Sewage Treatment Model with Friendly Technology on Commercial Ships to Reduce Pollution

The quantitative research method uses SEM analysis with SmartPLS software to obtain an analysis model of sewage treatment with environmentally friendly technology on commercial ships to reduce pollution based on the implementation of Annex IV MARPOL 1973/1978, the application of occupational health safety procedures, and sewage processing technology. SmartPLS-SEM was chosen because it is suitable for predictive and exploratory models, accommodates complex structural relationships, and does not require normally distributed data. The model estimation was conducted using the PLS algorithm with a path-weighting scheme. SmartPLS software was employed to run the analysis.

With the quantitative research method, the number of samples is determined based on the number of indicators in all research variables. The indicators of this study total 20 indicators, namely the implementation variables annex IV of MARPOL 1973/1978, amounting to 4 indicators, the variables of the implementation of occupational health safety procedures amounting to 4 indicators, the processing technology variables 4 indicators, the safety and health variables 4 indicators, and the variables of environmentally friendly sewage treatment amounting to 4 indicators. So the number of samples set for quantitative analysis of SmartPLS-SEM amounted to 150 crew members. he recommended sample size for SmartPLS-SEM ranges from 100 to 200, depending on the number of indicators and model complexity [21]. Samples were obtained by a random sampling method on the crew of commercial ships in Indonesian waters. The number of samples in this study is 150 ship crews, consisting of commercial ship crews, including passenger ship crews and cargo ship crews (general cargo ships, container ships, bulk carriers, tanker ships) in June, July, and August 2025.

This research consists of 5 research variables, consisting of exogenous variables, namely the implementation of annex IV of MARPOL 1973/1978, sewage processing technology, the application of occupational health safety procedures, and endogenous variables, including crew safety and health, and environmentally friendly sewage processing. The research questionnaire with scoring according to the Likert scale was distributed to 30 crew members first to be tested for validity and reliability with the IBM SPSS program. Statistics. These validity and reliability tests served as preliminary instrument screening, while the main validity and reliability assessments were conducted through the SmartPLS-SEM outer model analysis using outer loadings, composite reliability, rho_A, Average Variance Extracted (AVE), discriminant validity with three approaches, namely the Fornell-Larcker criteria, cross-loading, and Heterotrait-Monotrait ratio (HTMT).

Variables, indicators, and results of the validity test of research instruments are shown in Table 1.

Based on Table 1 of the results of the validity test of the research instrument, it can be explained that all variable indicators of sewage treatment research with environmentally friendly technology on commercial ships to reduce pollution obtained the results of the Pearson correlation value or r calculation ≥ r table. The number of respondents was 30 (N) with a table r value of 0.361, so that all indicators of the research instrument were declared valid because the Pearson correlation value or r was calculated ≥ r table and p value < 0.05. After the validity test of the research instrument was carried out, a reliability test was also carried out, the results of which are shown in Table 2. In the SmartPLS-SEM stage, reliability was further confirmed using composite reliability and rho_A, which are more appropriate for SmartPLS-SEM measurement models.

Table 1. Results of the validity test of sewage treatment research instruments with environmentally friendly technology on commercial ships to reduce pollution

Source: Primary data, 2025

Table 2. Results of the reliability test of sewage treatment research instrument with environmentally friendly technology on commercial ships to reduce pollution

Source: Primary data, 2025

Based on Table 2, it can be explained that all research variables obtained a Cronbach's Alpha value ≥ 0.70, so that it can be stated that the research instrument is declared reliable. After the research instrument was declared valid and reliable, it was then distributed to the research respondents of 150 merchant ship crews. The answers from the distribution of the questionnaire, which is a quantitative research instrument from 150 merchant ship crews, were then tabulated, including both the characteristics of the respondents, the characteristics of the ships where the respondents worked, to be analyzed with statistical descriptive methods in terms of frequency using the SPSS program. The characteristics of the 150 crew respondents can be shown in Table 3.

Of the 150 research respondents, all worked on commercial ships spread across 10 commercial ships. The characteristics of the commercial ship where the study was conducted, which included the name of the ship, type of ship, shipping area, deadweight ton (DWT), and the number of research respondents taken on the ship, are shown in Table 4.

Furthermore, data from 150 respondents were analyzed using SmartPLS-SEM. The indicators were scored according to the Likert scale, and then the outer and inner models were assessed. The outer model describes how each indicator relates to its latent variable using convergent validity (outer loadings > 0.70, composite reliability ≥ 0.70, rho_A ≥ 0.70, AVE > 0.50) and discriminant validity assessed through Fornell–Larcker criteria and HTMT ratios. The statistical significance of all outer and inner model parameters was evaluated using the bootstrapping procedure with 5,000 subsamples, as recommended in SmartPLS-SEM.

