Introduction

In this modern era, governments carry out large-scale development so that areas can transform into advanced regions and be able to keep up with current developments.[1] One of the infrastructures that supports this rapid growth is the toll road construction project.[2] In the implementation of highway construction projects, many problems and obstacles are often encountered, one of which is delays, with 38% of projects in Indonesia experiencing discrepancies between the actual execution time and the planned schedule.[3]

The delay in the implementation of the highway construction project will impact the postponement of a series of other objectives that follow. This delay constraint also occurs in National Strategic Projects (PSN), one of which is the Serang – Panimbang Toll Road Section 3 (Cileles – Panimbang) Development Project in the Banten Province area. The project is intended to support accessibility to the Special Economic Zone (SEZ), mainly in the tourism sector in the Tanjung Lesung area. The project has been ongoing since August 2022 and is being carried out by three main contractors through a Joint Operation (KSO) led by Sino Roads and Bridge Group Co. Ltd. (SRBGC), with participation from PT. W., and PT. A. The respective work portions in this KSO system are sequentially as follows: SRBGC (55%) – WIKA (22.5%) – ADHI (22.5%).[4] The project was originally scheduled in the initial contract to be completed within 720 calendar days. Over time and with several contract amendments, the execution period became 1,374 calendar days. The change in the execution period, with an addition of 654 calendar days, is based on work that could not be completed at several points in the three contractor work areas. This will consequently impact the delay in project completion and increased costs.[5]

In the construction project implementation phase, it is very important to carry out planning, coordination, and management to mitigate or avoid risks that are likely to occur. The risks that often occur during the implementation phase include time overruns, which are influenced by stakeholder, material, and external factors, resulting in losses for the contractor, especially when the agreed contract is a lump sum.[6] Obstacles and challenges in the implementation of development will certainly affect productivity, so a risk management study must be conducted by performing risk analysis and addressing potential risk impacts that affect construction performance. Therefore, this study was conducted to determine the effect of limited involvement of various parties in managing risk during the implementation of highway construction projects.[7]

Method

In the preparation of this final project proposal, the research object is the Serang – Panimbang Toll Road Construction Project Section III (Cileles – Panimbang) on the STA 74+275 – STA 77+387 stretch, which is 3.1 km long. The study, with this project as its object, aims to analyze the risk management system during the implementation phase of the related project in order to identify the risks causing project delays by determining the most dominant risks. Furthermore, from these risks, appropriate mitigation measures are determined to minimize the existing risks.

Figure 1. Location of Research Object of Project Archive Data, 2025

Research variables are risk factors based on several references that support the related research. In general, research variables are grouped into 2 (two) types, namely:

a. Exogenous variable / independent reliable.

b. Endogenous variable / dependent variable.

The research focused on the causes of risks that impact delays in the construction project implementation phase. It is based on literature sources, experience, and a developed list of risks. The existing data were analyzed through a qualitative-descriptive approach using interviews, observations, and literature-documentation studies. The results of the data were described to identify the severity and impact of these risk events. In this study, the following variables are included:

Table 1. Research Variables

Results and Discussion

At this stage, data processing is carried out using the House of Risk (HOR) method. Data processing begins by summarizing the questionnaire results on the severity scale (impact) and occurrence scale identification. The questionnaires were filled out by respondents from a population based on the location of the research object, which is the contractors implementing the Serang – Panimbang Toll Road Project Section 3A (Cileles – Panimbang), categorized by major categories such as positions/roles including project manager, deputy project manager, project engineering, project commercial, project finance, project production, and senior staff. The determination of the risk scale is based on the research by Anityasari & Wessiani (2011) as follows.

