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In Indonesia, illegal gold mining (PETI) is still a persistent environmental crime, especially in resource-rich areas like Bungo Regency, Jambi Province. The efficacy of local law enforcement is still in doubt, despite the fact that Article 158 of the modified Mining Law (Law No. 3 of 2020) offers a solid legal foundation for criminal penalties. The purpose of this study is to evaluate the efficacy of criminal law enforcement in Bungo Regency against PETI from the standpoint of Islamic law based on maqāṣid al-sharī‘ah. This study uses a juridical-empirical approach, combining pertinent court rulings, field data from law enforcement, and normative legal analysis. The results show that although legal measures like arrests and convictions have been carried out, they have not had a major deterrent effect. The overall effect of enforcement operations is weakened by structural issues, such as the economic dependence of local populations, the scarcity of alternative livelihoods, and the difficulties of prosecuting informal financiers. According to maqāṣid al-sharī‘ah, illicit mining is incompatible with the defense of basic principles, especially the preservation of life (ḥifḍ al-nafs), property (ḥifṢ al-māl), and environmental sustainability. The study comes to the conclusion that effective law enforcement necessitates an integrated strategy that combines preventive and rehabilitative tactics, such as economic empowerment, legal awareness campaigns, and regular supervision, with repressive measures. A more equitable, long-lasting, and socially conscious form of environmental criminal law enforcement is provided by combining positive law with the ethical framework of maqāṣid al-sharī‘ah.

Soil strength characteristics are strongly influenced by its physical and mechanical properties, one of which is shear strength. Soil shear strength is affected by cohesion (c), internal friction angle (ϕ), and soil moisture conditions. In open-pit mining conditions, soil moisture content is greatly influenced by rainfall and water seepage, which can increase the degree of saturation within the soil mass. An increase in the degree of saturation generally leads to a rise in pore water pressure, thereby reducing the effective normal stress and resulting in a decrease in soil shear strength. This study aims to determine the effect of the degree of saturation on soil shear strength. This research employs a quantitative method to analyze the influence of the degree of saturation under three conditions (natural, dry, and saturated) on soil shear strength through laboratory testing using the direct shear test. The tests conducted include soil physical properties testing in accordance with SNI 1965-2008, specific gravity testing based on SNI 1964-2008, and soil shear strength testing following SNI 3420-2016. The results indicate that the average degree of saturation under natural conditions is 64.63% with a cohesion value of 7.4 kN/m², under dry conditions is 33.18% with a cohesion value of 8.2 kN/m², and under saturated conditions is 83.08% with a cohesion value of 3 kN/m². It can be concluded that a higher degree of saturation or more saturated soil samples result in lower cohesion values, whereas a lower degree of saturation or drier soil samples lead to higher cohesion values.

This study aims to examine the effect of leverage and institutional ownership on tax avoidance, with profitability as a moderating variable, in plantation sector and mining sector companies listed on the Indonesia Stock Exchange (IDX) during the 2020–2024 period. This study employs a quantitative research method. The sample was selected using a purposive sampling technique, resulting in 16 companies as the research sample, with a total of 80 observations. Data analysis is conducted using multiple linear regression and moderated regression analysis (MRA). The results indicate that leverage and institutional ownership do not have a significant effect on tax avoidance. Furthermore, profitability is unable to moderate the relationship between leverage and tax avoidance as well as between institutional ownership and tax avoidance. This study has limitations related to the relatively small sample size, as many companies experienced losses during the observation period and therefore did not meet the sample selection criteria.

Mine slopes play a crucial role in ensuring the safety and sustainability of mining activities. Continuous mining operations can alter slope conditions, thereby increasing the potential for instability and slope failures. Slope stability is influenced by the balance between resisting forces and driving forces acting on the rock mass. When the resisting forces are smaller than the driving forces, the slope becomes unstable and failure may occur. Therefore, slope stability analysis is essential to prevent landslide hazards, as it directly affects occupational safety, equipment security, other assets, and overall production continuity. These conditions have encouraged PT Insani Bara Perkasa to develop a more accurate and real-time slope monitoring system. The application of radar-based monitoring was initiated using the CHCNAV PS-2000 system. This study aims to analyze the deformation behavior of mine slopes using radar technology. Data acquisition was conducted at Pit K1 Mahakam, PT Insani Bara Perkasa, covering Area 1 South, AR 2 South, AR 3 South, AR 5 South, AR 6 South, AR 7 West, AR 8 West, AR 9 South, AR 13 South, as well as TA-2, TA-3, and TA-6 areas. The study was carried out from November 2025 to December 2026. The analysis results indicate that most monitoring points are in stable conditions, with indications of a progressive phase observed in the AR 6 South area.

