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All Journal Jurnal Perikanan dan Kelautan Information System for Educators and Professionals : Journal of Information System Journal of Economic, Bussines and Accounting (COSTING) Alignment: Journal of Administration and Educational Management International Journal of Social Science, Educational, Economics, Agriculture Research, and Technology (IJSET) DEVOTE: Jurnal Pengabdian Masyarakat Global Journal Research of Social Science, Economics, and Management SUBSERVE: Community Service and Empowerment Journal Intechno Journal : Information Technology Journal Khidmat: Journal Community Service
Rahmat Hidayat
Universitas Terbuka
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Prediksi Kualitas Sambungan Las Robotik Menggunakan Random Forest dan Data Sensor Tegangan RAHMAT HIDAYAT
INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System Vol 10 No 2 (2025): INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS (Desember 2025)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Bina Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51211/isbi.v10i2.3778

Abstract

Menghadapi tantangan nyata di lini produksi, penelitian ini bertujuan menggantikan metode inspeksi las konvensional yang lambat dan rentan error. Inspeksi manual atau pengujian merusak kerap memakan waktu 2-3 hari per batch, menyumbang 15% biaya produksi, dan mengandung risiko human error 20-30%. Solusinya, kami kembangkan sistem prediksi real-time berbasis kecerdasan buatan yang “mendengarkan” proses pengelasan melalui sensor tegangan. Peneliti menganalisis 1.200 sampel las dari baja AISI 1020, merekam sinyal tegangan 10.000 kali per detik. Dari data ini, diekstraksi 24 “sidik jari digital” ciri statistik dan frekuensi yang mencerminkan kondisi pengelasan. Hasil las dikategorikan sebagai Baik, Porositas, atau Cacat Kritis berdasarkan inspeksi ultrasonik. Setelah menguji tujuh algoritma, Random Forest yang telah dioptimasi menunjukkan performa terbaik dengan akurasi 94,82%, hanya membutuhkan 23,4 milidetik untuk menganalisis satu sambungan. Ini mengungguli algoritma lain seperti Gradient Boosting (92,1%) dan Neural Network (90,7%). Sistem ini berpotensi merevolusi kontrol kualitas: mengurangi ketergantungan inspeksi manual hingga 70%, memangkas waktu inspeksi dari hari menjadi real-time, dan menurunkan biaya kualitas hingga 40%. Dengan demikian, penelitian ini tidak hanya membuktikan keampuhan machine learning, tetapi juga menawarkan solusi praktis yang siap diadopsi industri untuk meningkatkan efisiensi dan daya saing di era otomasi.
The Effect of Tax Supervision on Taxpayer Compliance in Submitting Annual Tax Returns at DGT Bali Regional Offices Ashari Nursetyo Nugroho; Rahmat Hidayat; Akadun
Journal Research of Social Science, Economics, and Management Vol. 4 No. 10 (2025): Journal Research of Social Science, Economics, and Management
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jrssem.v4i10.832

Abstract

Despite high tax revenue realization at Indonesia’s DGT Bali Regional Office, formal compliance in Annual Tax Return (SPT) submissions remains critically low (41.18%–44.93%), signaling a gap between enforcement and taxpayer adherence. This study investigates how tax supervision influences compliance, addressing regional disparities overlooked in prior literature.The research aims to analyze the effect of tax supervision on taxpayer compliance in SPT submissions, assessing perceptual and operational dimensions of supervision. A quantitative survey of 214 taxpayers (cluster random sampling) used Likert-scale questionnaires, analyzed via descriptive statistics and simple linear regression (SPSS v27). Tax supervision significantly improves compliance (46.8% contribution), with supervision perceived as effective overall (3.83/5) but weaker in measurement (3.34/5). Compliance scored highly (4.42/5), driven by formal compliance. The study underscores the need for enhanced measurement tools in supervision and explores uncharted factors (e.g., digitalization, socio-cultural influences) affecting compliance. It provides actionable insights for regional tax authorities to refine policies, bridging the gap between revenue targets and taxpayer engagement.
Co-Authors Abdul Rahman Akadun Andi Wijaya Arif Sugiono Asep Andri Astriyandi Ashari Nursetyo Nugroho Ayuning Budiati Dandan Haryono Dwi Mariska Farhan Aminulhaq Florentina Ratih Wulandari Guntur Bagus Pamungkas Guntur Bagus Pamungkas Gusti Nurdin Joko Tri Brata Moh. Syaiful Anwar Muhammad Mahdi Fi Diinillah Ovia Qadarsiki Rulinawaty Rulinawaty Shinta Permana Putri Sodikin Sodikin