Ahmad Fauzi
Universitas Negeri Semarang

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Pengaruh Parameter Pemakanan Terhadap Kekasaran Permukaan ST 40 pada Mesin Bubut CNC Ahmad Fauzi; Wirawan Sumbodo
Jurnal Dinamika Vokasional Teknik Mesin Vol. 6 No. 1 (2021): April
Publisher : Department of Mechanical Engineering Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/dinamika.v6i1.38114

Abstract

Material ST 40 yang digunakan dalam pembuatan poros roda mobil listrik, harus memiliki kekasaran permukaan yang baik. Karena poros nantinya akan dirangkai pada komponen lain yaitu bearing. Tujuan penelitian ini yaitu untuk mengetahui dan menganalisis pengaruh kecepatan potong, kecepatan asutan, dan kedalaman pemakanan terhadap kekasaran permukaan dengan menggunakan mesin bubut CNC. Metode penelitian ini menggunakan metode eksperimen. Variasi kecepatan potong yang diteliti yaitu 90, 120, 150 m/menit. Kecepatan asutan 0,15; 0,2; 0,25 mm/rev. kedalaman pemakanan 0,25; 0,5; 0,75 mm. penelitian ini menggunakan bahan ST 40, pahat CNMG 120408-MA, dan mesin bubut CNC Fanuc Oit Leadwell. Nilai rata-rata kekasaran permukaan paling baik diperoleh pada interaksi variabel kecepatan potong 150 m/menit, kecepatan asutan 0,15 mm/rev dan kedalaman pemakanan 0,25 mm sebesar 1,034 μm. Dan kekasaran permukaan paling kasar diperoleh pada interaksi variabel kecepatan potong 90 m/menit, kecepatan asutan 0,25 mm/rev, dan kedalaman pemakanan 0,75 mm sebesar 10,594 μm.An electric car wheel axle using ST 40 materials must have good surface roughness due to its contact with bearings. This study aims to identify and analyze the effect of cutting speed, feed rate, and depth of cut on the surface roughness of the axle machined using a CNC lathe. The research employs an experimental method. The varied machining parameters are cutting speeds (90, 120, 150 meters per minute), feed rate (0.15, 0.2, 0.25 mm/rev) and depth of cut (0.25, 0.5, 0.75 mm). This study uses ST 40 material, CNMG 120408-ma cutting tool, and CNC Fanuc OiT lathe. The best result of average surface roughness value is 1,034 μm (lower is better), obtained at a variable interaction of 150 m/min cutting speed, feed rate of 0.15 mm/rev, and depth of cut 0.25 mm.
Rasch evaluation of matched positively and negatively worded CTS items among high school students Ahmad Fauzi; Hartono; Sunyoto Eko Nugroho; Arif Widiyatmoko
Indonesian Journal of Educational Development (IJED) Vol. 7 No. 2 (2026): August 2026
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) Universitas PGRI Mahadewa Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59672/ijed.v7i2.7023

Abstract

Instruments composed of items worded in the same direction may be vulnerable to response bias. This study evaluated a modified Computational Thinking Scale (CTS) comprising 19 matched pairs of positively and negatively worded items. An instrument-development design adapted from ADDIE was used. The study population comprised science-track senior high school students in the Surakarta Residency. The sample included 393 Grade XI students from three purposively selected schools. Data were collected using a 38-item, five-category self-report questionnaire. Five experts assessed content validity, yielding coefficients of 0.80–0.95 and a mean of 0.89. Responses were analyzed using the Rasch model in Winsteps 5.7.3.0. Cronbach’s alpha and person reliability were 0.66, with person separation of 1.40, whereas item reliability was 1.00 and item separation was 14.67. Response categories showed ordered observed averages and Andrich thresholds, with outfit MNSQ values of 0.91–1.07. All items met the primary outfit MNSQ criterion, ranging from 0.82 to 1.21. Three algorithmic-thinking items showed statistically significant but small gender DIF contrasts of 0.30–0.35 logits. The hypothesis was partially supported because the instrument showed acceptable item-level functioning but limited person-level discrimination. Future studies should examine wording effects, matched-pair equivalence, dimensionality, and local dependence in broader, more diverse samples.