Measuring coal volume in the Stock ROM area played an important role in production control and mining evaluation. This research was conducted in the Stock ROM area at PT. Victor Dua Tiga Mega, where volume measurements were generally carried out using Total Station (TS) as the main method, howefer the use of Unmanned Aerial Vehicles (UAV) has begun to be implemented as a more efficient alternative. This study aims to compare the results of Stock ROM coal volume calculations using the Total Station and UAV methods. The research method was carried out by collecting data in the field, processing the digital Elevation Model (DEM), and calculating the volume using the Cut and Fill method. The results of the study the difference in volume between the two methods, where the UAV measurement results tend to be greater than those of the Total Station. The difference in Fine Coal volume was 724,15 m3 or 16,74% and Raw Coal volume of 9.335,98 m3 or 8,03%. Based on a comparison with weighing data, measurements using the Total Station provided results that were closer to the actual conditions in the field.

The mining sector is widely recognized as a high-risk industry characterized by complex social, environmental, and organizational challenges. In response, sustainability governance in mining has predominantly relied on institutional mechanisms such as regulations, voluntary standards, and sustainability reporting frameworks. However, growing evidence indicates that these approaches often fail to generate substantive sustainability outcomes because they insufficiently address human and organizational dimensions. This literature review aims to synthesize existing research on sustainability governance in the mining sector by shifting the analytical focus from institutional sustainability to human behavioral engagement. Using a systematic and thematic literature review approach, this study analyzes peer-reviewed articles indexed in Scopus that examine sustainability governance, human behavior, and organizational dynamics in the mining sector. The findings reveal a persistent gap between formal sustainability commitments and actual practices, frequently manifested in symbolic compliance and greenwashing. The review further demonstrates that human behavior—shaped by employee engagement, trust, perceived justice, and organizational culture—plays a decisive role in determining the effectiveness of sustainability governance. Moreover, the literature highlights the limitations of rigid, top-down governance models in managing the complexity and uncertainty inherent in mining systems, emphasizing the relevance of adaptive governance approaches that promote learning, flexibility, and stakeholder participation. This study contributes to the literature by integrating institutional, behavioral, and adaptive governance perspectives into a human-centered framework. Practically, it underscores the strategic role of human resource management in translating sustainability commitments into meaningful behavioral change and long-term sustainability outcomes in the mining sector.

This study aims to analyze the effect of transformational leadership and compensation on job satisfaction with employee performance as an intervening variable at PT Cipta Kridatama Site KIM Jambi. This research employed a quantitative approach using a survey method. The population of this study consisted of all employee of PT Cipta Kridatama Site KIM Jambi totaling 862 employees. The sample was determined using the slovin formula with a 10 percent error tolerance, resulting in 90 respondents. The sampling technique used was proportionate stratified random sampling. Data were collected through structural questionnaires and analyzed using Structural Equation Modeling based on Partial Least Squares (PLS-SEM) With The Assistance Of Smartpls 3 Software.  The result of  the study indicate that transformational leadership and compensation have a positive and significant effect on employee performance. Transformational leadership and compensation also have a positive and significant effect on job satisfaction. Furthermore, employee performance has a positive adn significant effect an job satisfaction.  The mediation test result show that employee performance is able to mediate the effect of transformational leadership and compensation on job satisfaction.These findings suggest that improving job satisfaction cannot be achieved solely through leadership and compensation policies, but also requires efforts to enhance employee performance. Therefore, organizations are encouraged to implement effective transformational leadership practices and fair compensation systems to improve employee performance and job satisfaction, particularly in high demand industries such as mining services.

The spread of hoax news in digital media is a serious problem because it can affect public opinion and social stability. This study aims to classify hoax news using the Support Vector Machine (SVM) algorithm. The dataset used is a hoax clarification dataset from the Ministry of Communication and Digital (Komdigi) of the Republic of Indonesia, totaling 1,872 data. The research process includes data collection, text pre-processing, feature extraction using TF-IDF, and classification using the SVM algorithm. Implementation was carried out using Google Colaboratory (Google Colab). Test results show that the SVM algorithm is able to provide good performance in classifying hoax news based on its topic with satisfactory accuracy, precision, recall, and F1-score values.