Table 2. Likert Scale of Severity (Impact)

Table 3. Likert Scale Occurrence (Probability)

1. House of Risk (HOR) Fase 1

Phase I of the House of Risk (HOR) is a stage for conducting a risk event analysis, where the risk priorities are identified so that risk mitigation planning can be carried out in the next phase. In this study, Phase I of HOR was conducted through the identification of risk events based on a review of existing studies, and then the identification of risk agents was carried out by distributing questionnaires to respondents according to predetermined criteria.[8]

The scale measurement in the questionnaire was conducted on the risk impact scale (severity) to determine the potential impact of the risk that may arise from the risk event. In addition, a measurement of the likelihood of the risk occurrence (occurrence) was also carried out based on the risk-triggering factors (risk agents) to interpret the frequency of the risk agents emerging. Then, a scale measurement of the correlation between the severity and occurrence scores was conducted. Risk agents with the highest ARP value will become risk priorities for mitigation efforts or solutions, thereby reducing the risk level.[9]

Based on the identification results from several literature reviews of previous studies and also referring to the risk register archive documentation of the Serang – Panimbang Toll Road Project Section 3A (Cileles-Panimbang), 18 risk events were identified, which were then measured for impact scale (severity) through the distribution of questionnaires to respondents. The impact scale measurement ranges from 1-5, where a score of 1 represents a very low impact level and a score of 5 represents a very high impact level. The conclusion of the impact scale assessment for each risk event is based on the mode (the most frequently occurring number) in the severity assessment. The conclusions of the severity assessment from the respondents' questionnaires are presented in the following table.

Table 4. Severity Assessment Results

2. Identification of Risk Triggers (Risk Agent)

The identification of risk triggers is based on the potential risk events. The stage of identifying risk triggers is carried out by integrating risk event factors through a focus group discussion (FGD) with several experts from different backgrounds to obtain diverse perspectives. Based on the results of the focus group discussion with experts, the discussion data is then processed using N-Vivo software to determine the statements that are most frequently expressed. [10]

From the FGD results, 18 risk-triggering factors (risk agents) were also obtained. The next step involved measuring the likelihood of occurrence scale by distributing questionnaires to respondents. This likelihood scale measurement ranges from 1 to 5, where a score of 1 represents a very rare occurrence from now, and a score of 5 represents a near-certain chance of occurrence.[11] The conclusion of the assessment of the likelihood scale for each risk agent is based on the mode (the most frequently occurring number) in the occurrence assessment. The conclusions of the occurrence assessment from the respondent questionnaire are presented in the following table.

Table 5. Occurrence Assessment Results

3. Identification of the Correlation Scale of Risk Events and Risk Agents

The relationship between risk events and risk severity based on severity and occurrence scores is then identified using a scale of 0, 1, 3, or 9 to indicate the correlation of each aspect.[12] In Edy Suyanto's (2022) research, the value of this correlation scale is based on an approach using Quality Function Deployment (QFD) with the following criteria and integrated with risk scale levels:

Table 6. Correlation Scale Table and Risk Scale

Based on the correlation scale table, the data in Table 6 below represents the correlation scale values of risk events and risk agents. The scale numbers were obtained after conducting interviews with the project management.

Table 7. Table of Correlation Scale between Risk Event and Risk Agent

4. Phase 1 HOR Calculation

The calculation stage in HOR Phase 1 is to calculate the Aggregate Risk Potential (ARP). To facilitate this calculation, it is carried out using a table and combines data from risk events, risk agents, and the correlation scale of each risk variable. The results of the aggregate risk potential calculation are used as the basis for determining the risk priority potential factors to be mitigated in HOR Phase 2. The ARP value is calculated using the following formula:

Description:

ARP_j : Aggregate Risk Potential

Oj : Occurance risk agent

Si : Severity risk event

Ri : Nilai korelasi

One example of calculating ARP according to the formula for risk event (Ej) E5 is:

Known: O = 5

Si = 3

Ri = 9

Solution: ARP= Oj . Σ Si . Ri

= 5 . (3.9)

= 135

Hasil perhitungan ARP tahapan House of Risk (HOR) Fase 1 disajikan dalam tabel 8 berikut :

Tabel 8. Hasil Perhitungan House of Risk (HOR) Fase 1

5. Evaluation of House of Risk (HOR) Phase 1 Calculations

This stage is the final step in data processing using the House of Risk (HOR) Phase 1 method. This evaluation stage is carried out based on the results of the recapitulation of the aggregate risk potential (ARP) calculation. The recapitulated ARP values are sorted by the highest value to be used as cumulative percentages in the preparation of a Pareto diagram. The higher the ARP value, the higher the priority for that risk agent to be mitigated earlier. The following is a recapitulation and percentage results based on the ARP value calculations in Table 9.

