Publication Search

Somongari Tourism Village in Indonesia's Purworejo Regency is the site of this research on the ways in which community-based creative economy development could promote ecotourism. As a destination rich in natural, cultural, and historical assets, Somongari demonstrates significant potential to integrate creative industries into tourism practices. Examining community involvement, entrepreneurship, and government, this study used a qualitative descriptive technique to gather data via observation, recording, and interviews.Findings reveal that creative economy initiatives—such as culinary innovation, agro-tourism, cultural storytelling, and digital promotion—strengthen destination attractiveness while generating income for residents. Innovation, inclusion, and intergenerational colaboration are greatly enhanced when women and youths are involved. Community ownership and fair distribution of benefits are reinforced via participatory governance and collective management. Limited product diversi-fication, reliance on seasonal tourism, and limitations in management competence are some of the difficulties that continue to exist. The study concludes that community-based creative economy development provides a strategic pathway for sustainable tourism by integrating economic empowerment, cultural preservation, and social participation. Strengthening entrepreneurship, enhancing digital marketing, diversifying tourism products, and fostering stakeholder collaboration are essential to improving competitiveness and resilience. This study contribute to the discourse on sustainable rural tourism by demonstrating how creative economy initiatives can serve as instruments of empowerment and sustainable destination development.

This study discusses the leadership values reflected in the folklore of Panglima Wangkang in Marabahan as a representation of the local wisdom of the Banjar-Bakumpai community. Panglima Wangkang is recognized as a prominent figure who played a significant role in resisting Dutch colonialism in the Barito region. This research aims to examine Panglima Wangkang not only as a war hero but also as a symbol of cultural unity, religious values, and traditional leadership that still lives in the collective memory of society today. The study employs a qualitative historical method with a postcolonial approach. The data were collected through library research involving historical archives, scientific journals, books, and documented folklore. The research stages included heuristics, source criticism, interpretation, and historiography. The findings reveal that Panglima Wangkang’s leadership reflects the values of courage, strategic intelligence, loyalty, religiosity, and social concern. His well-known military strategy, referred to as the “Trojan Horse” technique, demonstrates his tactical ability in confronting colonial forces. In addition, religious values are reflected in his message to always maintain ablution and in the belief regarding martyrdom. The story of the golden bullet also symbolizes the community’s respect for the struggle and honor of local heroes. Panglima Wangkang’s cross-ethnic identity as both Banjar and Bakumpai further strengthened community unity in facing colonialism. This study shows that folklore functions not only as a cultural heritage but also as a medium for transmitting leadership values and local identity that remain relevant in the social life of the Marabahan community today.

This study aims to analyze the application of standard costing and variance analysis in identifying production cost inefficiencies at UMKM Sari Kedelai Bu Ade, a soybean milk manufacturing business in Yogyakarta. The research used a descriptive quantitative approach with a case study method based on the company’s operational data. Standard costs were prepared using historical production data from the second semester of 2024, while actual production costs were calculated using operational realization data from the first semester of 2025. The analysis focused on direct material variance, direct labor variance, and factory overhead variance to identify the dominant sources of production cost inefficiency. The results show that direct labor variance became the largest unfavorable variance due to the use of actual working hours exceeding the established standards. Fixed overhead variance also indicated the existence of idle capacity because actual production had not reached the company’s normal production capacity. On the other hand, direct material variance and variable overhead variance still showed favorable conditions, indicating that the company was still capable of controlling material usage and several operational costs. This study concludes that the implementation of standard costing and variance analysis can help MSMEs identify production cost inefficiencies that were previously undetected through simple bookkeeping practices.

The rapid development of digital technology has transformed the tourism industry through the implementation of Augmented Reality (AR), which provides more interactive, educational, and immersive tourism experiences. In Indonesia, the adoption of AR has become increasingly important to address the unequal distribution of tourist visits, which remain heavily concentrated in a few destinations, particularly Bali. This study aims to identify the clusters of AR utilization in Indonesian tourism development and analyze their potential contributions to destination promotion, cultural heritage preservation, and tourism competitiveness. The study employed a Systematic Literature Review (SLR) approach based on the PRISMA guidelines. Data were collected from reputable national and international scientific publications discussing AR implementation in tourism, cultural heritage, and travel industries between 2014 and 2025. The findings reveal that AR utilization in Indonesia can be categorized into five major clusters: the Bali Tourism Corridor Cluster, the Jakarta Metropolitan Cluster, the West Java Cluster, the East Java Cluster, and the Eastern Indonesia Cluster. Various AR implementations in destinations such as the Bongal Historical Site, Tana Toraja, Langsa City, and Lawang Sewu demonstrate the technology’s ability to enhance visitor experiences, strengthen historical and cultural education, and support destination marketing strategies. Furthermore, technology readiness and human resource competence were identified as the most influential factors affecting successful AR adoption. The findings suggest that AR has significant strategic potential to expand destination exposure, reduce disparities in tourist distribution across regions, and support the sustainable digital transformation of Indonesia’s tourism sector.

