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Market basket analysis is an important technique in data mining used to understand consumer purchasing patterns. This research uses the Apriori algorithm to identify relationships between products in the shopping basket, aiming to improve sales and marketing strategies in the retail industry. The focus of this study is on retail transaction data from West Java Province, which has a large and diverse population, reflecting complex consumer purchasing patterns. The research identifies several key issues: limited understanding of consumer behavior, unoptimized business strategy opportunities, and challenges in managing large transaction data. As a solution, the application of the Apriori algorithm can help find frequent consumer purchasing patterns and design more effective marketing strategies. The results show that market basket analysis using the Apriori algorithm is effective in understanding consumer purchasing patterns in the retail industry. This algorithm allows companies to discover itemsets that frequently appear together in transactions, which can be used to design more effective marketing and sales strategies.

This study aims to examine capital structure, profitability and dividend policy on firm value. This study used a sample of mining companies listed on the Indonesia Stock Exchange for the 2020-2022 period. This sampling method is using purposive sampling. Based on predetermined criteria, a sample of 17 companies was obtained. This research was conducted with a period of 3 years, bringing the total sample to 51 companies. The type of data used is secondary data taken from the company's financial statements. The analysis technique used in this study is multiple linear regression using the SPSS 26 application program. The results show that capital structure (DER) has no effect on firm value (PBV), while profitability (ROA) has a significant positive effect on firm value (PBV). And dividend policy (DPR) has a significant positive effect on firm value (PBV).    

Mining companies are one of the companies that have great prospects in the future. Mining companies are one of the corporate sectors that are targeted for investment, this causes investors to often calculate share returns for their investments in companies in this sector. Stock returns in companies tend to fluctuate or experience erratic increases and decreases in stock returns. The increase or decrease in stock returns is caused by internal and external factors, internal factors can be seen through financial reports and external factors can be seen from macroeconomic and other factors. This research is secondary data, namely it comes from financial reports of mining companies registered in JII70 for the 2018-2022 period. This research is included in the type of quantitative research, using Eviews as a statistical medium and the statistical methods used in this research are multiple linear regression analysis, panel data testing, classical assumption testing, and hypothesis testing. while the results of this research show that partially both Net Profit Margin and Price To Book Value have a positive and significant effect on Stock Returns as well as simultaneously Net Profit Margin and Price To Book Value together or simultaneously have a positive and significant effect on Stock Returns while inflation weaken the relationship Net Profit Margin and Price To Book Value on Share Returns in mining companies registered on JII70.

This research aims to determine the effect of foreign ownership tax and profitability on the implementation of transfer pricing. This research uses a quantitative approach with secondary data in the form of data obtained from mining sector companies registered on the sharia securities list for the period (2017-2022). The sampling method uses purposive sampling with a sample consisting of 7 companies. This research uses data analysis methods, namely multiple linear regression and panel data processed with the SPSS application. The results of this research show that the tax and profitability variables do not have a significant effect on the application of transfer pricing, while foreign ownership has a positive and significant effect on the application of transfer pricing.

The purpose of this study is to ascertain how ownership structure affects dividend policy. The study's sample consisted of 22 mining businesses that were listed between 2021 and 2023 on the Indonesia Stock Exchange. Purposive sampling and panel data regression analysis were the sample strategies used in the investigation. The control variable was profitability, while the dependent variable was dividend policy. The independent variables were government, institutional, and foreign ownership. The findings demonstrate that dividend policy is negatively impacted by foreign ownership and profitability. Dividend policy is not significantly impacted by institutional ownership or the government. It is intended that by focusing on the amount of profit made such that shareholders receive dividend yield, this study would have ramifications for management of businesses. Prospective investors are also anticipated to use this study as a source of information to determine the amount of profit and dividend yield that the firm provides to its shareholders.

Data mining is a technique to dig up new information from a data warehouse, information is seen as very important and valuable because by mastering information it is easy to achieve a goal, this makes everyone compete to obtain information, as well as in trading businesses such as the Iblite Luxury store.  This store is located in Medan close to residents' houses, Sales transaction data will continue to grow, causing data storage to be even larger. Sales transaction data is only used as an archive without being properly utilized. Basically, a dataset has very useful information. Market basket analysis with a priori algorithm is one of the data mining methods that aims to find association patterns based on consumer shopping patterns, so that it can be known what items of goods are purchased in a At the same time, the results of this study found that the highest support and confidence values were Ysl and Chanel with a support value of 50% and confidence of 75%.

