Risk Management Based on NPV-at-Risk: A Case Study in Floating Solar Power Plant Project

There are some unpredicted factors in floating solar power plants that can affect the investment return value. This research aimed to develop an NPV-at-risk based risk management analysis on the floating solar power plant. This research proposed six-staged solutions: communication and consultation, context assignment, risk identification, risk analysis, risk evaluation, and risk mitigation. This study took place in a floating solar power plant in Indonesia. This research showed that some unpredicted risks, such as irradiation, operation and maintenance costs, inflation, and interest rate, could contribute to the investment return. This procedural proposal could be applied in the management of the income realization based on the income projection.

Comparing Total Cost of Ownership of Electric and Conventional Motorcycles in Indonesia

The adoption of Electric Vehicles (EV) is one of the solutions to reduce emission problems. In Indonesia, the government targets 2.1 million Electric Motorcycles (EM) ownership in 2025. One of the keys to encouraging the EV Indonesian market is vehicle cost analysis, like Total Cost of Ownership (TCO). This study developed a TCO model to compare EM with Conventional Motorcycles (CM) in Indonesia. Data were collected from surveys and information from stakeholders. The proposed TCO model considered a battery replacement cost, which influenced the resale value of the vehicle. As a result, the TCO of EM had a more economical value than CM of 12% (IDR 3 million) on low mobility, 16% (IDR 4 million) on medium mobility, and 18% (IDR 5.5 million) on high mobility. In addition, several scenarios were also analyzed as a study to consider providing subsidies ownership motorcycles in Indonesia.

Solving Just-in-Time Single Machine Scheduling with Variable Discrete Speed Machine using Hybrid NSGA-II

Due to industrialization and population growth, increasing energy demand can lead to energy scarcity because non-renewable resources are primarily used as energy sources. In addition, carbon dioxide gas, the waste of industrialization, can harm the environment. Therefore, environmentally friendly methods are encouraged in the industrial environment as energy preservation and climate change mitigation. This research discusses just-in-time single machine scheduling that takes into account energy consumption. In this research, energy consumption depends on the machine’s speed. The objectives are minimizing the just-in-time (JIT) penalty (the sum of weighted earliness/tardiness) and energy consumption. This research proposed a hybrid NSGA-II with a local search to solve the multi-objective scheduling problem. Thus, solving the JIT single-machine scheduling problem considers energy consumption to conserve energy and increase production efficiency. Numerical experiments demonstrated that the hybrid NSGA-II with local search is more effective than the standard NSGA-II in solving the problem. Therefore, decision-makers can use the scheduling model to select alternative solutions that consider energy and the environment without sacrificing efficiency.

A MILP Model for Water Level Sensor Placement with Multi-Sensor and Multi-Disaster Areas

A water level sensor is critical to measure water levels at strategic points in the river. The sensor location directly impacts the quality of the collected data sent to the flood early warning system. To prevent and minimize the risk of flooding, it is crucial to determine the optimal locations for water level sensor placement. This research proposes a Mixed-Integer Linear Programming (MILP) model for water level sensor placement considering multi-sensor and multi-disaster areas. In addition, this model was applied in a case study in Tikala River, Manado, Indonesia. The results indicated that all disaster areas could be covered by at least one single sensor. A sensitivity analysis was performed by running the model under several different budget scenarios. When the budget increases, the number of sensors and the coverage performance are getting larger. Thus, the proposed MILP model was able to determine the optimal locations for sensor placement under a limited budget.

The Moth-Flame Optimization Algorithm for Flow Shop Scheduling Problem with Travel Time

This article examined the flow shop scheduling problem by considering the travel time between machines. The objective function of this problem was to provide a makespan. The Moth Flame Optimization (MFO) algorithm was proposed to solve the flow shop problem. The MFO experiment was carried out with a combination of iteration parameters and the population of the MFO algorithm to solve the flow shop scheduling problem. The computational results showed that MFO could produce a better solution than the actual scheduling method. Furthermore, the MFO Proposal Algorithm was able to reduce the makespan by up to 3%.