The high volatility of cryptocurrency assets, particularly Ethereum, poses a significant challenge for investors during market downturns. Traditional passive strategies often lead to substantial capital erosion in bearish conditions. This study explores the application of Deep Reinforcement Learning (DRL) through the Deep Q-Network (DQN) algorithm to develop an adaptive trading agent. By integrating technical indicators—Relative Strength Index (RSI), Simple Moving Average (SMA), and Moving Average Convergence Divergence (MACD)—the proposed model aims to optimize decision-making processes. Experimental results using historical data from 2020 to 2026 demonstrate that while the market experienced a significant decline of 19.55%, the DQN agent successfully maintained capital stability with a marginal deviation of only -0.54%. This finding suggests that the DQN-based approach offers superior risk mitigation and capital preservation capabilities compared to conventional buy-and-hold strategies in volatile financial environments.

Bank stock price prediction is an important topic in the application of information technology because stock price movements are dynamic, sequential, and influenced by historical market patterns. This study aims to predict Indonesian banking stock prices using the Long Short-Term Memory method and evaluate the effect of Bayesian Optimization on model performance. The data used in this study consists of daily historical stock data of BBCA, BBNI, BBRI, BBTN, and BMRI from May 4, 2020, to May 4, 2026, obtained from Yahoo Finance. The input features include opening price, highest price, lowest price, closing price, and trading volume, while the prediction target is the stock closing price. The results show that the baseline model produced MAPE values ranging from 1.892% to 3.147%. The best baseline performance was obtained on BBCA with an R² value of 0.933, followed by BBTN with an R² value of 0.902. After optimization, performance improvement occurred on BBTN, with MAPE decreasing from 3.147% to 2.482% and R² increasing from 0.902 to 0.935. For BMRI, MAPE decreased from 2.385% to 2.206%, and R² increased from 0.687 to 0.743. This study concludes that Long Short-Term Memory can be used to predict Indonesian banking stock prices, while Bayesian Optimization can selectively improve model performance depending on the characteristics of each stock dataset.

Motor Vehicle Tax (PKB) is a key pillar of Regional Original Revenue (PAD) that supports development funding. However, seasonal fluctuations in payment realization create uncertainties in local budget planning. This study aims to address the limitations of the standard Random Forestalgorithm, which suffers from extreme prediction failures on time-series data due to its inability to capture temporal transitions between months. The proposed solution implements feature engineering using a Cyclical Encoding approach (Sine and Cosine transformations) and Lagged Variables. The dataset comprises historical records of motor vehicle tax potential and realization from January 2021 to November 2025. The baseline model evaluation without feature engineering yields highly inaccurate predictions with a Mean Absolute Percentage Error (MAPE) of 203.47% (accuracy of -103.47%). Conversely, after integrating Cyclical Encoding and Lagged Variables, the proposed model's performance improves drastically, achieving a MAPE of 14.40% (an accuracy rate of 85.60%), an MAE of 9,317 units, and an RMSE of 12,638 units. Feature Importance analysis confirms that the cyclically encoded month feature contributes the highest weight to the model's decisions with a score of 0.5031, followed by the potential feature at 0.1798. This study demonstrates that time-based feature engineering effectively optimizes Random Forestfor precise tax revenue forecasting.

This study aims to implement Business Intelligence using Microsoft Power BI to support network disturbance monitoring based on trend analysis. The main problem addressed in this research is that network disturbance data has only been used as documentation, resulting in suboptimal monitoring and data analysis processes. The data used in this study consists of historical network disturbance data, including information on disturbance location, type of disturbance, occurrence time, and resolution duration. The research methodology includes data collection, data preprocessing, implementation of a Business Intelligence dashboard, and trend analysis using interactive visualizations in Microsoft Power BI. The developed dashboard consists of Key Performance Indicators (KPI), interactive filters, line charts, pie charts, bar charts, and table visuals to support a more effective and structured network monitoring process. The results show that the implementation of the Business Intelligence dashboard is capable of supporting real-time, interactive, and user-friendly monitoring of network disturbances. The trend analysis results indicate that the number of network disturbances fluctuated each month, with the highest number occurring in August and the lowest in November. In addition, the dominant types of disturbances were identified as Supporting Facilities and Electrical Problems. Based on functional testing and user testing results, all dashboard features performed successfully and were considered effective in supporting monitoring activities and data-driven decision making.  

