This study focuses on developing a nano zinc oxide (ZnO) catalyst with fly ash (FA) as a support material for converting kapok seed oil (KSO) into biodiesel. This research aims to study the preparation of nano ZnO/FA solid catalysts and the catalyst's reactivity towards kapok seed oil biodiesel (KSOB) products. The catalysts were synthesized using a modification of the Stober process, which is the co-precipitation, impregnation, and precipitation step co-occurred. The catalyst is prepared on base condition using sodium hydroxide with a solvent of methanol and zinc chloride as a raw material. FA waste was effectively modified with zinc oxide particles to create a high-performance ZnO/FA composite catalyst. Under optimal stoichiometric NaOH and 60% ZnO, the resulting material achieved a remarkable specific surface area of 14.8 m²/gram, indicating its potential for enhanced catalytic activity. The prepared catalyst of nano ZnO/FA achieved successful methanolysis of KSO, with a maximum FAME yield of 61.09% attained at 65°C after 5 hours of reaction time, using a 3% catalyst dose and a KSO: methanol molar ratio of 1:15. The initial success of nano ZnO/FA with kapok seed oil paves the way for further development towards robust catalysts specifically tailored for low-grade oil conversion.

This study aimed to develop a conceptual model of the role of differentiation strategy and organizational citizenship behavior in mediating the effect of transformational leadership on the performance of private high schools in Pekanbaru. The sample was 140 principals and vice-principals of private high schools in Pekanbaru. The data obtained were processed using Structural Equation Modeling Partial Least Square (SEM PLS). The findings in this study are that transformational leadership has a positive effect on the performance of private high schools in Pekanbaru, differentiation strategy and organizational citizenship behavior mediate the effect of transformational leadership on the performance of private high schools in Pekanbaru. The most effective pathway to affect the performance of private high schools is the mediating pathway of organizational citizenship behavior on the effect of transformational leadership on the performance of private high schools.

Sustainable tourism is known as an effort to prevent the negative impacts of tourism development by considering economic, social and environmental aspects. Sustainable tourism development is very important to be used as a reference in managing tourism destinations. The large tourism potential in the Bali Province has been inventoried by the Provincial Government of Bali by establishing a tourism area. However, in its development, several designated tourism areas cannot develop optimally and tend to experience a decrease in the quality and quantity of tourist visits. This paper presents transformation pathways toward sustainable tourism development in tourism areas. The general objective is to determine strategies that can be pursued in the development of tourism areas. The specific objective is to develop the best policies and scenarios in the development of tourism areas. This research was conducted in the Soka Tourism Area in Bali Province, Indonesia, which is the only strategic tourism area in Tabanan Regency, which has great potential but has not been able to develop optimally. The data obtained from the focus group discussion, as a data collection method will be analyzed using the MULTIPOL method. The results of the research show that the development of sustainable tourism areas can be carried out by preparing a clear and measurable framework. Promotion, preparation of cross-sector programs and tourism management training activities are needed as priority programs. On the policy, it is necessary to carry out effective planning as an optimal policy involving all stakeholders. In addition, the “Progressive Transformation” and “Integrated Transformation” scenarios can be considered to achieve sustainable tourism development. This study can be an important input for stakeholders in determining policies for the development of tourism areas in the research locations and can be applied in other areas that have similar characteristics.

Logistics’ significance in international trade is being noted more and more frequently. This study was conducted to analyze the influence of logistics performance on trade volume between the Republic of Korea (ROK) and member states of the Association of Southeast Asian Nations (ASEAN) in order to identify the areas of the Indonesian logistics industry that require improvement to increase trade volume between Indonesia and the ROK. This study focuses on Indonesia, Vietnam, Malaysia, Thailand, and the Philippines, which are actively responding to the reconfiguration of the global value chain (GVC). The report also includes Cambodia, Laos, and Myanmar, which can be viewed as potential GVC competitors of Indonesia due to their considerable manufacturing growth potential. Based on the gravity model, which explains trade volume between regions, this study looked into the effect of the logistics performance index (LPI) of these ASEAN nations on trade with the ROK by analyzing panel data. This study utilized previously published (secondary) data to derive new outcomes. Most of the statistical data were extracted from the World Bank database, IHS Markit, and Euromonitor. The results show that an improvement of LPI can lead to growth in the trade volume between ROK and ASEAN Nations including Indonesia. The study’s insights suggest which logistical areas Indonesia should focus on developing in order to boost trade with ROK and obtain a competitive edge in the GVC reconfiguration.