Sustainable EOQ Model with Multi Container Transportation Problems

Industrial developments and environmental problems encourage decision-makers to determine optimal decisions. In addition, transportation is an aspect that has a significant contribution to environmental damage. Therefore, inventory and transportation decisions need to be integrated to minimize environmental problems. This study made an effort to develop a model of Sustainable EOQ with Multi Container Transportation Problems. The optimal procedure was proposed to determine the optimal number of containers in one vehicle. The results suggested that the proposed procedure could minimize the total annual inventory cost compared to the company's current solution.

Perception and Consumer Behavior of Halal Product Toward Purchase Decision in Indonesia

Indonesia is a country with a majority Muslim population. Therefore, Indonesian consumers have to be more thorough in assuring halal guarantees. One of some identities as a Muslim is consuming halal products. Various factors can affect consumers in purchasing halal products. However, the consumption of halal-certified products is still relatively low. This study was intended to analyze the factors that influenced consumer perceptions in purchasing halal products. A case study was carried out on the coffee product, one of Indonesia's most popular culinary products. The data were collected based on a survey of 170 respondents who live in Surakarta, Central Java Province, and are Muslim. This study suggested that the factors that significantly influenced the purchase were the variables of religiosity, halal label certification, and product prices. In contrast, the variables of halal awareness and brand image had no significant effect. Thus, the five variables simultaneously had a significant positive effect on purchasing decisions for halal products.

Risk Mitigation Via Integrating House of Risk and Probability Impact Matrix in Halal Food Supply Chain

One of the food industry challenges is how to identify sources of risk by considering the halal concept. This study aimed to identify risks and determine risk handling priorities in the supply chain strategy of halal food. This research offered integration of the house of risk and the probability impact matrix to manage risk mitigation in the halal food industry. A case study in the halal food industry was applied in Indonesia based on Supply Chain Operations Reference (SCOR). This study identified 27 risk events and 31 risk agents through 2 phases. Result research showed that employees who did not have special skills (A20) had the highest risk. Moreover, reward and punishment to employees (PA16) was the best proactive action for making effective improvements. The implication of this research is to provide recommendations to management in mitigating risks in the halal food industry.

A Three-Echelon Dual-Channel Supply Chain Model with Learning Effect Under the Return Policy

In today's competitive and technologically developed era, many retailers have adopted an e-channel to increase sales, in addition to the existing traditional retail channel. Although many researchers studied this issue, there is hardly any research that comprehensively considers the learning-effect and return-policy. Therefore, this research aimed to develop an imperfect production dual-channel supply chain model consisting of a supplier, a manufacturer, and a retailer. The manufacturer also has a refurbishment unit adjacent to its production hub, where it reworks all the defectives. The main objective is to maximize the supply chain profit by considering factors, such as inspection error, return policy, and learning-effect of the employees. Finally, this model is analyzed with the Leader-follower relationship strategy and an integrated approach. The research found that the integrated approach is profitable for the entire supply chain, while commodity prices can be minimized. Sensitivity analysis is also presented in this study.

Integration of Rough SWARA and COPRAS in the Performance Evaluation of Third-Party Logistics Providers

Currently, the use of logistics service providers in companies has become a decision chosen by several companies. Companies use Third Party Logistics (3PL) to focus more on other essential activities in the company. Evaluating the performance of a 3PL provider is an essential process in determining performance of a 3PL provider. A wrong evaluation process could lead to company’s loss. The main objective of this study was to propose a 3PL performance appraisal procedure. This study integrated the Rough method Step-wise Weight Assessment Ratio Analysis (SWARA) and the Complex Proportional Assessment Method (COPRAS) to assess the performance of 3PL providers. The SWARA Rough method was used to assess the ranking of the criteria. The results of the Rough SWARA ranking were utilized by the COPRAS method to assess supplier performance. A case study was conducted in an animal feed production company in Indonesia. The results showed that there were criteria for product safety; on-time delivery, responsiveness, and flexibility with the greatest weight among the 16 criteria used.