cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Unang arifin
Contact Email
bcsies@unisba.ac.id
Phone
+6281214569091
Journal Mail Official
bcsies@unisba.ac.id
Editorial Address
UPT Publikasi Ilmiah, Universitas Islam Bandung. Jl. Tamansari No. 20, Bandung 40116, Indonesia, Tlp +62 22 420 3368, +62 22 426 3895 ext. 6891
Location
Kota bandung,
Jawa barat
INDONESIA
Bandung Conference Series: Industrial Engineering Science
Published by Universitas Islam Bandung
ISSN : -     EISSN : 28282132     DOI : https://doi.org/10.29313/bcsies.v2i2
Core Subject : Science, Engineering,
Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering
Bandung Conference Series: Industrial Engineering Science (BCSIES) menerbitkan artikel penelitian akademik tentang kajian teoritis dan terapan serta berfokus pada Teknik Industri dengan ruang lingkup, NASA-TLX, Alat Kualitas, Analisis SWOT, Analytical Hierarchy Process, Arsitektur Sistem Informasi Layanan Administrasi, Basis Data, Cetak biru Pelayanan, Failure Mode And Effect (FMEA), Fault Tree Analysis (FTA), First Come First Served, Framework for the Application of Systems Thinking (FAST), Hay Method, Human Resource Scorecard, Kuesioner 7 waste, Model tingkat aspirasi Quality Function Deployment (QFD), Model-driven development Six sigma, Multichannel Single Phase, NASA-TLX, Notasi kendall, Pelayanan, Pergudangan, Persediaan Sistem informasi, PIECES, Proses antrian, QFD (Quality Function Deployment) Lean manufacturing, Quantitative Strategic Planning Matrix (QSPM), Root Cause Analysys, Seven Tools, Sistem Antrian, Sistem Informasi, Strategi Pengembangan Model Driven, Stripping Obat Kualitas, Take Home Pay, Traffic Light System, TRIZ Kualitas, Work Sampling. Prosiding ini diterbitkan oleh UPT Publikasi Ilmiah Unisba. Artikel yang dikirimkan ke prosiding ini akan diproses secara online dan menggunakan double blind review minimal oleh dua orang mitra bebestari.
Arjuna Subject : Teknik (semua kategori) - Tenik Industri dan Manufaktur
Articles 1 Documents
 1 
Search results for , issue "499-508" : 1 Documents clear
Model Prediksi Pembentukan Blast Furnace Slag Berbasis Regresi Linear Berganda pada Industri Baja Sry Wahyuny Umar L; Setyawati Yani; Syamsuddin Yani
Bandung Conference Series: Industrial Engineering Science 499-508
Publisher : UNISBA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/bcsies.v6i2.24045

Abstract

Abstract. Blast furnace generates slag as a major by-product in the steel industry, affecting operational efficiency, flux consumption, energy requirements, and waste management. Variations in slag chemical composition contribute to fluctuations in slag formation, requiring a data-driven predictive approach to support process control. This study aims to develop a blast furnace slag formation prediction model using multiple linear regression based on key chemical composition parameters, including CaO, SiO₂, Fe, and Al₂O₃. The research data were obtained from blast furnace process observations during April 2026, consisting of 17 operational datasets. The analysis involved regression model development, significance testing, coefficient of determination evaluation, and comparison between actual and Predicted slag values. The results indicate that the developed regression model achieved an R² value of 0.9244, an adjusted R² value of 0.8969, and a Significance F value of 4.1296 × 10⁻⁶. The model successfully explains most variations in slag formation and demonstrates high agreement between actual and Predicted values. Multiple linear regression provides a potential predictive modeling approach for improving blast furnace operation control and supporting sustainable steel industry development. Abstrak. Blast furnace menghasilkan slag sebagai produk samping utama dalam industri baja yang berpengaruh terhadap efisiensi operasi, konsumsi flux, kebutuhan energi, dan pengelolaan limbah. Variasi komposisi kimia slag menyebabkan perubahan jumlah slag yang terbentuk sehingga diperlukan pendekatan prediktif berbasis data untuk mendukung pengendalian proses. Penelitian ini bertujuan mengembangkan model prediksi pembentukan blast furnace slag menggunakan regresi linear berganda berdasarkan parameter komposisi kimia CaO, SiO₂, Fe, dan Al₂O₃. Data penelitian diperoleh dari pengamatan proses blast furnace selama April 2026 dengan 17 data pengamatan. Analisis dilakukan melalui pembentukan model regresi, pengujian signifikansi, evaluasi koefisien determinasi, serta perbandingan nilai aktual dan prediksi. Hasil penelitian menunjukkan model regresi menghasilkan nilai R² sebesar 0,9244, adjusted R² sebesar 0,8969, dan Significance F sebesar 4,1296 × 10⁻⁶. Model mampu menjelaskan sebagian besar variasi pembentukan slag serta menunjukkan kedekatan tinggi antara nilai aktual dan prediksi. Pendekatan regresi linear berganda berpotensi diterapkan sebagai predictive modeling untuk mendukung optimasi operasi blast furnace dan pengembangan industri baja berkelanjutan.

Page 1 of 1 | Total Record : 1

 1 

Filter by Year

0000


Reset
Filter By Issues
All Issue Vol. 6 No. 2 (2026): Bandung Conference Series: Industrial Engineering Science Vol. 5 No. 2 (2025): Bandung Conference Series: Industrial Engineering Science Vol. 4 No. 2 (2024): Bandung Conference Series: Industrial Engineering Science Vol. 4 No. 1 (2024): Bandung Conference Series: Industrial Engineering Science Vol. 3 No. 2 (2023): Bandung Conference Series: Industrial Engineering Science Vol. 3 No. 1 (2023): Bandung Conference Series: Industrial Engineering Science Vol. 2 No. 2 (2022): Bandung Conference Series: Industrial Engineering Science Vol. 2 No. 1 (2022): Bandung Conference Series: Industrial Engineering Science Vol. 1 No. 1 (2021): Bandung Conference Series: Industrial Engineering Science 597-604 589-596 579-588 569-578 561-568 553-560 545-552 537-544 527-536 517-526 509-516 499-508 More Issue