The objective of this study is to determine the most advantageous stock investment choices for a company by employing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodology. The study centres on the Indonesian stock market, specifically examining the top 10 businesses that have had the highest performance on the LQ45 index. The TOPSIS approach is employed to assess the appropriateness of individual companies by considering many parameters, including as market capitalization, current ratio, earnings stability, dividend history, growth rate, price-to-earnings ratio, and price-to-book value. According to the TOPSIS research, the study has identified PT Waskita Karya (Persero) Tbk (WSKT) and PT Waskita Beton Precast Tbk (WSBP) as the two most favourable investment options. Investors can utilise the findings of this study to create well-informed assumptions regarding their stock investments in the Indonesian market.

This study focuses on optimizing feature extraction methods to enhance satellite image analysis, a critical task in various fields such as remote sensing, environmental monitoring, and urban planning. The primary objective is to improve the accuracy and efficiency of feature extraction techniques tailored for satellite imagery. Through a comprehensive literature review and experimentation, this research evaluates existing methods and proposes enhancements to address their limitations. The study employs a diverse dataset representative of real-world satellite imagery scenarios and evaluates the performance of the optimized feature extraction methods using established metrics. Key findings include significant improvements in feature extraction accuracy and computational efficiency, demonstrating the efficacy of the proposed approach. This research contributes to advancing the state-of-the-art in satellite image analysis and provides valuable insights for researchers and practitioners in related domains.

The rapid expansion of mobile data usage in developing countries necessitates the evaluation of data network performance to enhance service delivery and customer satisfaction. This study evaluates the performance of the GLO 3G data network in Bali Metropolis, Taraba State, Nigeria. The research assesses the network's quality, speed, and reliability, considering their impact on the overall user experience. The study employs a mixed-methods approach, combining quantitative data from network performance measurements and user surveys to gather comprehensive insights. For the quantitative aspect, network performance metrics, such as throughput, latency, and signal strength, are collected using specialized software installed on smartphones distributed across the study area. On the other hand, the qualitative aspect involves conducting surveys to understand users' perceptions, satisfaction levels, and usage patterns related to the GLO 3G data network. The findings of this study will shed light on the strengths and weaknesses of the GLO 3G data network in the Bali Metropolis. The evaluation will identify potential areas for improvement, enabling service providers to optimise their network infrastructure and address customer concerns effectively. Moreover, the research will contribute to the existing knowledge on telecommunications in developing regions, providing valuable insights for policymakers and stakeholders seeking to enhance digital connectivity and bridge the digital divide in Nigeria.