ANALYSIS OF THE INFLUENCE OF LOW BIDDING FACTORS ON QUALITY AND COST PERFORMANCE IN PROCUREMENT OF SMALL CLASS PIER PROJECTS IN THE GOVERNMENT ENVIRONMENT

: Since COVID 19 pandemic hit Indonesia, many small harbor contractors have been forced to provide low bid prices ( < 80% HPS) for harbor auctions sourced from APBN funds in 2019-2022. Even though the bid price given is low, many contractors are able to complete the work according to the quality and price required in the contract agreement. This research analyzes the factors that cause contractors who have successfully completed the work, dare to provide low bids in the auction process. From the data obtained an processed using SEM-PLS method, it is know that the company’s internal condition factors have the most significant influence with a path coefficient of 0.464. The biggest indicator of the company’s internal condition is the company’s need to achieve the minimum sales/ profit target in one year, with a path coefficient value of 0.866. Financial characteristic factors also have a significat influence with a path coefficient value of 0.223. Meanwhile the technical characteristics factors has an influence with a path coefficient value of 0.213.


INTRODUCTION
The State Budget (APBN) is a manifestation of state financial management that aims to prosper its citizens as much as possible (Subekan & Iskandar, 2021).The State Budget (APBN) is a state financial instrument aimed at prospering citizens, in accordance with Article 23 of the Constitution 45 (Sugianto & Siagian, 2023).The government, especially in the era of President Joko Widodo, focuses on infrastructure development to increase prosperity and reduce development gaps.The Ministry of Transportation is mandated to build ports/docks at 65 crossing locations and 306 sea locations from 2015-2019 (Kou & Shi, 2024;Wu & Tham, 2023).
In addition to explaining in detail about the method of auctioning construction work within the government, Perlem LKPP No.12 of 2021 also regulates further evaluation for prospective providers who provide low bids (Del Río & Kiefer, 2023;Smith, 2002;Tjan et al., 2023).That is an offer with a value below 80% of the Self-Estimated Price (HPS) prepared by the Commitment Making Officer (PPK) (Negara, 2022).This further evaluation is important to be carried out so that the Auction Working Group (POKJA) and KDP can ensure that prospective suppliers can really complete the work in question, according to the expected quality and time, with an unreasonable budget (Pakasi, 2019).Based on research (Kurniati & Supriyatna, 2022), the percentage of < 80 HPS offers by contractors at the Ministry of PUPR increased slowly from 2015 to 2019 (7.28% to 11.92%) and increased sharply since 2020 (32%) and 2021 (43.71%).
The phenomenon of < 80% HPS quote, called low bid, was researched by (Oetomo a et al., 2015) and identified 6 factors: job characteristics, company external, internal company, bid terms, project finance, and employment contract (Olatunji et al., 2023).Similar research by (UNTOROYONO, 2012) highlights internal, external, and regulatory factors as the main influences of low bidding.(Dewi & Susetyo, 2022) add that the success of low-bid contractors is related to the supply of materials themselves, allowing low-price quotes without sacrificing quality (Shelton, 2018).The focus of this research is the government tender for the construction of a small class pier, where the pier is a structure in the port (Panayides et al., 2017).The size of the tender is adjusted to the qualifications of the business entity, and the small class dock has a project value of ≤ Rp15,000,000,000 (AUTHORITY, 2021;Bradley, 1980).
In order to achieve this goal, a literature study is conducted by detailing related research themes, such as factors of low bid prices on construction projects in the government environment, factors underlying contractors in bidding or participating in construction project tenders, and dock construction projects.The variables contained in this literature will be the basis for conducting a preliminary survey to gain an in-depth understanding of these factors (Shaw & Coles, 2004).

RESEARCH METHODS
This study adopts a quantitative descriptive approach focusing on the factors influencing the submission of low bids by suppliers in small-class dock construction projects within the Indonesian government (Jenkins, 2022).Preliminary data were obtained from secondary sources, such as journals and past research, to form the basis of the phase 1 questionnaire (Fairley et al., 2021).This questionnaire is given to expert respondents with the aim of identifying variables relevant to the study.After analysis and validation, a stage 2 questionnaire was created and directed to expert respondents to explore the relationship between these variables and the type of auction that occurred (Mengist et al., 2020).
The study population includes the entire core workforce involved in the Small Class Wharf Construction work package funded by the State Budget from 2019 to 2022, with low price offers (<80% HPS) and successfully completed by the Executing Contractor.The sample was selected through a purposive sampling method with inclusion criteria involving participation in the work package and successful completion.The minimum sample size required, based on Slovin's formula, is 48 respondents.
The data analysis process involves validity tests, multiple correlations, reliability tests to evaluate the reliability of questionnaires, and multivariate analysis.SEM-PLS analysis is used to thoroughly examine the relationship between variables.Literature studies and preliminary surveys become the basis for the selection of research variables.The survey involved expert interviews and the distribution of questionnaires to parties involved in the dock project as the main respondents.Quantitative data were collected through questionnaires, literature studies, and secondary data.Data analysis involves rating techniques, multivariate analysis, and SEM-PLS analysis to achieve research objectives.