The inner model was evaluated using collinearity statistics (VIF < 5 indicates no multicollinearity), R-squared (0.25 = weak; 0.50–0.75 = moderate; >0.75 = strong), and hypothesis testing based on the significance of path coefficients. All p-values and t-statistics reported in the results section were generated from the SmartPLS bootstrapping procedure.

Table 3. The characteristics of respondents

Source: Primary data, 2025

Table 4. Boat characteristics

Source: Primary data, 2025

Based on the results of this study with SmartPLS-SEM analysis, it was found that the implementation of annex IV MARPOL 1973/1978 had a direct effect on the treatment of sewage with environmentally friendly technology on commercial ships to reduce pollution coefficient by 0.273, with a P Values of 0.000 this is consistent with previous research which stated that compliance with international regulations is the main foundation in protecting the marine environment [9, 11]. The results of this study also add empirical evidence that regulatory compliance has an impact on crew health safety and health directly safety and health with a coefficient of 0.369, with a P Value of 0.000, and regulatory compliance also has an indirect impact through an increase in the safety and health of crew members by 0.092 with a P Value of 0.016. This shows that regulations not only function as a legal instrument, but also as a learning mechanism that increases crew awareness of health and safety risks in waste treatment.

The positive influence of sewage treatment technology on environmentally friendly treatment to reduce pollution by 0.226 with P Values confirms the importance of adopting technology according to the size of the vessel, operating area, and international standards. In line with previous literature [11, 15], the use of modern technologies such as biological treatment and UV disinfection is effective in reducing the levels of pathogens and pollutants. This finding indicates that vessels employing UV disinfection, MBR systems, or biological treatment technologies, all of which comply with MEPC.227(64) effluent requirements, achieve higher environmental performance. These technologies reduce pathogens, solids, and chemical residues, resulting in safer and more sustainable waste discharge practices. The novelty of this study is the discovery of the effect of technology not only on the quality of waste treatment, but also on crew safety of 0.316 with P values of 0.001 and the indirect influence of sewage treatment technology on sewage treatment environmentally friendly technology on commercial vessel to reduce pollution through the variable between crew safety and health of 0.079 with P values of 0.023. In other words, the proper application of technology reduces exposure to hazardous chemicals and the risk of work accidents, resulting in a dual effect on environmental and occupational health aspects.

The application of occupational health safety procedures has been proven to have a significant effect on crew safety, with a coefficient of 0.271 with a P value of 0.000, as well as the application of occupational health safety procedures to sewage processing with environmentally friendly technology to reduce pollution by 0.213, with a P value of 0.001. These findings reinforce previous research that stated that safety culture contributes to crew behavior in managing waste [15, 16]. The results of this study show that without the support of the implementation of strict occupational health safety procedures, even advanced technology will not be optimal in preventing marine pollution. This means that regulations and technology must be integrated with human-based risk management.

This study proves the mediating effect of safety and crew health on the relationship between regulations, wage processing technology, and the application of occupational health safety procedures with waste treatment with environmentally friendly technology on commercial ships to reduce pollution. A significant indirect effect value (P values < 0.05) indicates that improved crew welfare and health strengthen the effectiveness of the application of environmentally friendly technology. This shows that a holistic approach, which focuses not only on regulation or technology, but also on crew working conditions, is key to the successful implementation of sustainable waste treatment systems on commercial ships.

This research has theoretical implications, namely, from the academic side, this research expands the theory of environmental compliance and maritime safety by adding an integrative perspective between international regulations (Annex IV MARPOL), human factors (the implementation of occupational health safety procedures and crew health safety), and technology. The structural model obtained (R Square = 0.601 for the main endogenous variable) shows that the combination of regulatory, technological, and occupational safety factors can explain more than 60,1 % of the variability of sewage treatment with environmentally friendly technologies to reduce pollution. This reinforces the literature that multidimensional approaches are more effective than single approaches.

For the shipping industry that affirms that the MARPOL Regulation must be enforced consistently, with stricter port supervision, investment in environmentally friendly technologies such as biological treatment systems, membranes, and UV disinfection must be prioritized not only on cruise ships, but also on commercial ships, crew occupational health safety training needs to be expanded so that crew understand the risks of waste treatment and be able to operate the technology safely. Governments and shipping companies need to build a maritime safety culture that is integrated with environmental protection policies.

The novelty of this research lies in the development of an integrative analysis model that connects Annex IV MARPOL, the application of occupational health safety procedures, and processing technology with the health safety of crew members as mediators. Most of the previous research focused on garbage management or the application of technology on cruise ships, while this study expanded the scope to commercial ships by involving human factors as the key to the success of environmentally friendly sewage processing.

The data supporting the findings of this study are available from the corresponding author upon reasonable request. The dataset includes anonymized responses and does not contain any personal or confidential information.