Publication Search

In late August 2025, Indonesia was rocked by nationwide political demonstrations, triggered by the death of a delivery driver at the hands of police. These protests turned violent, leading to multiple casualties, injuries, and arson attacks on government and commercial buildings. This unrest has raised international concerns regarding the country’s safety image. This paper uses a qualitative descriptive approach to analyze secondary sources, such as news media, government releases, and academic literature, to explore how hosting the 2025 MotoGP at the Mandalika Circuit could be used as a nation-branding strategy to counter negative perceptions. The study draws on nation branding theory, destination image concepts, event leveraging, and Situational Crisis Communication Theory (SCCT). Findings suggest that Indonesian authorities are actively promoting MotoGP Mandalika 2025 as an opportunity to demonstrate the country’s resilience and safety standards. We analyze two scenarios: one in which the event is canceled and one where it is successfully executed. The paper argues that canceling the event, unless due to a legitimate health crisis, would signal weakness and harm the country's image, while proceeding with it would reflect confidence and effective crisis management. As a "brand shield," the MotoGP event is being leveraged to reinforce the narrative of Indonesia as a stable and safe international sports host, demonstrating the country's ability to manage crises while showcasing its commitment to safety and resilience.

This research discusses the economic policies implemented during the leadership of the Khulafaur Rashidin and their impact on the welfare and stability of the Muslim community. Through a descriptive qualitative method with a literature study approach, this research analyzes key policies such as the establishment of Baitul Mal, zakat and tax management, infrastructure development, as well as administrative reforms and wealth distribution by the caliphs. The results show that these policies played an important role in creating a fair distribution of wealth, improving people's welfare, and maintaining economic and social stability. The Islamic economic principles applied, such as social justice, transparency, prohibition of usury, and market supervision, have proven to be relevant and can be an inspiration in facing modern economic challenges.

MotoGP is a world-class motorcycle racing event involving participation from various countries around the world. In its implementation, it is necessary to import spare parts, vehicles, team equipment, and other technical equipment to circuits around the world, including Mandalika, Indonesia. This temporary import status makes MotoGP logistics require important documents, such as ATA Carnet and Customs Notification of Special Economic Zones (PPKEK) so that the goods can enter the Customs Area without being subject to customs and excise. This research method uses a qualitative method with a descriptive approach because it aims to understand in depth the process of handling MotoGP import cargo, especially related to the use of ATA Carnet documents and Customs Notification of Special Economic Zones (PPKEK) in the Mandalika Special Economic Zone. The results of this study indicate that the use of customs documents, such as ATA Carnet and Special Economic Zone Customs Notification (PPKEK) is used depending on the needs of each user who wants the entry of MotoGP logistics into Indonesia to be exempted from customs and excise so that these two documents become important instruments in implementing the temporary import status scheme for MotoGP logistics so that it can facilitate the handling process at Zainuddin Abdul Madjid International Airport to distribution to the Mandalika Special Economic Zone (KEK). The conclusion of this study is that with the existence of two customs mechanisms, namely ATA Carnet and Special Economic Zone Customs Notification (PPKEK), as well as the role of PT. Angkasa Pura Logistik in handling the flow of goods at the airport, the smoothness of MotoGP logistics is more guaranteed.

The rapid development of Lombok tourism and the MotoGP event will be held in September 2024, driving the need for transportation, especially air transportation, Zainuddin Abdul Madjid  Lombok International Airport has several units that play a role in optimizing the airport, one of which is the Apron Movement Control (AMC) unit, this unit has a very important role in supervising all traffic movements on the air side which includes aircraft parking stands, traffic of people, vehicles, and Ground Handling arrangements, flight data administration and licensing of vehicles operating on the apron, this study aims to determine the differences in the implementation of the AMC unit's duties before and during the Mandalika MotoGP event, and to determine the obstacles faced when carrying out tasks during the event. This study uses a qualitative method, the data used are primary and secondary data, primary data is obtained from observation and interviews, while secondary data from SOP, documentation in the form of photos and regulations related to the problem being studied, data analysis techniques use data reduction, data presentation and drawing conclusions, testing the validity of data using triangulation techniques. This study shows that AMC officers successfully carried out their duties in accordance with SOP, including the process of plotting aircraft parking, operating Aviobridge, supervising Ground Support Equipment and supervising Marshaller Service, the responsibility of officers in providing services to airport users, especially in the Airside area, was carried out well, the obstacles faced including FOD, lack of facilities and personnel available, use of Driving Licenses and the suitability of vehicles/equipment and lack of communication between units can be handled and provide evaluation so that all movements in the Airside area run smoothly.

News is a text that has an important role in disseminating information. News text is so useful that it has become a literacy material for students due to the development of advanced technology. Although it has become one of the sources of student literacy, online news texts are still classified as having syntactic errors such as a lack of understanding of the language used in compiling a sentence in the news. The purpose of this study is to describe sentence errors in the news contained in the old CNN Indonesia news, such as "December Sky Phenomena: Geminid Meteor Shower to Solstice", "Mandalika Circuit's Important Role in Bringing Indonesian Drivers to Success in Asia", "Solar Storms Raining on Earth, RI Safe?", "The First Candidate Debate will be Held at the KPU Office on December 12", and "When HIV Tests Become a Scary Scourge Because of People's Scorn". This research uses a descriptive method with a qualitative approach. The results of this study found several findings such as effective sentences, ineffective sentences, spelling errors according to EYD, errors in the use of diction, and sentences that are not clear to the reader. The most common error found in the five news articles is ineffective sentences. The benefit of this research is to provide knowledge insights in the form of understanding sentence writing systematically, which will be useful in improving understanding of authorship in news texts and preventing errors from occurring again in the same news so that it is worthy of being a literacy material for 12th grade high school students.

The MotoGP One race in West Nusa Tenggara Lombok, Mandalika which was held on March 18 2022, received many responses or reactions from the public on social media, especially Twitter. There are those who agree and disagree about the holding of MotoGP in Mandalika, to find out the responses of the people who agree or disagree is needed that can process tweets data using the sentiment analysis method. The use of BERT (Bidirectional Encoder Representations from Transformers) for sentiment analysis produces a bidirectional language model that can understand the context of all words from a sentence. The dataset used goes through preprocessing stages such as case folding, data cleaning, tokenization, normalization, and removal of stopwords before sentiment analysis is carried out. This study uses several hyperparameters, namely a batch size of 32, the optimizer uses Adam with a learning rate of 3e-6 or 0.000003, and an epoch of 25. The evaluation results of the model obtain an accuracy of 55%. Precision for positive by 56%, neutral by 59%, and negative by 44%. Recall for positive is 74%, neutral is 29%, and negative is 54%. F1-score for positive is 64%, neutral is 38%, and negative is 48%.