanding, scientific reasoning, and meaningful learning experiences. Augmented Reality (AR) offers promising affordances for addressing these issues through interactive, context-rich three-dimensional representations. This study employed a PRISMA-based Systematic Literature Review (SLR) of 12 empirical articles published between 2015 and 2025 in Scopus-indexed databases, major international publishers, and accredited SINTA journals. The findings reveal a marked increase in AR research in chemistry education between 2023 and 2025, with research and development (R&D) and quasi-experimental designs predominantly conducted at the senior secondary level. Across studies, AR consistently enhances conceptual understanding, multi-level representational competence, higher-order thinking skills, and student engagement. Moreover, AR aligns strongly with the pedagogical principles of the Merdeka Curriculum, particularly project-based learning, authentic assessment, differentiated instruction, and the development of the Pancasila Student Profile. These insights position AR as a strategic innovation for advancing deep and meaningful chemistry learning. Further research is recommended to investigate the long-term effects of AR and its integration within inquiry-based and project-based instructional models.

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