Mining is a crucial sector in the global economy, yet it faces high risks and serious potential hazards for workers. According to statistical data from the Ministry of Energy and Mineral Resources, the number of mining accidents in 2023 increased significantly compared to 2021 and previous years, totaling 217 incidents. Therefore, the effective implementation of occupational health and safety management systems (OHSMS) is necessary to protect worker safety and health. The purpose of this writing is to review the implementation of occupational health and safety management systems (OHSMS) in mining companies, covering policy establishment, K3 planning, K3 plan execution, K3 performance monitoring and evaluation, as well as review and enhancement of OHSMS performance. This review employs a Literature Study method, sourcing data and articles from Google Scholar, PubMed, and ScienceDirect. Based on the literature study, the analysis of Occupational Health and Safety Management System implementation reveals that, on average, mining companies have their own policies established. Regarding K3 planning, each company has its own K3 planning strategy. However, the execution of K3 plans shows varying levels of implementation across different companies. In terms of performance monitoring and evaluation, companies assess K3 performance using specific indicators and undertake necessary improvements. Finally, review and performance enhancement efforts are undertaken for continuous improvement.

Rock strength has an important role in the mining industry. These forces can determine many aspects of mining such as slope geometry, excavation, blasting, and drilling. Rock strength can include tensile strength, compressive strength, and shear strength. In this case, the test is carried out to determine the correlation of uniaxial compressive strength and indirect tensile strength. The method used to determine the correlation of compressive strength and indirect tensile strength is by linear regression approach, which will then be analyzed for accuracy through Root Mean Square Error (RMSE), and Mean Absolute Percentage error (MAPE). This study used quantitative and qualitative methods, starting from the coordinate data of rock sampling locations, physical properties and mechanical properties. In this study, there were 6 sampling locations located in 2 different areas, namely Loa Janan and Sanga-sanga. The secondary data used are regional geological maps and maps of the area where the study is located. Furthermore, secondary data is processed using Arcgis software for mapping, and using Microsoft Excel software to assist in calculations in determining the value of physical and mechanical properties of rocks. The results of the compressive and tensile strength tests in this study showed a perfect corelation using linear regression, namely UCS= 3.9582 σt - 0.4004, with a correlation coefficient (R) of 0.972 and a determination coefficient (R2) of 0.945. and obtained RMSE 0.033 and MAPE 5.89%.

Reclamation is an activity carried out throughout the stages of the mining business to organize, restore, and improve the quality of the environment and ecosystem so that it can function again according to its designation (Law No. 3 of 2020). In PT Wijaya Mandiri Energi's mining activities that have been completed, the required activity is to carry out reclamation. In planning reclamation activities, technical reclamation tools are needed. Therefore, in this study, calculations were carried out to determine the number of technical equipment requirements used in reclamation activities that will be carried out in pit 3 south. Based on observations of mining activities carried out in pit 3 south, data is obtained in the form of productivity values of digging-loading equipment, transport equipment and displacement equipment. In this research, the quantitative analysis method is used by calculating the value of the area, productivity and actual working hours so as to obtain the value of the need for digging tools, transport tools and displacement tools needed in reclamation activities to achieve optimal value. As for the research conducted with an area of 5.95Ha and a production target of 208,250 m3, with the productivity of Doosan 500LCV excavator equipment of 218.64 m3 / hour, dump truck of 58.84 m3 / hour and SEM 822D bulldozer of 351.64 m3 / hour, the number of excavator Doosan 500LCV digging and loading equipment is 2 units, Beiben 2642 dump truck of 8 units and SEM 822D bulldozer of 2 units.

PT. Garuda Utama Persada is a company that provides security and loss prevention services to clients in related fields, mining, offices, housing, airports, power plants, factories, hotels, restaurants, banks, hospitals, shopping centers, warehouses and high-rise buildings. The aim of this research is to analyze the influence of training and development programs on employee performance at PT. Garuda Utama Persada. The research was conducted for 3 months (April – June 2024). The data collection method was through interviews and questionnaires which were distributed to 105 respondents. The analysis method is quantitative statistics. Data analysis includes instrument quality tests consisting of validity and reliability tests, classical assumption tests, t tests and F tests. The results of this research show that the training program partially has a positive and significant effect on employee performance (t count 3.114 > t table 1.98350 and sig value 0.002 < 0.05). Partial development has a positive and significant effect on the performance of PT employees. Garuda Utama Persada (t count 3.992 > t table 1.98350 and 0.000 < 0.05). The implication of the results of this research is that providing good training and development programs will improve employee performance.

