This bibliometric review evaluates the research progress and knowledge structure regarding the impact of supporting facilities on halal tourism development. Using the Scopus database and bibliometric analysis with the “bibliometrix” package in R, the study covers the period from 2016 to 2023. The search, employing keywords like “halal tourism,” “facilities,” “infrastructure,” and “local support,” identified 26 relevant publications. The findings highlight a limited body of research, with the Journal of Islamic Marketing being the most active publisher in this area, contributing six articles. Indonesia emerges as a leading contributor to halal tourism research, driven by its significant Muslim population and the economic potential of this niche market. Key facilities, such as mosques, musholla, and high-quality halal food options, are identified as crucial factors influencing Muslim travelers’ destination choices. This review provides a comprehensive overview of the current research landscape on supporting facilities in halal tourism and highlights opportunities for future investigation to further enrich the field.
Islamic based low-cost private school facing a suffer from a lack of new students due to the incapability to adapt to current condition. They are already “lost in the competition” with other school. This quality also includes the inability of the low-cost private schools to adapt with technology and change. Another finding is that low-cost private schools struggling in managing the funding and management. Low-cost private high school has become a key support in ensuring the fulfilment 12-year compulsory education stated by Indonesian Education Law. With only 40 percent of the total population able to attend public schools, the government as well as the private sector needs to accommodate affordable private schools to meet the need of high schools in Jakarta. Low-cost private schools become essential in providing the gap between the need of schools from the total population of students and the availability of the public school. The previous study highlighted organizational agility with the mediation of Islamic Work Ethic can be achieved through leadership capability and organizational culture, whilst several studies also suggest that Islamic Work Ethics or Istiqamah have no impact in promoting organizational agility. This research conducted in 2022–2023 encompassed 133 low-cost private high school in Jakarta in which all of them are Islamic low-cost private high school. The finding of this study is that school principal leadership capabilities and school culture are positively affect school agility with Istiqamah as mediated variable.
Among contemporary computational techniques, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are favoured because of their capacity to tackle non-linear modelling and complex stochastic datasets. Nondeterministic models involve some computational intricacies when deciphering real-life problems but always yield better outcomes. For the first time, this study utilized the ANN and ANFIS models for modelling power generation/electric power output (EPO) from databases generated in a combined cycle power plant (CCPP). The study presents a comparative study between ANNs and ANFIS to estimate the power output generation of a combined cycle power plant in Turkey. The inputs of the ANN and ANFIS models are ambient temperature (AT), ambient pressure (AP), relative humidity (RH), and exhaust vacuum (V), correlated with electric power output. Several models were developed to achieve the best architecture as the number of hidden neurons varied for the ANNs, while the training process was conducted for the ANFIS model. A comparison of the developed hybrid models was completed using statistical criteria such as the coefficient of determination (R2), mean average error (MAE), and average absolute deviation (AAD). The R2 of 0.945, MAE of 3.001%, and AAD of 3.722% for the ANN model were compared to those of R2 of 0.9499, MAE of 2.843% and AAD of 2.842% for the ANFIS model. Even though both ANN and ANFIS are relevant in estimating and predicting power production, the ANFIS model exhibits higher superiority compared to the ANN model in accurately estimating the EPO of the CCPP located in Turkey and its environment.
Using generative artificial intelligence systems in the classroom for law case analysis teaching can enhance the efficiency and accuracy of knowledge delivery. They can create interactive learning environments that are appropriate, immersive, integrated, and evocative, guiding students to conduct case analysis from interdisciplinary and cross-cultural perspectives. This teaching method not only increases students’ interest and participation in learning but also helps cultivate their interdisciplinary thinking and global vision. However, the application of generative artificial intelligence systems in legal education also faces some challenges and issues. If students excessively rely on these systems, their ability to think independently, make judgments, and innovate may be weakened, leading to over-trust in machines and reinforcement of value biases. To address these challenges and issues, legal education should focus more on cultivating students’ questioning skills, self-analysis abilities, critical thinking, basic legal literacy, digital skills, and humanistic spirit. This will enable students to respond to the challenges brought by generative artificial intelligence and ensure their comprehensive development in the new era.
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