RESULTS AND DISCUSSION
The statistical hypothesis in the questionnaire validity test is shown as follows: H0: The questionnaire statement on the variable indicator is invalid H1: Questionnaire statement on indicator valid variable The statistical hypothesis is said to reject H0 if the r value is calculated > r table or P-Value < α which means that the questionnaire statement on the variable indicator is said to be valid.The number of samples obtained in this study was 48 respondents, so that the free degree obtained was 48-2=46 and the level of significance (α) used in this study was 0.05.Based on this information and Appendix #, it was obtained that the r value of the table in this study was 0.285.The results of data processing with SPSS software are shown in Appendix # and the validity test results on variable X and variable Y for all indicators are respectively shown in Table 1  Based on Table 3 above, it shows that based on the answers of 48 respondents from 25 questionnaire question indicators, a Cronbach Alpha's score of 0.968 was obtained.Cronbach's Alpha value is greater than 0.7.These results show that the questionnaire that has been made is reliable and can be used in this study.The results of descriptive statistical analysis based on respondents' answers to all indicators were processed using the help of SmartPLS software and shown in Based on Table 4 respondents rated the variable indicator with the lowest score between 1-3, the median ranged from 4-5, and the highest score was 5. Indicators X4.2 (Proximity of the implementing company's relationship with the supplier of dock work materials) and X4.3 (Proximity of the implementing company's relationship with the supplier of equipment owners) have the highest average score of 4.417.In contrast, the indicator X1.5 (Term of employment in 1 fiscal year) has the lowest average score of 3.792.In variable Y, the indicator Y1.1 (Low bid price if <80% HPS) has the highest average score of 4.042, while Y1.Table 5 above shows that the outer loading value is generated.Indicators on a variable that has an outer loading of less than 0.7 must be removed from the research model and reconstruct validity test analysis is carried out.The outer loading results obtained in Table 5 show that there is no outer loading value less than 0.7.Thus, indicators that can measure the variable to be measured have been declared constructively valid.Table 6 above shows the results of construct reliability tests for each variable based on Cronbach's Alpha, rho_A, Composite Reliability, and AVE values according to the output results that have been processed using SmartPLS software.It was obtained that Cronbach's Alpha and rho_A values of all variables above 0.7, Composite Reliability of all variables above 0.7, and AVE of all variables above 0.5.H.The value of cross loading based on the results of analysis using the help of SmartPLS software is shown in   The R-Square value resulting from structural model testing shows the structural model's R-Square value to the low bid price (Y) of 0.909, indicating that 90.9% of low bid price variability is influenced by variables of technical characteristics of the work (X1), financial characteristics of the work (X2), internal conditions of the implementing company (X3), and external conditions of the company (X4).An adjusted R-Square of 0.900 confirms that 90.0% of low bid price variability is significantly influenced by variables in the model, including technical characteristics of the work, financial characteristics of the work, internal conditions of the executing company, and external conditions of the company.The evaluation criteria show that the research model has high substance, and an R-Square value above 0.5 signifies the acceptance of the model without multicollinearity problems, according to the classification of Chin (1996) in Sarwono (2016).The test results of the path coefficient are shown based on the results of data processing using SmartPLS software shown in Table 8 below: The R-Square in the structural model to the low bid price (Y) is 0.909, indicating that 90.9% of the variability of the low bid price is influenced by the technical characteristics of the job (X1), the financial characteristics of the job (X2), the internal conditions of the executing company (X3), and the external conditions of the company (X4).A total of 9.1% variability was influenced by other factors that were not modeled.Adjusted R-Square (0.900) shows that 90.0% of low bid price variability is influenced by variables in the model that are significant, including the technical characteristics of the work, the financial characteristics of the work, the internal conditions of the executing company, and the external conditions of the company.The remaining 10.0% variability is influenced by other factors that are also significant.The criteria of R-Square and Adjusted R-Square values indicate that this model has high substance, with R-Square values above 0.5 reflecting the acceptance of the model without multicollinearity problems, according to the classification of Chin (1996) in Sarwono (2016).The statistical 2 (Low bid price if the evaluation of price fairness by the Election Working Group) has the lowest score of 3.979.These results indicate respondents' agreement with factors affecting the low bid price, including the technical characteristics of the work, the financial characteristics of the work, the internal conditions of the executing company, and the external conditions of the company Page 262 Asian Journal of Engineering, Social and Health Volume 3, No. 2 February 2024

Table 1 . Variable X Validity Test Results No
:Based on Table1above, it shows that all indicators in variable X have a calculated r value greater than table r or a P-Value value smaller than α=0.05 which concludes the test results that all indicators in variable X are valid.
Variable r calculate r table P-Value (Sig.)Conclusion

Table 2 . Variable Y Validity Test Results
Based on Table2above, it shows that all indicators in variable Y have a calculated r value greater than table r or a P-Value value smaller than α=0.05 which provides a conclusion from the test results that all indicators in variable Y are valid.The results of the questionnaire reliability test using the SPSS Program can be seen in Table3below Page 260 Asian Journal of Engineering, Social and Health Volume 3, No. 2 February 2024

Table 6 . Results of Construct Validity and Reliability Evaluation
Table 7 below:

Table 7 . Cross Loading Values
Table7above shows the cross loading values for each indicator for all variables.Table7shows that the highest cross loading value for each indicator of something variable is measured.Thus, each indicator on all variables has met the discriminant validity test.