This study aims to investigate the influence of macro fundamental variables (such as inflation, interest rates, and exchange rates), micro fundamental variables (such as DER, DPR, DR), as well as capital structure variables, financial performance, and ownership structure as intervening variables on firm value in the mining sector on the Indonesia Stock Exchange. This study uses a quantitative approach with secondary data from the financial statements of mining companies listed on the Indonesia Stock Exchange for the period 2010 to 2019. Data collection is done by random sampling of these companies, and data analysis uses the SmartPls 4 application to test the relationship between the variables studied. The results of this study are expected to provide a deeper understanding of how macroeconomic and microeconomic fundamental factors, as well as capital structure, financial performance, and ownership structure, contribute to firm value in the context of the mining sector in Indonesia. The practical implications of this study are expected to provide guidance to stakeholders, including company management, investors, regulators, and academics, in optimizing investment strategies and decision-making in this highly potential sector. This research can also make a theoretical contribution in expanding the understanding of the factors that influence firm value in the mining sector

This research aims to analyze whether there is an influence of Macro Fundamental Analysis, Ownership Structure, Micro Fundamentals on Company Value with Profit Management, Financial Performance and Company Characteristics in Mining Sub Sector Companies Listed on the Indonesian Stock Exchange 2018-2023. The research used in the research is quantitative method research. The type of data used in this research is secondary data obtained from searching and reviewing annual reports of mining companies listed on the BEI (Indonesian Stock Exchange) for the period 2018 - 2023 via the official website www.idx.co.id, the company's official website, and use supporting journals related to this research. The samples used were 6 mining companies selected using a purposive sampling method, then processed or analyzed using the Smart-PLS version 4 application. The results of this research show that Micro Fundamentals have no significant effect on Company Characteristics, while Macro Fundamentals and Ownership Structure have a significant effect. on Company Characteristics. Micro Fundamentals and Ownership Structure do not have a significant influence on Financial Performance, while Macro Fundamentals have a significant influence on Financial Performance. Macro Fundamentals, Micro Fundamentals and Ownership Structure do not have a significant effect on Earnings Management. Macro Fundamentals, Micro Fundamentals, Company Characteristics, Financial Performance, Earnings Management and Ownership Structure do not have a significant effect on Company Value.      

Research on forecasting new student admissions at SD Negeri 10 Koto Tinggi Surian employs data analysis using simple linear regression to predict the number of new students based on previous years and formulate it into a mathematical model. In its calculation process, this approach can adopt both quantitative and qualitative methods. The prediction error rate for the next year is very low. Out of 41 predicted students, only one differs from the actual number. The study's data spans student admissions from 2019 to 2023. The research findings demonstrate the effectiveness of conventional linear regression techniques. The prediction for 2023 indicates an intake of 42 students. Therefore, it can be concluded that simple linear regression accurately predicts new student admissions at SD Negeri 10 Koto Tinggi Surian with high accuracy.    

This research discusses the causes of the crime of transporting black stone in the jurisdiction of the Gorontalo Regional Police and efforts to overcome it. The method used in the research is empirical with qualitative descriptive data analysis which describes and describes data and field facts. Based on research results, Gorontalo is in 5th position in the province with the highest poverty; and The lack of public understanding and knowledge regarding mining, where the lack of public knowledge, influences the existence of illegal mining. This situation is based on a lack of education and understanding as the main factors in the community's decision to carry out illegal mining actions, including a lack of socialization and legal education to the community. The prevention of criminal acts of transporting black stone by the Gorontalo Regional Police is carried out through initial efforts made by the police, in this case the Gorontalo Regional Police, namely visiting or visiting the community and providing advice regarding mining activities. Apart from that, conduct patrols in mining areas for early handling, especially checking permits for heavy vehicles used in mining areas, including transport vehicles. Not only that, legal counseling and socialization is also carried out to the community as a first step in overcoming this criminal act; and Repressive Efforts by taking action against the perpetrators, in order to have a deterrent effect. This step is carried out through investigations, inquiries and other coercive measures authorized by law, which end with the application of criminal sanctions against the perpetrators.

This study aims to determine the adaptation strategies carried out by kja farmers in ex-mining ponds, to see the social conditions of kja farmers and to find out the problems faced by kja farmers. The research location was chosen in the ex-mining pond of Bangun Rejo Village, Tenggarong Seberang District. The type of research data used in this study uses primary data and secondary data. The sampling technique used in this study was purposive sampling. The data analysis used is qualitative descriptive analysis. The results showed that there are several adaptation strategies carried out by kja farmers in ex-mining ponds so that the business continues to be sustainable, namely, selecting the right fish species, collaborating with related parties, managing water quality, making independent feed and expanding marketing networks. The social conditions of kja farmers can be seen from the aspects of education, livelihoods and cooperation between networks. Problems faced by kja farmers include difficulties in obtaining activity permits, lack of support from the government, rising feed prices and irregular payment of results.