Technological developments and globalization have brought changes to the mindsets and behaviors of the younger generation, including a declining interest in history learning and low historical awareness. Islamic Cultural History (ISH) plays a crucial role in shaping historical awareness because it encompasses values ​​of faith, scholarship, tolerance, leadership, and morals relevant to modern life. This study aims to analyze the role of ISH learning in shaping the historical awareness of the younger generation, explain its importance in understanding Islamic historical values, and examine the effective implementation of ISH learning in the modern era. This study used a qualitative method with a library research approach. Data were obtained from books, scientific journals, articles, and various other sources relevant to the research theme. Data were analyzed descriptively and analytically through a process of collection, reduction, interpretation, and drawing conclusions. The results indicate that ISH learning plays a significant role in building the historical awareness of the younger generation by instilling Islamic character values ​​and identity. Historical awareness helps students understand the interconnectedness of the past, present, and future, enabling them to draw lessons from historical events. Implementation of Islamic Education (SKI) learning can be carried out through a contextual approach, active learning methods, the use of digital technology, role models, and experiential learning. Thus, SKI serves not only as a means of transferring knowledge but also as a medium for character and identity formation for the younger generation in the era of globalization.

Surau is the oldest traditional Islamic educational institution in Minangkabau and played an important role in the development of Islamic education in Indonesia before the twentieth century. This study is motivated by the modern shift in understanding the function of surau, which is often viewed merely as a place of worship, whereas historically it possessed broader educational, social, and cultural functions. The research aims to analyze the origins and transformation of surau, identify the roles of influential figures in its development, and examine its social functions within Minangkabau society. This study employs a qualitative approach using the historical research method through library research based on various primary and secondary sources. Data analysis was conducted through the stages of heuristics, source criticism, interpretation, and historiography to produce a systematic and factual historical account. The findings reveal that surau transformed from a Hindu-Buddhist ritual center into an Islamic educational institution that functioned as a center for religious instruction, character building, intellectual development, and social integration. Figures such as Syekh Burhanuddin Ulakan, Tuanku Nan Tuo, and Syekh Muhammad Djamil Djambek made significant contributions to the reform and development of the surau educational system. In addition, surau also served as a center for community deliberation, a residence for young men, and a space for moral and cultural development. The study implies that surau became an important foundation in shaping the Islamic educational system in the Nusantara by harmoniously integrating religious values, local culture, and social life.

The preservation of the nation's collective memory is a very important aspect in maintaining national identity, but its existence today is threatened by physical damage and limited access to information. This study aims to explain effective preservation methods to ensure the sustainability of the collective memory as a historical heritage. The methodology applied is qualitative descriptive by collecting data through literature review and document analysis from various literature sources and regulations related to archives. The results of this study show that the implementation of the current preservation strategy still faces major problems, especially the difference between the expected tennis standards and the reality of limited funds and the ability of human resources to carry out restoration. In addition, the digitalization process has not been fully linked to the planned long-term digital preservation management. The implications of this study show that strengthening the collaboration and technical capabilities of archivists is very important so that all historical artifacts of the nation are maintained in their authenticity, protected, and can be widely accessed by future generations.

 Cryptocurrency price prediction, particularly for highly volatile assets like Solana (SOL), is a crucial challenge in time series data analysis in digital finance. This study aims to compare the performance of the XGBoost machine learning algorithm with the Temporal Fusion Transformer (TFT) deep learning model in predicting Solana's daily closing price. The dataset used consists of historical Solana price data and network fundamentals data in the form of Total Value Locked (TVL). The research process includes data preprocessing, dividing training and test data, model training, and evaluation using the Root Mean Squared Error (RMSE) metric. The results show that using the same-day price feature has the potential to cause target leakage, resulting in invalid prediction accuracy. In testing using pure historical data without data leakage, the XGBoost model performed better than TFT with an RMSE of 4.27, while TFT produced an RMSE of 18.59. Furthermore, the integration of network fundamentals data in the form of TVL did not improve prediction accuracy and even caused a decrease in performance for the XGBoost model with an RMSE of 7.10. The results of this study show that the use of historical price action features is more effective than fundamental network indicators for short-term daily Solana price predictions.

