Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Indonesian Journal of Science and Technology Jurnal Pendidikan: Teori, Penelitian, dan Pengembangan
Minghat, Asnul Dahar Bin
Unknown Affiliation
Computer Science & IT Education Environmental Science

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
The Price Dynamics of Hand Sanitizers for COVID-19 in Indonesia: Exponential and Cobweb Forms Machmud, Amir; Minghat, Asnul Dahar Bin
Indonesian Journal of Science and Technology Vol 5, No 2 (2020): IJOST: VOLUME 5, ISSUE 2, 2020
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v5i2.24431

Abstract

This study aims to analyze the impact of the COVID-19 pandemic on changes in handsanitizer prices in Indonesia. This study is motivated by the increasing demand for handsanitizers which has had an impact on price ratings. The method used is an explanatory survey with an exponential form approach for the demand function and Linear Cobweb Form for the supply function. The structure of the hand sanitizer market is assumed to be a perfectly competitive market. The results of the study indicate that despite changes in prices, the numerical analysis shows that prices are stable. The entry and exit of companies in the market does not affect price stability. This finding implies that after the pandemic the prices of handsanitizers will return to normal, so producers and consumers must remain rational.
A Descriptive Analysis of AI Competence and Teaching Performance among Pre-Service Automotive Engineering Teachers in Vehicle Diagnostic Learning Effendi, Muhammad Idris; Purnomo, Purnomo; Sutadji, Eddy; Firdausia, Fadliyanti; Minghat, Asnul Dahar bin
Jurnal Pendidikan: Teori, Penelitian, dan Pengembangan Vol. 11, No. 5
Publisher : citeus

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The rapid advancement of Artificial Intelligence (AI) has transformed the automotive industry, particularly in vehicle diagnostics, which increasingly relies on data-driven and intelligent systems. This shift necessitates that students in Automotive Engineering Education not only possess technical skills but also demonstrate AI competence and effective teaching performance. This study aims to analyze the level of AI competence and teaching performance among students in the context of vehicle diagnostic learning. A descriptive survey research design was employed involving 87 students as respondents. Data were collected using structured questionnaires measuring dimensions of AI competence (AI literacy, AI tool utilization, AI-based problem solving, and AI integration) and teaching performance (lesson planning, instructional delivery, classroom interaction, technology use, and learning evaluation). Data were analyzed using descriptive statistics, including mean, percentage, standard deviation, and score categorization. The findings indicate that students generally demonstrate a high level of AI competence, particularly in AI literacy and AI tool utilization, although AI integration remains at a moderate level. Similarly, teaching performance is categorized as high in lesson planning, instructional delivery, and classroom interaction, but relatively lower in technology integration and learning evaluation. These results reveal a gap between technological competence and its pedagogical implementation. In conclusion, while students are technologically prepared, their ability to integrate AI effectively into teaching practices remains limited. The findings highlight the need for strengthening AI-integrated pedagogical competencies and provide an empirical basis for developing AI-TPACK-based learning models in vocational education.
Co-Authors Amir Machmud, Amir Eddy Sutadji Effendi, Muhammad Idris Firdausia, Fadliyanti Purnomo Purnomo