Kampar Regency, as the largest pineapple producer in Riau Province, has yet to provide significant added value for the surrounding SMEs. The limitations in technology and innovation, infrastructure support, and market access have prevented this potential from being optimally utilized. A Technopark can provide the necessary facilities and infrastructure to enhance production efficiency, innovation, and product quality, thus driving local economic growth. The objective of this study is to identify and determine potential locations for the development of a pineapple-based Technopark in Kampar Regency. This study is crucial as a fundamental consideration in selecting the technopark location and assessing the effectiveness and success of the technopark area. The method used in this study is AHP-GIS to analyze relevant parameters in the site selection process for the technopark area. Parameters considered in this study include slope, land use, availability of raw materials, accessibility of roads, access to water resources, proximity to universities, market access, population density, and landfill. The analysis results indicate that the percentage of land highly suitable for the technopark location is 0.78%, covering an area of 8943 hectares. Based on the analysis, it is recommended that potential locations for the development of a pineapple SMEs-based technopark in Kampar Regency are dispersed in Tambang District, encompassing three villages: Rimbo Panjang, Kualu Nenas and Tarai Bangun. The findings of this study align with the spatial planning of Kampar Regency.

Realistic project scheduling and control are critical for running a profitable enterprise in the construction industry. Finance-based scheduling aims to produce more realistic schedules by considering both resource and cash constraints. Since the introduction of finance-based scheduling, its literature has evolved from a single-objective model to a multi-objective model and also from a single-project problem to a multi-project problem for a contractor. This study investigates the possibility of cooperation among contractors with concurrent projects to minimize financial costs. Contractors often do not use their entire credit and may be required to pay a penalty for the unused portions. Therefore, contractors are willing to share these unused portions to decrease their financing costs and consequently improve their overall profits. This study focuses on the partnering of two contractors in a joint finance-based scheduling where contractors are allowed to lend credit to or borrow credit from each other at an internal interest rate. We apply this approach to an illustrative example in which two concurrent projects have the potential for partnering. Results show that joint finance-based scheduling reduces the financing cost for both contractors and leads to additional overall profits. Our further analyses highlight the intricate dynamics impacting additional net profit, revealing optimal scenarios for cooperation in complex project networks.

Accurate prediction of US Treasury bond yields is crucial for investment strategies and economic policymaking. This paper explores the application of advanced machine learning techniques, specifically Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) models, in forecasting these yields. By integrating key economic indicators and policy changes, our approach seeks to enhance the precision of yield predictions. Our study demonstrates the superiority of LSTM models over traditional RNNs in capturing the temporal dependencies and complexities inherent in financial data. The inclusion of macroeconomic and policy variables significantly improves the models’ predictive accuracy. This research underscores a pioneering movement for the legacy banking industry to adopt artificial intelligence (AI) in financial market prediction. In addition to considering the conventional economic indicator that drives the fluctuation of the bond market, this paper also optimizes the LSTM to handle situations when rate hike expectations have already been priced-in by market sentiment.

The urgency of implementing sharia economics and a green economy is in the same spirit as the efforts made by the international community to promote sustainable development. The purpose of this study is to describe the role of Islamic economics in realizing sustainable, green economic development. The approach used in this research is a qualitative approach through literature study and content analysis methods. The results of this study state that the concept of sharia economics, when implemented wisely by human resources as khalifah on earth based on the Qur’an and Hadith and following Islamic law, including hifdzhu al-din, hifzhu al-nafs, hifzhu al-aql, hifzhu al-nasl, and hifzhu al-maal, will realize the goal of sustainable green economic ideas. Maqashid sharia-based views have a complex mindset, considering not only environmental aspects but also moral, financial, and hereditary aspects.

This paper explores the influence of the concept of "moral education" on physical education, and focuses on the application of Teaching Personal and Social Responsibility (TPSR) responsibility teaching model in physical education. Physical education teaching is not only the teaching of skills, but also the indoctrination of values. Through the thought of "cultivating people by virtue", we can make physical education based on moral education and return to the essence of education. The TPSR model makes this idea concrete, emphasizes the personal process and social responsibility, and includes the cultivation of students' sense of responsibility, team spirit and self-management ability in physical education teaching. Through theoretical discussion and empirical analysis, this study revealed the practical application and effect of TPSR model in physical education teaching, proved the importance of this teaching model, and put forward the construction idea of TPSR physical education teaching model. Future research can expand more application scenarios of the TPSR model to achieve better quality and more comprehensive physical education.

This quasi-experimental study examined the effect of a mechanics course delivered through a Learning Management System (LMS) on the creativity of prospective physics teachers at a teacher training college in Mataram, Indonesia. The study was conducted in the post-pandemic era. Using a pretest-posttest one-group design, the researchers evaluated changes in creativity across three domains: figural, numeric, and verbal. The results showed significant improvements in overall creativity, with the most critical gains observed in the figural domain. Further analysis revealed that fluency was the creative indicator with the most enhancement. In contrast, other indicators displayed varying degrees of improvement. These findings highlight the potential of LMS-based instruction in fostering creativity among future physics educators, particularly in the figural, numeric, and verbal domains. This study adds to the growing body of evidence supporting technology integration into teacher education, especially during times of crisis. Future research should explore more targeted instructional strategies within LMS environments and utilize comprehensive creativity assessment methods further to enhance creative learning experiences for prospective physics teachers.