This study explores the factors affecting dentists’ willingness to use social media in their practices, examining how consumer behavior influences their adoption decisions. Despite the growing use of social media across industries, its adoption in dentistry remains relatively underexplored. As investments in digital technologies increase, understanding dentists’ intentions to integrate social media becomes crucial, especially considering the evolving consumer behavior patterns in healthcare. Using the Technology Acceptance Model (TAM) and factoring in patient pressures, this study analyzes data from 209 respondents through SPSS and Smart PLS 4.0. The results offer valuable insights for dentists, highlighting the benefits of social media integration, and justifying investments in these platforms to align with changing consumer expectations. The study also discusses its limitations and suggests future research directions to further explore social media adoption in dentistry and its potential to drive economic growth within the sector.

Freshwater problems in coastal areas include the process of salt intrusion which occurs due to decreasing groundwater levels below sea level which can cause an increase in salt levels in groundwater so that the water cannot be used for water purposes, human consumption and agricultural needs. The main objective of this research is to implementation of RWH to fulfill clean water needs in tropical coastal area in Tanah Merah Village, Indragiri Hilir Regency, with the aim of providing clean water to coastal communities. The approach method used based on fuzzy logic (FL). The model input data includes the effective area of the house’s roof, annual rainfall, roof runoff coefficient, and water consumption based on the number of families. The BWS III Sumatera provided the rainfall data for this research, which was collected from the Keritang rainfall monitoring station during 2015 and 2021. The research findings show that FL based on household scale RWH technology is used to supply clean water in tropical coastal areas that the largest rainwater contribution for the 144 m² house type for the number of residents in a house of four people with a tank capacity of 29 m² is 99.45%.

Finding the right technique to optimize a complex problem is not an easy task. There are hundreds of methods, especially in the field of metaheuristics suitable for solving NP-hard problems. Most metaheuristic research is characterized by developing a new algorithm for a task, modifying or improving an existing technique. The overall rate of reuse of metaheuristics is small. Many problems in the field of logistics are complex and NP-hard, so metaheuristics can adequately solve them. The purpose of this paper is to promote more frequent reuse of algorithms in the field of logistics. For this, a framework is presented, where tasks are analyzed and categorized in a new way in terms of variables or based on the type of task. A lot of emphasis is placed on whether the nature of a task is discrete or continuous. Metaheuristics are also analyzed from a new approach: the focus of the study is that, based on literature, an algorithm has already effectively solved mostly discrete or continuous problems. An algorithm is not modified and adapted to a problem, but methods that provide a possible good solution for a task type are collected. A kind of reverse optimization is presented, which can help the reuse and industrial application of metaheuristics. The paper also contributes to providing proof of the difficulties in the applicability of metaheuristics. The revealed research difficulties can help improve the quality of the field and, by initiating many additional research questions, it can improve the real application of metaheuristic algorithms to specific problems. The paper helps with decision support in logistics in the selection of applied optimization methods. We tested the effectiveness of the selection method on a specific task, and it was proven that the functional structure can help the decision when choosing the appropriate algorithm.

Plastic products, including plastic packaging, were products whose increasing demand continued because the community still needed plastic as packaging. On the other hand, plastic waste, which was increasingly high and difficult to decompose, was a problem that needed to be solved together. This study aims to understand how plastic company packaging implements TQM, its environmental impact, and how plastic packaging companies are taking steps towards green manufacturing. This research used a qualitative phenomenological method to understand the problem based on the actor’s perspective. The data collection method was in-depth interviews with informants from 3 plastic companies in East Java, Indonesia, followed by observation and FGD. We carried out Triangulation, member checking, and professional involvement to determine the data’s validity, reliability, and trustworthiness. The results of this study indicated a management system that promotes quality as a business strategy and is oriented towards customer satisfaction by involving all members of the organization. TQM emphasized continuous improvement, customer satisfaction, and employee involvement. By implementing aspects of TQM, plastic packaging companies could improve their production processes and reduce waste, increasing efficiency and profitability. In addition, TQM could also contribute to the company’s green performance by promoting environmentally friendly practices, including using electric machines to replace hydraulic machines, thereby reducing the use of electrical energy and CO₂ emissions. The use of solar panels was a step towards green manufacturing. Companies that adopt TQM principles are more likely to implement environmentally friendly initiatives such as reducing energy consumption and using recyclable materials and can demonstrate a commitment to corporate social responsibility. The company’s membership in EcoVadis and SMETA further strengthens the company’s direction towards Green Manufacturing and competitive advantage.