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Identification Of Vegetable Fat Formulations on Hardness, Cleaning and Conditioning of Solid Soap Hulyadi, Hulyadi; Muhali, Muhali; Prayogi, Saiful; Azmi, Irham; Firdaus, Laras; Suryati, Suryati; Mirawati, Baiq; Gargazi, Gargazi
Journal of Authentic Research Vol. 4 No. 2 (2025): December
Publisher : LITPAM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/ty850306

Abstract

This study aims to examine the effect of varying vegetable oil compositions (coconut, palm, and olive) on the physical and chemical qualities of solid soap, specifically in terms of hardness, cleansing ability, and moisture content. This study used a laboratory experiment with five soap formulas combining various vegetable oil compositions. The results showed that the formula with a combination of 60% coconut oil and 40% palm oil produced the soap with the highest hardness, while the formula with a combination of 60% coconut oil and 40% olive oil provided the best moisture content. The soap with a composition of 60% coconut oil and 40% palm oil also demonstrated better cleaning ability, thanks to the lauric acid content in coconut oil, which has antibacterial properties. This study recommends the use of a combination of coconut and palm oils to produce soap with the best quality in terms of hardness and cleansing ability, and coconut and olive oils for soap with greater skin moisturizing properties. It is hoped that this research will contribute to the development of the natural soap industry in Indonesia, reduce dependence on imported raw materials, and increase the competitiveness of natural soap products in the global market.
Analysis of the Role of Algorithms in the Analysis of Organic Molecular Structures: A Study of Formal Charges and Their Reactivity Muhali, Muhali; Hulyadi, Hulyadi; Gargazi, Gargazi; Azmi, Irham; Bayani, Faizul
Empiricism Journal Vol. 6 No. 4: December 2025
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/q58j9193

Abstract

This study aims to identify students' competency in understanding the formal charge and reactivity of organic molecules through algorithm-based learning and mathematical formulations. A quasi-experimental pretest–posttest design was used with Chemistry Education students who had taken the topic of chemical bonding and Lewis structures. Essay and multiple-choice tests were used to measure the accuracy of Lewis structures, formal charge calculations, charge symbol interpretation, and reactivity predictions. The pretest results showed an average student score of 32.4, while the posttest score increased to 74.1, with an N-gain of 0.62 (moderate–high category). Students showed significant improvement in identifying reactivity centers (electrophilic/nucleophilic) and linking charge distribution to structural stability. The application of algorithms also strengthened their ability to visualize electronic structures, particularly in the context of sp3and sp3 hybridization. Computational chemistry simulations helped students develop stronger symbolic and predictive representations of chemical reactions. This study concludes that the integration of algorithms and symbolic approaches in learning effectively improves students' conceptual and computational literacy in organic chemistry.
A Systematic Review of Threshold Concepts in Higher Education: Characteristics, Learning Barriers, and Pedagogical Interventions Firdaus, Laras; Dewi, Ika Nurani; Primawati, Sri Nopita; Hulyadi, Hulyadi; Sabrun, Sabrun; Azmi, Irham
International Journal of Essential Competencies in Education Vol. 4 No. 2 (2025): December
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/qerb8q19

Abstract

This systematic review synthesises peer-reviewed empirical and conceptual research on threshold concepts (TC) in higher education published between 2015 and 2025. The review aims to examine how threshold concepts are theorised, operationalised, and empirically investigated across disciplinary contexts, with particular attention to their defining characteristics, associated learning difficulties, and pedagogical implications. Following a rigorous process of database searching, screening, and eligibility assessment, a total of 26 studies were included, comprising 11 peer-reviewed journal articles and 15 articles reporting empirical studies. The analysis integrates qualitative, quantitative, and mixed-methods studies to generate three key contributions: (1) a refined synthesis of TC characteristics as epistemic and, in some cases, ontological turning points in learning; (2) a structured categorisation of learning challenges associated with threshold crossing, including cognitive, affective, and contextual dimensions; and (3) an overview of pedagogical approaches designed to support learners during liminal phases. Findings indicate that TC consistently facilitate transitions from surface understanding to disciplinary ways of knowing, although their forms and manifestations vary across fields. While pedagogical interventions increasingly acknowledge the necessity of learning difficulty, robust longitudinal evidence remains limited. The review concludes with practical indicators for educators, and methodological recommendations, especially the need for longitudinal study, mixed methods design, and clearer operational criteria to strengthen future research and curriculum design.
Pelatihan Pemanfaatan ChatGPT dan Scite.ai untuk Meningkatkan Kualitas Penulisan Artikel Pengabdian Hunaepi, Hunaepi; Sibua, Sulami; Asy’ari, Muhammad; Ikhsan, Muhammad; Kesuma, Dadang Warta Candra Wira; Aminullah, Aminullah; Prayogi, Saiful; Kurnia, Nova; Mirawati, Baiq; Azmi, Irham; Hidayati, Rospin; Afrilyana, Maya
Nuras : Jurnal Pengabdian Kepada Masyarakat Vol. 6 No. 1 (2026): January (In Progress)
Publisher : Lembaga Pendidikan, Penelitian, dan Pengabdian Kamandanu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/nuras.v6i1.614

Abstract

This community service activity aims to improve the competence of lecturers at the Faculty of Culture, Management, and Business, Mandalika University of Education, in writing quality community service articles through the use of artificial intelligence technology, specifically ChatGPT and Scite.ai. The method used was an interactive workshop based on direct practice, equipped with a pre-test, delivery of theoretical materials, practice using AI, post-test, and reflection sessions. The analysis results showed a significant increase in post-test scores compared to the pre-test, with the majority of participants' N-gain being in the medium to high category. Participants were also able to produce draft community service articles with good to very good quality categories based on the assessment rubric. The level of participant satisfaction with the materials, methods, and implementation of the workshop was in the high category, indicating the success of the training approach used. This activity also contributed to the achievement of the SDGs, especially the goals of Quality Education (SDG 4), Innovation and Infrastructure (SDG 9), and Partnership (SDG 17). This training can be replicated as a model for increasing lecturer capacity in the context of digital transformation of higher education.