Open-pit mining activities in Indonesia contribute significantly to the national economy but require stringent monitoring to mitigate environmental degradation. Conventional monitoring methods relying on terrestrial surveys are often constrained by vast coverage areas, high operational costs, and limited field accessibility. This study aims to develop an artificial intelligence model capable of automatically detecting and mapping mining areas to enhance surveillance efficiency. The applied method is Deep Semantic Segmentation utilizing the U-Net Convolutional Neural Network (CNN) architecture. The model was trained using Sentinel-2 satellite imagery, focusing exclusively on Red, Green, and Blue (RGB) spectral channels to replicate human visual perception. Experimental results demonstrate that the proposed model performs reliable segmentation of mining areas, achieving an Accuracy of 93.58% and a Global Intersection over Union (IoU) of 0.8067. These findings indicate that the U-Net architecture can effectively extract spatial features of mines even when utilizing standard visual data. This research contributes to the development of an efficient, cost-effective, and scalable digital monitoring prototype to support innovation in sustainable environmental governance.

Law Number 11 of 2006 on the Governance of Aceh embodies the principle of lex specialis due to its territorial scope, while Law Number 4 of 2009 on Mineral and Coal Mining also contains a lex specialis character as it specifically regulates the mining sector. This situation raises a legal question regarding how the principles of lex specialis derogat legi generali, lex superior derogat legi inferiori, and lex posterior derogat legi priori should be interpreted and applied by the Government within the framework of Aceh as a Special Autonomous Region. This study aims to conduct an in-depth legal analysis using a progressive law approach to examine whether the principles of lex posterior or lex superior may override the principle of lex specialis as applied in Aceh’s special autonomy regime. The research employs normative legal methods with qualitative analysis. The findings indicate that the principle of lex specialis derogat legi generali as stipulated in the Law on the Governance of Aceh must take precedence due to its specific territorial applicability and special autonomous status. In resolving such normative conflicts, a clear legal framework is required, accompanied by the renewal of legal theories and principles to ensure legal certainty, prevent regulatory overlap, and promote harmony among statutory regulations.

The stability of disposal slopes is a critical aspect of open-pit mining operations because it directly affects operational safety and the continuity of overburden dumping activities. Disposal areas composed of overburden materials generally exhibit heterogeneous characteristics, particularly when soft materials such as mud are present, which can significantly reduce slope stability. Therefore, a comprehensive slope stability evaluation is required prior to further disposal development. This study aims to assess the stability condition of a disposal slope under initial conditions, evaluate the influence of material conditions, and analyze the effectiveness of counterweight application in improving both the safety factor and disposal capacity. The research methodology involved the collection of primary and secondary data, including slope geometry, lithological conditions, and the physical and mechanical properties of disposal materials obtained from laboratory testing and company technical data. Slope stability analysis was performed using the limit equilibrium method with the assistance of geotechnical software, taking into account groundwater conditions and operational loading. The analysis results indicate that the initial disposal condition yielded a safety factor of 0.718, indicating an unstable slope condition. After simulating the removal of mud material, the safety factor increased to 0.907 but remained below acceptable stability criteria. The application of a counterweight significantly improved slope stability, resulting in a safety factor of 1.498. Further optimization through slope geometry redesign produced a final safety factor of 1.101, which satisfies the requirements stipulated in KEPMEN ESDM No. 1827 K/30/MEM/2018. Additionally, the redesign increased the disposal capacity from 119,507,864.23 LCM to 119,682,378.22 LCM, representing an increase of 174,513.99 LCM. These results demonstrate that counterweight application combined with geometric optimization is effective in enhancing both slope stability and disposal capacity.

The auditor's responsibilities include not only assessing the accuracy of financial statements and detecting fraud, but also evaluating the company's ability to continue its business on an ongoing basis. This responsibility arises from the expectations of shareholders and other stakeholders that auditors provide timely and relevant information about the company's future prospects to support rational and evidence-based investment decision-making. In this context, audit opinions related to business continuity are an important instrument in reducing information asymmetry between management and investors. This study aims to analyze the impact of liquidity, solvency, and audit quality on the issuance of business continuity declarations. The research sample consisted of coal mining companies listed on the Indonesia Stock Exchange between 2014 and 2017, a period marked by fluctuations in commodity prices and global economic uncertainty. Logistic regression is used as an analysis method because dependent variables are dichotomous. The results showed that audit quality had a significant negative impact on the issuance of business continuity declarations, while liquidity and solvency did not have a significant impact on the issuance of the declarations, indicating that the factors of governance and auditor independence were more decisive than short-term financial conditions.