This study analyzes the role of supporter fanaticism and loyalty in influencing the purchase decisions of official PSMS Medan merchandise. A qualitative descriptive method was employed through in-depth interviews, observation, and documentation, supported by secondary data from literature studies. The results show that fanaticism is reflected in emotional attachment, active involvement, long-term support, and social environmental influences. Supporter loyalty appears in consistent attendance at matches, following games, discussing the club, and repeated purchases of official merchandise. Purchase decisions are influenced by product type, design/form, and quantity, while also considering financial capability. Overall, fanaticism shapes emotional bonding, whereas loyalty drives repeated purchasing behavior; both contribute significantly to merchandise purchasing. These findings highlight the importance of design innovation, product quality improvement, and marketing strategies based on emotional and historical attachment to the club. Keywords: Consumer Behavior; Fanaticism; Merchandise; Purchase Decision; Supporter Loyalty.

The implementation of local democracy in Indonesia faces challenges when the electoral and procedural mechanisms regulated in modern village administration are not fully in line with the socio-cultural traditions of indigenous communities. Many villages still strongly uphold the values, norms, and authority of traditional institutions that have historically regulated communal life, including in terms of leadership legitimacy. Tension between formal democracy and customary values arises when the village political process is perceived as not reflecting the cultural identity of the community. This situation creates a need to understand how the integration of customary institutions can strengthen the legitimacy of village leaders in the local democratic system. This study uses a literature review method with a content analysis approach because the study focuses on the concept of the role of customary institutions in strengthening local democracy and the legitimacy of village leadership. This method allows researchers to explore theories and compare previous findings to form a systematic understanding. The research data comes from 19 secondary sources in the form of scientific books and journal articles published between 2016 and 2025 that are relevant to the themes of customs, village governance, community participation, and local leadership. The search was conducted using the Publish or Perish application with purposive sampling techniques to select sources directly related to the main research issue. This study concludes that the integration of traditional institutions into local democracy produces a model of village leadership that is legally strong and culturally rooted. This integration provides a basis for strengthening local democracy based on cultural wisdom, thereby supporting village development.

This study explores the themes of poverty and educational values in the novel Al-Bidayah wa al-Nihayah by Naguib Mahfouz using the sociology of literature approach developed by Alan Swingewood. The novel is selected because it portrays the social reality of Egyptian society in the 1940s, particularly the lower class facing economic hardship, social inequality, and limited social mobility. This research employs a qualitative descriptive method through reading, note-taking, and library research. The data are drawn from narratives, dialogues, and events in the novel that reflect both poverty and educational values. The analysis is conducted by relating the textual content to its social and historical context. The findings indicate that poverty is not merely an economic issue but also a structural condition affecting the psychological, moral, and social aspects of the characters. Furthermore, the novel conveys educational values, including religious, moral, social, and cultural dimensions, which are closely linked to the realities of pre-revolutionary Egyptian society. Overall, Swingewood’s approach highlights the novel as a form of social critique as well as a medium for fostering readers’ social awareness.

The expression “God regretted” in Genesis 6:7 is one of the most theologically problematic statements in the Old Testament, as it seems to contradict the classical doctrine of God’s immutability. This study aims to examine the meaning of this expression through an exegetical approach, emphasizing the analysis of the Hebrew text and the lexical use of the word nāḥam. The method employed is qualitative-descriptive with a historical-grammatical and biblical-theological approach. The primary data are derived from the Hebrew text in the Biblia Hebraica Stuttgartensia and supported by lexical sources. The results indicate that the word nāḥam in Genesis 6:7 does not imply regret in the sense of wrongdoing, but rather refers to divine sorrow over the moral corruption of humanity. The expression represents a form of anthropomorphism used to depict the relationship between God and humans in language comprehensible to human beings. From an Old Testament theological perspective, this text affirms that God is relational and active in history, without compromising the consistency of His character. Therefore, the “regret of God” does not contradict the doctrine of divine immutability, but rather enriches the understanding of His involvement in human life.

