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All Journal Matriks Teknik Sipil Journal of Engineering Science and Technology Management
Panuwun, Rizky Tulus
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Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Materials Science & Nanotechnology

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KOMPONEN BIAYA YANG MEMPENGARUHI ESTIMASI BIAYA PENINGKATAN JALAN PROVINSI Handayani, Fajar Sri; Sugiyarto, Sugiyarto; Panuwun, Rizky Tulus
Matriks Teknik Sipil Vol 3, No 3 (2015): September 2015
Publisher : Program Studi Teknik Sipil FT UNS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/mateksi.v3i3.37293

Abstract

Jalan provinsi merupakan infrastruktur yang sangat vital yang menghubungkan ibukota provinsi dengan ibukota kabupaten atau antar ibukota kabupaten/kota. Pembangunan jalan provinsi dibutuhkan estimasi biaya konstruksi sebelum pelaksanaan fisik dilakukan dan memerlukan analisis detail dan kompilasi dokumen perkiraan harga pekerjaan maupun dokumen penawaran. Model biaya konstruksi jalan dibutuhkan agar kegiatan estimasi dapat terlaksana dengan baik supaya dapat memberikan estimasi secara cepat dan akurat. Penelitian menggunakan metode Cost Significant Model (CSM) dengan persamaan regresi linier berganda yang dikembangkan oleh Poh dan Horner dalam mengestimasi biaya konstruksi jalan provinsi. Identifikasi kegiatan-kegiatan konstruksi jalan provinsi yang ada di Jawa Tengah dilakukan dengan mengumpulkan data mengenai biaya konstruksi jalan provinsi dalam 3 tahun terakhir (2012 - 2014) untuk menghasilkan suatu model biaya konstruksi. Hasil analisa didapatkan komponen biaya yang paling signifikan berupa komponen biaya lapis pondasi dan biaya perkerasan.
Comparative Study of Cost Significant Model and Artificial Neural Networks Methods for River Retaining Wall Cost Estimation in Grobogan Regency Panuwun, Rizky Tulus; Pratiwi Adi, Henny; Soedarsono, Soedarsono
Journal of Engineering Science and Technology Management (JES-TM) Vol. 5 No. 2 (2025): September 2025
Publisher : Journal of Engineering Science and Technology Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jestm.v5i2.306

Abstract

Grobogan Regency in Central Java Province has a high level of flood risk, so the construction of river retaining walls is an important infrastructure for disaster mitigation. The estimation of construction costs at the early planning stage plays a crucial role in budgeting and technical decision-making. This study aims to compare the accuracy and consistency of two cost estimation approaches: Cost Significant Model (CSM), based on multiple linear regression, and Artificial Neural Networks (ANN) using the backpropagation algorithm. The dataset comprises 42 Bill of Quantity (BoQ) documents (37 training data and 5 testing data), with additional validation conducted through field surveys at seven proposed retaining wall locations. Model performance was evaluated using Mean Absolute Percentage Error (MAPE) to measure accuracy and Bland–Altman Plot to assess consistency. The results indicate that CSM achieved a MAPE value of 1.70%, which is lower than that of ANN, which yielded 2.50%. The Bland–Altman analysis also shows that CSM demonstrates higher consistency, as the linear regression approach allows prediction beyond the training data range, making it more adaptive to actual conditions. In contrast, ANN tends to be constrained within the normalized training data range, reducing its flexibility when encountering new data variations. Therefore, it can be concluded that CSM performs better than ANN in terms of accuracy and consistency in estimating the construction cost of river retaining walls in Grobogan Regency.
Co-Authors Handayani, Fajar Sri Pratiwi Adi, Henny Soedarsono Soedarsono Sugiyarto Sugiyarto