Regional economic development requires a comprehensive understanding of the structure, potential, and dynamics of economic sectors so that formulated policies can be targeted and sustainable. Bojonegoro Regency as one of the regions in East Java Province has unique economic characteristics with the dominance of certain sectors, so it is necessary to conduct an in-depth analysis of the economic sectors that play a role in driving regional growth. This study aims to identify basic and non-basic sectors, analyze the dynamics of changes in economic sectors, and assess the sectoral competitiveness of Bojonegoro Regency compared to East Java Province. This study uses a quantitative approach with secondary data in the form of Gross Regional Domestic Product at constant prices by business field obtained from the Central Statistics Agency. The analytical methods used include Location Quotient, Dynamic Location Quotient, and Shift Share. The results show that the mining and quarrying sector remains the sector with the most dominant relative advantage in the economic structure of Bojonegoro Regency. However, the analysis of dynamics and competitiveness indicates that several non-extractive sectors are starting to show faster development and growth potential. This finding suggests an opportunity for transformation of the regional economic structure towards a more diverse pattern. The implications of this research emphasize the importance of regional economic development strategies that do not only rely on traditional leading sectors, but also encourage the development of more sustainable potential sectors.

Regional economic development requires understanding the structure and performance of economic sectors to create effective policies. PadangiCity, the capital of West SumatraiProvince, plays a strategic role in the regional economy. However, differences in sector contributions and growth indicate structural imbalances that need attention. This studyiaims to identify leading and potential economic sectors in Padang City to support sustainable development planning. The study uses Location Quotient (LQ), iDynamic Location Quotient (DLQ), and the Growth Ratio Model (GRM) to analyze secondary data on GrossiRegional Domestic Product (GRDP) at constant 2010 prices from 2020 to 2024, sourced from the CentraliBureau of Statistics of Padang City and West Sumatra Province. LQ results show that most sectors in Padang City are base sectors, especially business services, transportation and warehousing, ifinancial and insurance services, real estate, and wholesale and retail trade. DLQ analysis indicates that mining and quarrying, trade, transportation and warehousing, iinformation and communication, and health and social services have higher growth prospects than the reference region. GRM results show that trade, information andicommunication, real estate, health services, andiother services are leading sectors with good performance and growth potential. In contrast, agriculture, manufacturing, and construction are still lagging sectors. These findings highlight a structural shift in Padang City’s economy toward service-sector dominance and underline the need for sustainable, inclusive, and adaptive development policies to support long-term economic growth.

This study aims to analyze consumer purchasing behavior on e-commerce platforms using the Decision Tree algorithm as an easily interpretable classification method. The dataset used consists of 12,330 transaction records with 18 attributes representing visitor characteristics and user activities during interactions with the e-commerce platform. The research stages include data exploration to identify initial patterns, data preprocessing to handle missing values and class imbalance, splitting the data into training and testing sets, training the Decision Tree model, evaluating model performance, and visualizing the tree structure to analyze decision rules.The test results show that the Decision Tree model with a maximum depth of 3 achieves fairly good performance, with an average accuracy of 89.78%, precision of 69.82%, recall of 59.95%, and an F1-score of 64.51% for the buyer class. The visualization of the decision tree provides clear interpretation of the main attributes influencing purchasing decisions, thereby facilitating understanding for non-technical decision makers. Overall, this study demonstrates that the Decision Tree method is effective in modeling consumer purchasing behavior in e-commerce and can be utilized as a basis for data-driven business decision making, particularly in marketing strategies and improving sales conversion rates.

Diabetes Mellitus is one of the chronic diseases with high morbidity and mortality rates, making data-driven analysis necessary to understand patient mortality patterns. This study aims to analyze the mortality rate of Diabetes Mellitus patients based on age and length of hospitalization using a data mining approach with the K-Means Clustering method. The study employs a quantitative approach using secondary data obtained from the medical records of Diabetes Mellitus patients at Ibnu Sina Regional General Hospital, Gresik Regency, in December 2022. The dataset consists of 266 patient records with variables including age, length of stay, and final patient status. Data analysis was conducted through preprocessing stages, including data cleaning, transformation, and normalization, followed by the clustering process using the K-Means algorithm with the assistance of the RapidMiner application. The results show that patient data are divided into three clusters based on age ranges: 0–40 years, 41–55 years, and 56–90 years. The cluster with the age range of 56–90 years has the highest number of patient deaths compared to the other clusters. Meanwhile, the length of hospitalization does not show a significant effect on patient mortality. This study is expected to serve as a consideration for hospitals and health institutions in efforts to prevent and manage Diabetes Mellitus, particularly among the elderly population.