The determination of changes in the land surface is an event caused by changes in the volume of the rock layer below. and geological processes such as tectonic and volcanic activity, removal of material from the subsurface such as mining and natural causes such as the occurrence of holes in limestone. The purpose of this study is to determine the magnitude of land surface changes that occur in the Nias Island area caused by earthquakes. The data used in the processing stage with the DinSAR method in 2022 recording, with specifications of dual polarization VV + VH, beam mode IW (interferometric wide) and flight direction ascending. Sentinel 1 data used in this study are 4 pairs of scans, where each pair of scans consists of one scans being the master and another scans being the slave. The master image is the SAR image before the earthquake, while the slave image is after the earthquake. The magnitude of land surface changes that occurred on Nias Island, based on the 2022 earthquake, the largest uplift was the earthquake on December 30, 2022, with a range of values (1.012042) mm with an area of 72,641,981 Hectares. The largest subsidence occurred in the earthquake on December 30, 2022, with a range of values ranging from (-1.373125) mm to (-1.235427) mm with an area of 61347,891 Hectares.

The aim of limestone mining activities is to obtain the main raw material, namely limestone, which can then be used as a construction raw material such as cement. This data collection method is to collect primary data obtained from identifying activity locations and secondary data obtained from Journal Reviews and other scientific articles and then compiling them into a narrative. From the results of this analysis, it can be seen that there is a positive impact, namely the recruitment of workers from the local area and a negative impact, namely a decrease in ambient air quality, a decrease in water quality, soil erosion, disruption of flora and fauna and plant vegetation.

The purpose of the study was to determine the economic sector and economic change in Halmahera Seletan district, secondary data from 2019-2023, descriptive quantitative research methods, LQ and SSA analysis tools. The results of the study, the economic sector which is the basic sector is in the agriculture, forestry and fisheries economic sector, the mining and quarrying sector, the manufacturing sector, the water supply sector, waste management, waste and recycling, the construction sector, the wholesale and retail trade sector, car and motorcycle repair, and the real estate sector, the education services sector, the health services sector and social activities, the economic sector is the basic sector but the regional component of the economic sector in South Halmahera district does not have economic growth, But in the proportional growth component (proportional shift) is a developed economic sector to be developed, the agriculture, forestry and fisheries sector, the mining and quarrying sector, the processing industry sector, the water supply sector, waste management, waste and recycling, the construction sector, the wholesale and retail trade sector, car and motorcycle repair is a basic sector but in the competitiveness share this sector is not a sector that has high economic competitiveness within the South Halmahera district area and economic sectors from other regions.)  

The increasing popularity of e-commerce has driven the development of more sophisticated product recommendation systems to enhance user experience. Within this framework, the incorporation of Artificial Intelligence (AI) has become essential for enhancing the caliber of product suggestions through the examination of user behavioral patterns and product attributes. This paper explores the incorporation of artificial intelligence into e-commerce product recommendation systems. This strategy integrates AI methodologies like machine learning, data mining, and natural language processing (NLP) to produce recommendation systems that are personalized and pertinent. Through in-depth analysis of user data and product information, the system can predict user preferences with higher accuracy, improve user engagement levels, and ultimately increase sales conversions. By combining domain knowledge, technical expertise, and the latest research methodologies, This research offers valuable insights for both e-commerce system developers and artificial intelligence researchers. The integration of artificial intelligence into product recommendation systems represents a critical measure in facilitating growth and fostering innovation within the ever-changing e-commerce landscape.  

Community Service Activities to examine countermeasures against mineral and coal mining crimes in the jurisdiction of the Gorontalo Regional Police and the Inhibiting Factors. The activity method is field study, the research method used in the research is empirical with qualitative descriptive data analysis which describes and describes field data and facts. Based on the results of the research, the handling of mineral and coal mining crimes in the jurisdiction of the Gorontalo Regional Police is carried out by carrying out repressive efforts. This activity includes a series of actions aimed at uncovering cases that have occurred, where the stages start with a series of inquiries, inquiries and other coercive measures authorized according to the law. Carrying out preventive efforts, including a series of activities aimed at preventing crimes before they occur, where investigators make arrangements for security, including conducting patrols at locations thought to contain indications of criminal acts. In relation to criminal acts, especially mining, the Gorontalo Regional Police provides guidance and encouragement to the community to actively participate in efforts to prevent and ward off crime, by reporting suspicious incidents; and Carrying out pre-emptive efforts, starting from conducting an analysis of regional conditions and potential vulnerabilities, collaborating with related elements, to anticipate violations or crimes. The inhibiting factors in dealing with mineral and coal mining crimes in the Gorontalo Regional Police are: Legal Content Factor, where the imposition of sanctions does not include the threat of a minimum sentence, thus affecting the police, public prosecutors and judges' decisions to be less strong; Law Enforcement Factor, where officials can be a supporting factor in the implementation of the law, or actually become a protector for the perpetrator; Community Cultural Factors relate to the basic values ​​of what is good and what is bad, in order to support the implementation of law, which originates from the community's legal understanding and attitudes or behavior. Facilities and facilities factors, where the police have constraints in terms of the number of competent human resources, thereby maximizing the role of PPNS investigators from other agencies.