The discipline of Qur'anic Studies (‘Ulūm al-Qur’ān) has experienced a significant paradigm shift from the classical textual-normative approach to a modern contextual and hermeneutic framework. This systematic literature review aims to map the dynamics of this growth by evaluating the ontological, epistemological, and teleological boundaries of Qur'anic studies within contemporary Islamic scholarship. Utilizing a qualitative Systematic Literature Review (SLR) design, data were gathered from reputable academic journals published over the last decade and analyzed through thematic synthesis. The findings reveal four major transformations. First, an ontological redefinition where the Qur'an is no longer viewed merely as a static written text, but as a performative living discourse, necessitating a strict demarcation between the Qur'an and Hadith to prevent the sacralization of the profane. Second, an epistemological reconstruction that shifts the discipline from mechanistic auxiliary sciences to a holistic-interdisciplinary methodology integrating social sciences and humanities. Third, an expansion of scope beyond textual analysis into applied realities, notably the emergence of Living Qur'an and Digital Qur'an sub-disciplines responding to the disruption of religious authority. Fourth, a teleological shift where the ultimate goal of studying the Qur'an transitions from individual piety to social transformation, serving as an intellectual defense mechanism against post-truth populism and promoting emancipatory theology. The implication of this study suggests that contemporary Qur'anic studies must proactively offer ethical frameworks for global challenges rather than merely preserving historical dogma

Nagari Pandam Gadang is a village in Gunuang Omeh District, Lima Puluh Kota Regency, West Sumatra Province, with an area of 64.00 km² and a population of approximately 5,058. This article aims to present a comprehensive profile of the village, covering aspects of geography, history, public facilities, tourism potential, and the economic conditions of the community. The data in this article is compiled based on the Administrative Map created by KKN students from Padang State University in 2026, supported by field observations and related literature sources. Geographically, this village has a potential natural landscape for the development of the agricultural and tourism sectors. From a historical perspective, Nagari Pandam Gadang is known as the birthplace of national hero Ibrahim Datuk Tan Malaka. In addition, this village has natural tourism potential such as the Many Fish Tourism and the Lotus Cave, which have not been optimally managed. The community's economic condition is still dominated by the traditional agricultural sector. Therefore, an integrated development strategy is needed to improve community welfare through the sustainable utilization of local potential based on local wisdom.

This study aims to examine the contributions of A.M. Sangaji to the field of education during the period of 1922–1949 within the broader context of anti-colonial struggle. This research employs a qualitative method with a historical approach, involving the stages of heuristics, verification, interpretation, and historiography. Data sources are derived from library research, including books, scholarly articles, and relevant historical documents. The findings reveal that A.M. Sangaji’s contributions to education were closely intertwined with his political and social activism within Sarekat Islam. He actively established Qur’anic teaching centers and educational institutions, particularly in East Kalimantan, aimed at enhancing intellectual and religious awareness among indigenous communities. Furthermore, his role as a writer and orator significantly influenced the development of national consciousness and resistance against colonial rule. His integrity, ideas, and commitment to education highlight his substantial role in the history of Indonesian education. This study concludes that A.M. Sangaji’s contributions extended beyond formal education to encompass social, political, and religious education oriented toward the liberation of society from colonial oppression. Therefore, A.M. Sangaji deserves recognition as both an educational figure and a national hero, with enduring relevance for contemporary educational development.

The development of artificial intelligence (AI) has significantly transformed human resource management, particularly in recruitment and employee selection processes. AI-based recruitment systems utilize algorithms to enhance efficiency, speed, and objectivity in evaluating candidates. These systems allow organizations to process large volumes of applications more quickly and identify suitable candidates based on data-driven criteria. However, despite these advantages, the use of AI also presents challenges, especially concerning algorithm transparency and the potential for bias, which may compromise fairness in decision-making. Therefore, the role of human resource (HR) leaders becomes crucial in ensuring that AI systems are implemented in a transparent, accountable, and ethical manner. This study aims to analyze the application of algorithm transparency in AI-based recruitment and examine the role of HR leaders in overseeing and auditing these technologies to minimize algorithmic bias. The research adopts a Systematic Literature Review (SLR) approach by analyzing various scholarly articles related to AI in recruitment, algorithmic bias, and AI governance. The review process includes stages of identification, selection, evaluation, and synthesis of relevant literature from multiple scientific databases. The findings indicate that algorithm transparency is a key factor in developing fair and accountable recruitment systems. HR leaders play a strategic role through oversight mechanisms, algorithm audits, and the establishment of governance policies. Without proper supervision, AI systems risk perpetuating historical biases embedded in training data. Therefore, integrating AI with responsible HR leadership is essential to achieving transparent, fair, and sustainable recruitment practices.