Football in Indonesia is not merely a sport but a social phenomenon that triggers massive public emotional engagement. Every result of the Indonesian National Team, particularly in prestigious events such as the FIFA World Cup Qualifiers, often generates waves of opinion in digital spaces filled with criticism, support, and disappointment. The failure of the Indonesian National Team in the 2026 FIFA World Cup Qualifiers has become an important momentum to systematically understand public perception. The purpose of this study is to identify the distribution of public sentiment and to reveal the main issues most frequently discussed through keyword visualization, thereby providing an overview of societal reactions. This research utilizes 971 comments from the TikTok platform as the primary dataset, collected through a crawling process and processed using text mining stages before being classified with a sentiment analysis method. The findings indicate a sentiment distribution dominated by Neutral at 63.67%, Negative at 32.36%, and Positive at 3.97%. The word cloud visualization highlights dominant keywords such as “Pecat” (Dismiss), “Evaluasi” (Evaluation), and “PSSI” (Indonesian Football Association), reflecting public criticism of managerial aspects, although positive words such as “Semangat” (Spirit) and “Dukung” (Support) also appear, emphasizing supporter loyalty. These results contribute to an empirical understanding of the issues most highlighted by the public and the distribution of collective emotions, which can serve as a basis for PSSI and stakeholders in formulating communication strategies, policy evaluations, and improvements to the national football management system.

Savings and Loan Cooperatives (KSP) play a vital role in expanding community access to capital, especially within the informal sector. Nevertheless, non-performing loans remain a persistent challenge that can threaten liquidity and long-term institutional sustainability. KSP CU Mera Ndi Ate faces similar issues, which are assumed to stem not only from administrative weaknesses but also from members’ perceptions and behavioral factors. This research aims to examine the potential causes of non-performing loans through text-based sentiment analysis using an unsupervised learning approach. A quantitative method with a data mining framework was applied. Data were gathered through interviews, observations, documentation, and 200 customer opinion texts processed using the Orange Data Mining application. The analytical stages included preprocessing, corpus development, feature extraction, sentiment clustering, and visualization. Because the dataset lacked predefined labels, unsupervised learning was used to identify naturally emerging sentiment patterns. Findings reveal a predominance of critical sentiments related to credit assessment procedures and service quality. The highest sentiment score (75) concerned insufficient creditworthiness evaluation, followed by concerns about service efficiency (66.6667). These insights suggest that improving assessment accuracy and service quality may help reduce non-performing loans.

Tax Management refers to a company’s efforts to manage its tax obligations efficiently and legally in order to optimize net income. This study aims to examine the effect of Fixed Asset Intensity and Leverage on Tax Management, with Profitability as a moderating variable, in mining companies listed on the Indonesia Stock Exchange (IDX) for the 2021–2024 period. This research is conducted because tax management practices are considered to potentially influence corporate profitability and financial performance. The study is grounded in Agency Theory and employs a quantitative approach. The sample was selected using purposive sampling, resulting in 28 companies observed over four years, with a total of 112 secondary data observations obtained from annual reports or financial statements. Data analysis was performed using EViews 13 with a Moderated Regression Analysis (MRA) approach. The findings indicate that: (1) Fixed Asset Intensity has no significant effect on Tax Management; (2) Leverage has a significant negative effect on Tax Management; (3) Profitability does not moderate the relationship between Fixed Asset Intensity and Tax Management; and (4) Profitability strengthens the effect of Leverage on Tax Management.

Mining companies are increasingly required to demonstrate environmental, social, and governance (ESG) accountability through sustainability reporting (SR). However, empirical evidence regarding the impact of SR on firm value in Indonesia’s mining sector remains inconsistent. This study aims to systematically examine the relationship between sustainability reporting and firm value using legitimacy theory as the conceptual framework. A Systematic Literature Review was conducted following the PRISMA 2020 protocol, employing narrative and thematic synthesis. Peer-reviewed articles published between 2018 and 2025 were retrieved from Google Scholar, Garuda Portal, and SINTA databases using relevant keywords. From 4,260 initial records, 11 studies met the inclusion criteria after screening, deduplication, and quality appraisal using an adapted CASP checklist. The findings reveal three dominant patterns: most studies report a positive effect of SR on firm value through improved transparency, corporate reputation, and investor confidence; several studies find no significant relationship due to short-term investor orientation; while a minority report negative effects associated with low disclosure quality and greenwashing concerns. Furthermore, the effectiveness of SR is influenced by disclosure quality, corporate governance, profitability, and leverage. This study implies that sustainability reporting can enhance firm value when disclosures are credible, consistent, and material, supporting legitimacy theory and encouraging alignment with the GRI 14: Mining Sector 2024 standard.