The research aimed to know the influence of long-term relationships, information sharing, Cooperation, and integration process in partial on the supply chain effectiveness of the EPC Steam Power Plant project in the Province of North Sulawesi. It was also to know whether enterprise risk management moderates the influence, long-term relationship, information sharing, Cooperation, and integration process toward supply chain effectiveness. The employees who became the sample in the supply chain activities of the steam power plant project in North Sulawesi were 250 people, 149 of whom were proportionally from the project owner. The research uses the data analysis technique using Structural Equation Modelling-Partial Least Square. The result of the study indicated that long-term relationships, information sharing, Cooperation, and integration process partially have a positive and significant influence on supply chain effectiveness. In addition, enterprise risk management proved to moderate the impact of information sharing. Still, it needed to moderate the effect of a long-term relationship, Cooperation, and integration process on the supply chain effectiveness of the EPC Steam Power Plant Sulut-3 project.

In today's rapidly changing economic landscape, financial resilience has become increasingly important especially for public sector organizations. This study investigates the impact of e-government adoption and social support on individuals' financial resilience in Indonesia, with a focus on the mediating role of financial management skills. A quantitative research methodology was employed, and 348 complete and suitable questionnaires from individuals in the financial department in local government in Indonesia were analyzed using SmartPLS 4.0 software. The results indicate a significant relationship between e-government adoption and financial management skills, suggesting that digitizing government services contributes to improved financial resilience. Additionally, social support was found to have a positive impact on financial management skills, supporting the notion that social networks provide resources and support for financial well-being. Financial management skills were also found to be significantly associated with financial resilience, indicating that individuals with strong financial management skills are better equipped to adapt to changing circumstances. While the mediating effect of financial management skills between e-government adoption and financial resilience was not significant, it was significant in the relationship between social support and financial resilience. These findings provide insights into the factors that enhance financial resilience in an increasingly digitized society and inform strategies to promote financial well-being in Indonesia.

Several Multivariate Adaptive Regression Spline (MARS) approaches are available to model categorical and numerical (especially continuous) data. Currently, there are other numerical data types—discrete or count data—that call for specific consideration in modeling. Additionally, spatially correlated count data is frequently observed. This has been seen in the case of health data, for example, the number of newborn fatalities, tuberculosis patients, hospital visitors, etc. However, currently no structurally consistent nonparametric regression and MARS model for count data incorporating spatial lag autocorrelation. The SAR-MAGPRS estimator (Spatial Autoregressive - Multivariate Adaptive Generalized Poisson Regression Spline) is developed to fill this gap. Although it can be applied to different count distributions, the estimator was developed in this study under the assumption of a Generalized Poisson distribution. This paper provides an information-theoretic framework for incorporating knowledge of the spatial structure and non-parametric regression models, especially MARS for the count data types. Moreover, the proposed method can assist in modeling the number of diseases while health policies are being developed. The framework presents an application of the Penalized Least Square (PLS) method to estimate the SAR – MAGPRS model.

As a capital market investment, stocks have risks that must be managed. Therefore, investors should consider the returns and risks of investment products. This study aims to estimate the risk of insurance companies' loss when investing. The method used to estimate the level of risk is Value at Risk (VaR) based on Extreme Value Theory (EVT). The data used is secondary data in the form of daily stock closing prices from two insurance companies, AXA General Insurance and BRI Insurance, from January 2016 to January 2022. The data were used to estimate the risk value according to the EVT principle. As a result, Insurance AXA General Insurance, with 5.91% liquidity, has the lowest VaR value with a 99% confidence level, while BRI Insurance has 5.04%. We concluded from these results that AXA General Insurance has a lower investment risk. It means that each company has a different risk value. Therefore, investors should know these risk factors when choosing a company.

Emerging maritime cyber threats put Indonesia's marine technology-based systems at risk This study aims to determine the dimensions and analysis of risk assessment in maritime cyber security based on 3D models in the Indonesian sea area. A statistical descriptive qualitative method approach supported by the Analytical Hierarchy Process (AHP) and Technique for Order by Similarity to Ideal Solution (TOPSIS) methods were used in this study. Risk analysis in maritime cybersecurity has 3 (three) main criteria: Threat, Vulnerability, and consequence. Based on the results of 3D risk analysis, the six dimensions of MCS are identified as having a level of risk at Very Low and Low Risk. The highest risk value is obtained by the dimension of Cyber security-related company procedures (D2) (0.368) and the lowest risk value is Ship's systems readiness (D3) (0.048).

The MEWMA chart is one of the traditional multivariate charts which are widely employed in inspecting the quality of manufacturing and services. This chart is created through monitoring the small shifts of mean vectors of variable quality characteristics. Often in practice, the measurement of a quality characteristic produces uncertain, incomplete values, so that ambiguous numbers are obtained. In this condition, a neutrosophic-based control chart can overcome the problem resulting from the ambiguous data. The paper’s objective is to construct a new multivariate monitoring scheme based on a neutrosophic chart, namely the neutrosophic Multivariate EWMA (NMEWMA). Furthermore, the performance of the new multivariate monitoring scheme is evaluated in detecting process shifts employing the Average Run Length (ARL) and Standard Deviation Run Length (SDRL). This control chart is an innovation in the quality monitoring of uncertain data. The research result obtained indicates that the NMEWMA chart performs better than the MEWMA in finding the small mean shifts as well as in the real case application.