J-Selaras: A new Innovation Model for Rate Rationalization in Contract Documents

Mohd Nasir Saari, Prof. Madya Dr. Mustafa Man, Mohd Adza Arshad and Dr. Wan Aezwani Wan Abu Bakar
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Mohd Nasir Saari: Centre of Excellence for Engineering and Technology (CREaTE), Public Works Department Malaysia, Jalan Kemus, Simpang Ampat,78000 Alor Gajah, Melaka, Malaysia.
Prof. Madya Dr. Mustafa Man: Faculty of Computer Science and Mathematics, Universiti Malaysia Terengganu (UMT), 21030 Kuala Nerus, Terengganu, Malaysia.
Mohd Adza Arshad: Centre of Excellence for Engineering and Technology (CREaTE), Public Works Department Malaysia, Jalan Kemus, Simpang Ampat,78000 Alor Gajah, Melaka, Malaysia.
Dr. Wan Aezwani Wan Abu Bakar: Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin (UniSZA), Besut Campus, 22200 Besut, Terengganu, Malaysia.

International Journal of Research and Innovation in Social Science, 2024, vol. 8, issue 10, 1428-1436

Abstract: Effective rate rationalization plays a crucial role in modifying tender rates to determine equitable and rational contract amounts, particularly within the context of the construction industry in Malaysia to ensure that contractor prices do not exhibit any front-loading tendencies and establish equitable pricing for variations. Despite the importance of rate rationalization, the Malaysian construction industry grapples with various challenges in the domains of tendering and estimating. These challenges include the scarcity of precise historical data, project intricacy, time limitations, cost variations, restricted technology integration, and the competitive dynamics within the bidding environment. To address these challenges, this study introduces an innovative rationalization model that utilizes the Z-Score Altman model. This model aims to fine-tune the data and establish justifyable rates. and determine reasonable rates through meticulous data integration. Data integration, a widely accepted technique, facilitates smooth data conversion and sharing across diverse applications with different database formats and locations. The proposed model incorporates dynamic algorithms that systematically transfer data between application systems, accommodating various data formats, whether structured or unstructured. Integrating the Z-Score algorithm within the model efficiently filters out extraneous data within the Excel single-sheet file. This algorithm rapidly transfers data to multiple Excel sheets using the macro formulation, recognizing minimum and maximum values, calculating modified means, and employing cut-off analysis to narrow down the rates deemed most favorable. This research rigorously evaluates rates put forth by successful tenderers, staying within established parameters, and providing a durable algorithm that outlines the calculations and conditions guiding this thorough evaluation.

Date: 2024
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