Table 9. Recapitulation of Aggregate Risk Potential (ARP) Values

According to Grosfeld-Nir, Ronen, & Kozlovsky (2016), a good Pareto chart is one in which about 20% of the attribute components carry 80% of the weight. It can thus be concluded that 80% of the risk of loss is caused by 20% of these essential factors.[13] By prioritizing the 20% risk factors, the impact of the 80% risk can be managed and mitigated early. In this study, a Pareto diagram is used to identify the main risk agents that will become a priority in the management and mitigation of risks. The formulation of risk management, handling, and mitigation efforts as a form of preventive action will be carried out in the HOR Phase 2 stage.

Figure 2. Pareto Diagram of Risk Agents

From the Pareto diagram, the results for the selected risk agents show that there are 3 risk factors. Since there are 4 main variable factors in this study, 4 risk agent factors were taken based on the Pareto diagram. Thus, the order of the risk agents is as follows:

Table 8. Selected Risk Agent

Based on the results of the selected risk agent in the HOR Phase 1 stage, processing was then carried out with HOR Phase 2 to plan risk management and mitigation so that potential risks and their impacts can be minimized.

a. House of Risk (HOR) Phase 2 In this stage of House of Risk (HOR) Phase 2, mitigation management efforts (PAk) will be carried out as the most effective and efficient preventive action to be implemented in the field according to actual conditions. [14] To determine the most effective and efficient mitigation efforts, a Focus Group Discussion (FGD) was conducted with selected experts from various fields and experiences in civil engineering.

b. Identification of Mitigation Preventive Action Identification of risk mitigation actions as preventive steps is carried out based on the results of risk dominance analysis in the HOR Phase 1 stage. The identification of preventive action (PAk) steps is conducted through discussions (FGD) with experts. The results of the FGD are processed using N-Vivo software to determine the statements most frequently expressed as forms of preventive action.[15] The results of the word frequency recap from the N-Vivo software for each dominant risk factor in each variable can be visually seen in the following diagram:

Figure 3. Word Frequency Recap for PA 1

Figure 4. Word Frequency Recap for PA 9

Figure 5. Word Frequency Recap for PA 14

Figure 6. Word Frequency Recap for PA 15

Thus, based on the results of the Focus Group Discussion (FGD) and the processing of HOR Phase 2 data using N-Vivo software to determine risk mitigation steps in managing and minimizing risk-triggering factors (risk agents), the following results were obtained:

Table 9. Mitigation Efforts Preventive Action

6. Identification of Risk Agent Correlation and Preventive Action

The identification of the correlation scale values between risk agents and preventive actions is used to determine how strong the relationship is between each risk trigger factor and its corresponding preventive action. The correlation scale provisions used are as shown in Table 12 below:

Table 10. Correlation Scale of Risk Agent and Preventive Action

After determining the correlation scale between each risk trigger factor and the preventive action steps, the determination of the difficulty degree scale (Dk) in its implementation in the field was also carried out. This scale determination was done together with the project management, who act as the highest decision-makers in the project, using direct interview methods. Measurement of the difficulty degree scale value is conducted after the correlation scale between risk agents and preventive actions for each variable is known. The measurement of the difficulty degree scale value is applied according to the provisions in Table 11 below:

Table 11. Difficulty Degree Scale Values (Dk)

Based on the provisions for determining the correlation scale and difficulty level value, the results of the correlation scale and difficulty level scale are obtained as shown in Table 12 below.

Table 12. Correlation Results of Risk Agent and Preventive Action

7. Calculation House of Risk (HOR) Fase 2

After the correlation scale value and the degree of difficulty are known, the Total Effectiveness (Tek) for each mitigation step is then calculated. The results of the Total Effectiveness (Tek) calculation are used to calculate the Effectiveness to Difficulty Ratio (ETD). The determination of the ETD value will be used to identify the priority ranking of each variable from preventive actions to be implemented earlier while still considering the degree of difficulty and effectiveness. The calculation of the Total Effectiveness (Tek) value uses the following formula: T_ek = Σ j · ARP_j x Ejk (2)

Description= Tek = Total Effectiveness

ARPj = Aggregate Risk Potential – Agent j

Ejk = Risk Agent j

One example of calculating Tek according to the formula for risk agent (Ai) A15 is: Known = ARP= 431

Ejk = 9

Asked = Tek ..?

