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Life Cycle Assessment (LCA) Analysis Of Concrete Slab Construction For Estimating The Environmental Impact Annisa Nur Rakhmawati; Yatnanta Padma Devia; Indradi Wijatmiko
Rekayasa Sipil Vol 14, No 3 (2020)
Publisher : Department of Civil Engineering, Faculty of Engineering, University of Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.rekayasasipil.2020.014.03.10

Abstract

Global warming and air pollution become one of the environmental issues facing the world. the construction sector consumes about 40% of total global energy. Many strategies have been adopted to improve the efficiency of building construction to reduce material consumption and carbon emissions. One way to find out the environmental impact and carbon emissions produced is with a Life Cycle Assessment (LCA). This study aims to predict the environmental impact of concrete slab construction in two-story dwellings using the Life Cycle Assessment (LCA) approach of the material used with the help of software, namely Simapro 9.0. The scope of the study is the cradle to the grave. The results of the SimaPro 9.0 concrete plate construction analysis, especially in global warming are 1.02, E+07 kg CO2 eq. The biggest contribution to the manufacture of concrete slabs is the casting process with a value of 1.00, E+07 kg CO2 eq.
The Influence of Workforce Competence and Supervision Systems on Construction Project Productivity Rakhmawati, Annisa Nur; Khalilah Daud Isaac Makhmut; Eko Tjahjono; Ratna Marhaenita Widjaja
⁠International Journal of Sustainable Social Culture, Science Technology, Management, and Law Humanities Vol. 2 No. 2 (2025)
Publisher : Universitas Kristen Cipta Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71131/ypdent05

Abstract

The construction industry plays a strategic role in supporting national development, but low labor productivity remains a challenge, especially in medium-scale construction projects. Labor productivity is influenced by various factors, including competence and the effectiveness of the monitoring system. Although a number of previous studies have examined these two variables, the findings show inconsistencies, so further study is needed to confirm their contribution to construction project productivity. This study aims to analyze the effect of labor competence and the monitoring system on construction project productivity. This study uses a quantitative approach with an explanatory research type. A sample of 72 respondents was determined using purposive sampling from a population of 80 workers on the PT Y boarding house construction project in Malang City. Data collection was carried out through questionnaires, observations, and documentation. Data analysis used multiple linear regression with the support of validity, reliability, and classical assumption tests. The results showed that both workforce competency and the supervision system had a significant effect on project productivity. The supervision system variable showed the most dominant effect with a significance value of 0.000 and a regression coefficient of 0.538, while workforce competency had a significance value of 0.014 with a regression coefficient of 0.412. Simultaneously, both variables have a significant effect on productivity with an R-Square value of 0.620, which means that 62% of productivity variation can be explained by these two variables.
Analisis Luas Daerah Rawan Banjir Kota Medan Berbasis Sistem Informasi Geografis (SIG) Indri Triawati; Annisa Nur Rakhmawati; Wahyu Nursamhuda
Journal of Innovative and Creativity Vol. 5 No. 3 (2025)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/joecy.v5i3.4540

Abstract

Medan City is an urban area that frequently experiences flooding during the rainy season. This study aims to analyze the extent of flood-prone areas in Medan City using Geographic Information System (GIS) technology. The research method was carried out through a georeferencing process on flood-prone area maps and the creation of shape files to calculate the area affected by flooding. The data used included flood vulnerability parameters and water inundation maps, which were then processed using QGIS software. The analysis results show that areas with a low level of flood vulnerability cover an area of ​​approximately 2,844 hectares (10.72%), areas with a moderate level of vulnerability cover 8,642.4 hectares (32.6%), and areas with a high level of vulnerability cover 14,632 hectares (55.2%). These findings indicate that more than half of Medan City's area is categorized as moderate to severe flood prone. Therefore, more effective mitigation measures and spatial planning management are needed to minimize the risk of future flood disasters.