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DIAMOND LIKE CARBON (DLC) COATING ON CARBON STEEL WITH PLASMA TECHNIQUES FOR GAS PIPES Yahya, Ilham Nur Dimas; Rudyardj, Djony Izak; Ady, Jan
Indonesian Applied Physics Letters Vol. 1 No. 2 (2020): Indonesian Applied Physics Letters - Desember 2020
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v1i2.23446

Abstract

A study about coating on carbon steel by plasma technique aims to determine the variation of time and pressure on the hardness and corrosion strength of a material. The material used in this research was carbon steel with carbon chest of 0.245%. This carbon steel was a plasma technique process with a temperature of 300oC and various pressure variations, such as 1.2 mbar; 1.4 mbar; 1.6 mbar; 1.8 mbar; And 2.0 mbar. The highest hardness was found at 1.8 mbar pressure, which was 161.7 VHN. Then set with a temperature of 300oC and a pressure of 1.8 mbar and a time variation, which were 1 hour; 1.5 hours; 2 hours; 2.5 hours; 3 hours. The largest hardness value was obtained at 3 hours with a hardness value of 161.7 VHN. Then the corrosion test obtained the optimum value at 2 hours with a corrosion value of 0.69 mpy. This was because on the surface of carbon steel there was a layer of Diamond Like Carbon (DLC).
Attitudes Towards an AI-Augmented Pedagogy in Enhancing English Academic Writing Proficiency: Empirical Evidence from Electrical Engineering Students Indriati, Titin; Veniati, Veniati; Trionanda, Stevanus; Yahya, Ilham Nur Dimas; Manto, Manto
Paedagoria : Jurnal Kajian, Penelitian dan Pengembangan Kependidikan Vol 17, No 2 (2026): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/paedagoria.v17i2.37865

Abstract

This quantitative survey study investigates the perceptions of Electrical Engineering students toward the integration of Artificial Intelligence (AI)-augmented pedagogy in improving English academic writing proficiency. A total of 48 students majoring in electrical engineering at Bangka Belitung State Manufacturing Polytechnic participated in the study. Data were collected through close-ended questionnaires. The data were analyzed using SPSS 25, revealing strong internal consistency (Cronbach’s α = 0.92. The findings revealed that students’ overall attitudes toward the integration of AI were strongly positive (M = 79.69, SD = 11.07), with all three attitudinal dimensions namely cognitive (M = 40.33, SD = 5.18), affective (M = 20.37, SD = 2.97), and behavioral (M = 18.98, SD = 3.34) which also falling within the positive category. These findings reflect the students’ preparedness to engage in technology-supported language learning. Moreover, the study concludes that AI-augmented pedagogy holds significant potential to strengthen students’ academic writing proficiency, particularly in technical and vocational education. Hence, it is recommended that AI tools be integrated into writing instruction while simultaneously fostering the students’ critical digital literacy and sense of ethical awareness.