Suchergebnisse

Petroleum exploration decision remains a subject of petroleum and economic studies for decades. Most of the studies discuss the investment decision by focusing on either a technical or economic perspective. In reality, economic, geological, and environmental factors are expected to determine the way investors make a decision. This study aims to increase the understanding of best practices in decision-making by scrutinizing integrative perspectives applying panel data of 32 basins in Indonesia in 2004–2015. This study provides several contributions to optimize decisions on wells drilled. First, this study derives an empirical model examining several plausible factors of economy, geology, and environment. Second, the findings demonstrate how to empirically examine which factors significantly determine wells drilled by companies. The last contribution is to empirically support a technical transformation from Western to Eastern exploration due to the natural depletion of oil fields.

Oil exploration has been subject to economic research for decades. Earlier studies of exploration models are mostly discussed the behavior of exploration at the macro-level analysis such as field, firm, region, and continental. This paper then focuses on the geological and economic factors that determine the well-drilling decision at the micro-level using disaggregated panel data of 32 geological basins in Indonesia over the period of 2004–2013. This study shows that the number of drilled wells is determined significantly by the lag of success rate, lag of discovery size, lag of global oil price, and regional location of geological basin. AbstrakEksplorasi migas telah menjadi subyek ekonomi dalam beberapa dekade. Studi-studi sebelumnya dengan model eksplorasi, kebanyakan mengembangkan model Fisher (1964), secara umum dikelompokkan oleh persamaan yang menjelaskan respons eksplorasi pada tingkat makro menggunakan lapangan, perusahaan, wilayah, dan kontinental. Paper ini fokus pada analisis faktor-faktor geologi dan ekonomi yang menentukan tingkat sumur pemboran pada tingkat mikro menggunakan data panel dari 32 basin di Indonesia dalam periode 2004–2013. Hasil empiris menunjukkan bahwa tingkat sumur pemboran ditentukan secara signifikan berdasarkan tingkat keberhasilan pemboran, ukuran temuan dan harga minyak pada tahun sebelumnya serta lokasi basin geologis.Kata kunci: Pengeboran; Variabel Geologi; Variabel Ekonomi; EksplorasiJEL classifications: L71; Q35

Currently, climate change due to global warming is a concern for many parties. The greenhouse gas emissions level is increasing day by day. The major contributors to Air pollution are the greenhouse effect. Transportation accounts for about 27% of air pollution, and governments in various countries use electric vehicles to reduce air pollution. However, the success of using electric vehicles is depending on perception, people's sentiment, and understanding. The main purpose of this research is to find out how public sentiment towards electric vehicles is through tweets and comments on the Twitter social media platform using sentiment analysis. The data obtained are 1084 tweets and comments. The data were classified using the Naïve Bayes method, K-Nearest Neighbor, and Decision Tree. The results showed that the Naïve Bayes Classification Method gave better results than K-Nearest Neighbor, and Decision Tree with an accuracy rate of 94% positive sentiment by 53%, negative sentiment by 38%, and neutral sentiment by 9%. So, it can be concluded that public sentiment towards electric vehicles is quite good based on conversations on the Twitter social media platform. In addition, the author also visualizes the results of the analysis in the form of graphs and word clouds so that they can help the electric vehicle industry players to understand public sentiment better and more accurately.