Answer=

After obtaining the Total Effectiveness (Tek) value, the Effectiveness to Difficulty Ratio (ETD) is calculated using the following formula:

(3)

Description = ETDk = Effectiveness to Difficulty Ratio

Tek = Total Effectiveness

Dk = Degree of Difficulty

One example of ETDk calculation according to the formula for risk agent (Ai) A15 is:Given= Tek= 3879

Dk= 5

Asked= ETDk ..?

Answer =

In more detail, the calculation of the ETDk value in House of Risk (HOR) Phase 2 can be seen in the following Table 13:

Table 13. Results of House of Risk (HOR) Phase 2 Calculation

8. Evaluation of House of Risk (HOR) Phase 2 Calculations

Based on the results of the House of Risk (HOR) Phase 2 calculations and the ranking results from the Effectiveness to Difficulty Ratio (ETDk) calculations, the priority preventive actions are identified as steps for managing and controlling risk mitigation to reduce both the triggers and the impact of the risk.

Table 14. Recapitulation of Preventive Action (PAk) Ranking

Conclusion

Based on the results of research conducted using the House of Risk method and data processing with N-Vivo software, several final results and conclusions were obtained as follows: Identification of delays in the implementation time across all work areas of the Serang – Panimbang Toll Road Construction Project Section 3 (Cileles – Panimbang) indicated a work time extension of up to 654 calendar days. After the initial risk identification stage was carried out and correlated with the project risk register data for the three work areas and validated with experts and respondents, several factors causing delays in the implementation of the toll road construction project were identified, totaling 18 risk-triggering factors and 18 risk-causing factors. From these 18 factors, they were then categorized into 4 variable categories, namely (X1) Technical & Operational Risk, (X2) Project Management Risk, (X3) Environmental Risk, and (X4) External Risk. Based on the results of the research using the HOR Phase 1 method, the main factors causing delays that impact the execution time of highway construction projects were identified. In the HOR Phase 1 method, four main risk-triggering factors (top risk agents) were identified in order: (A1) The design of the work during planning does not align with the results of the soil investigation during the implementation phase, (A15) Part of the funding comes from foreign loans, (A9) Uncertainty of technical and administrative data, and (A14) The work location cannot be executed due to land issues.

The strategy steps for risk management against probabilities/opportunities that could reduce the risk of project schedule delays are planned using the Phase 2 HOR method based on the results of Phase 1 HOR. At the Phase 2 HOR stage, planning efforts are carried out to manage and mitigate risks by correlating them based on the correlation scale and the degree of difficulty in field implementation. From the determination of this correlation scale through interviews with representatives from the project management team, the highest priority as a risk mitigation strategy was obtained, namely (PA 1) Conducting validation of the initial design using soil investigation data from an independent geotechnical consultant to achieve accurate and realistic results, with monitoring and controlling efforts including setting minimum geotechnical data standards in accordance with SNI 8460:2017, SNI 1726:2019 and specifications, and using a design validation checklist against soil parameters (SPT, CPT, shear strength, settlement). and conduct cross-reviews with the internal team and independent consultants before the final design; (PA 14) Verify legality before starting work, integrate force majeure clauses and time adjustments into the contract, and ensure transparency regulations related to compensation with monitoring and controlling efforts; coordinate intensively with the project owner regarding land acquisition updates, as well as periodically monitor and control work that cannot be carried out due to land issues; (PA 9) Prepare pre-contract, technical, and administrative documents earlier with monitoring and controlling measures; assign PICs for each type of document and internal deadlines before the tender schedule; and (PA 15) Synchronizing the cash flow disbursement schedule and reviewing loan clauses and exchange rate risks by periodically monitoring and controlling the rupiah exchange rate, and assigning a team appropriate to the contract field.