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Currently we cannot escape the influence of information technology. Because like it or not, the development of science and the application of technology is experiencing an increasingly rapid increase, especially in every work environment such as business practitioners.Computer/information technology is the technology that is most widely used in various agencies, both government and private. The rapid development of technology over time means that human work can generally be completed quickly. Technology is a tool that is often used in human activities. The role of technology today makes information processing easier because processing is necessary so that the resulting information can be useful for its users. Competition in the business world requires developers to find a pattern that can increase sales and marketing of goods, one of which is by utilizing transaction data. The availability of abundant data, the need for information to support decision making to create business solutions, and infrastructure support in the field of information technology are the reasons for the birth of data mining technology. Problems that occur at UD. Martua is lacking in reviewing the products being sold, what products consumers need and less effective data storage. With data mining, it is intended to provide real solutions to UD. Martua can find out which items are selling well and which items are not selling well, then can compare sales from year to year to become an effective medium for developing sales at UD.Martua. In grouping sales data, the fields used are item name, quantity purchased, quantity sold for 1 week, then the data will be processed with the k-means clustering algorithm. The final result with 20 grouping data samples was the final result with 2 clusters, namely, cluster 1 (C1) with 10 best-selling items, cluster 2 (C2) with 10 non-selling items. With data mining using the K-Means algorithm, losses for UD.Martua..speeding up decision making to restock goods that are selling well so that consumers who want to buy don't have to wait long. Providing information from sales data to find out what causes profits or losses at UD.Martua. Providing convenience for UD.Martua in determining which products are selling and which are not selling so that there is no accumulation of goods that are not selling and resulting in losses for UD.Martua.

The large number of ex-illegal gold mines in Setajo Raya Subdistrict which was caused by illegal mining activities made the former mining land abandoned by the miners and no longer used. The number of losses incurred from these PETI activities include: changes in the color of river water, damaged soil due to excavation, river pollution. Seeing the condition of the problems that exist in the District of Setajo Raya, a research was carried out on "Utilization of Ex- Mining Gold Without Permits in Sentajo Raya District". This study aims to identify the use of ex-gold mining land without a permit in Sentajo Raya Subdistrict to minimize the bad effects of the former PETI mining and reuse the land. To achieve the goal, there are 3 (three) research objectives, namely Identifying the distribution of ex-mining gold without a permit in Sentajo Raya District, Identifying the potential for exploitation of ex-gold mining without a permit in Sentajo Raya Subdistrict and developing a strategy to use land for ex-gold mining without a permit in Sentajo Raya District. . This study uses spatial analysis which is used to identify ex-mining land with field observation methods, qualitative and quantitative analysis is used to determine the use of ex-mining land with a questionnaire method of 99 respondents and SWOT analysis is used to determine the strategy of using ex-mining land. The distribution of former gold mining without a permit in Sentajo Raya District has 8 points, the number of distribution of former gold mining. Potential land use there are 4 types of land use that can be used as a strategy for exploiting ex-gold mining land, namely, as fish farming land, tourist attractions, reservoirs, and agriculture. permits in Sentajo Raya District are used for fish cultivation

Data mining is a technology that plays an important role in supporting data-driven decision making, especially in complex and dynamic higher education environments. In the context of education management, the ability to predict student graduation is an essential aspect because it can help institutions plan strategic steps, intervene earlier, and optimize academic resources. This study aims to apply the C4.5 decision tree algorithm to build a student graduation prediction model based on academic data. The research dataset includes key variables such as Grade Point Average (GPA), total Semester Credit Units (SKS) taken, and student attendance rates during lectures. The analysis was conducted using the C4.5 algorithm, which is known for its high level of interpretability, making the model results easy to understand by policy makers. The test results showed an accuracy of 84.6%, indicating that this method has the potential to support data-based academic management systems. These findings are expected to serve as a basis for educational institutions to improve the effectiveness of monitoring and evaluating the student learning process.

This study aims to determine the effect of the current ratio, debt to equity ratio and net profit margin on the share prices of mining companies listed on the Indonesian stock exchange in 2020-2022. The research data were 60 companies and a sample of 5 companies was obtained, using a purposive sampling technique. The data analysis technique used is Simple Linear Regression Analysis and Multiple Linear Regression Analysis. The results showed that the current ratio partially has a significant effect on stock prices, the debt to equity ratio partially has a negative and insignificant effect on stock prices, while the net profit margin partially has a significant effect on stock prices. And simultaneously the current ratio, debt to equity ratio, and net profit margin have a significant effect on stock prices.

This study aims to examine the effect of corporate social responsibility and capital intensity on tax evasion by using research samples of mining sector companies listed on the Indonesia Stock Exchange in 2019 - 2020. The taxes levied by the state function as the main source aiming to finance public expenditures and function as a tool to regulate and implement policies in the social and economic fields and to be used for the greatest prosperity of the people and the people. The phenomenon of tax avoidance in Indonesia can also be seen from the tax ratio (Tax Ratio). Tax collection performance can be seen from the ratio of taxes collected by the state. Tax avoidance is a saving on the amount of tax payable, individual and corporate taxpayers use the weak points of existing tax rules, in carrying out their tax management. Tax avoidance is also associated with tax planning, both of them use legal means to reduce or even eliminate tax obligations, but from a tax policy point of view, neglecting tax avoidance practices can result in injustice and reduced efficiency of a tax system. . The results obtained from this study are that corporate social responsibility has a negative effect on tax evasion. Meanwhile, capital intensity has no effect on tax evasion. This study uses a quantitative approach. This test is done with linear regression

The Bunda Jombang Housing development project is a project that has a land area of ​​31,401 hectares, where this housing development project was previously located on a former quarry land (Andim Rendy S, 2022), therefore it is necessary to carry out land work (land clearing) to restore the existing land structure. damaged as a result of previous mining activities. Researchers schedule earthworks so that there are no deviations from the planned schedule. An appropriate scheduling method is needed for efficient and effective utilization of the resources used. Research using the Precedence Diagram Method has the aim of analyzing implementation time and being able to determine effective scheduling for continuous work in housing development projects. (Author, 2021)

Schools will receive assistance from recipients of boss funds at school X implementing a program from the government to provide BOS assistance to underprivileged school children in School X. The Bos Assistance Program is a government assistance program in the form of providing cash to underprivileged school children or families capable. Implementation of the program aims to improve the welfare of the less fortunate. Currently, the distribution of Bos Fund Assistance is considered to be still not on target and does not meet the criteria that are used as benchmarks for the people who will receive the assistance. The Naïve Bayes method is used in this case study to classify which children can and cannot afford school fees so that it can more easily select school children or families who are truly eligible to receive the Bos Fund Assistance. This study uses 20 data and 5 criteria including: name, age, gender, status, income, and beneficiary status. After conducting research with a total of 20 data and using the Naïve Bayes method, the results obtained were as many as 45% of underprivileged children and families who were eligible to receive Boss Fund Assistance and as many as 55% of children and families who were not eligible to receive Assistance Boss Fund..

This study aims to examine the effect of Ownership Institutional, Leverage, and Size Board Commissioner on CSR disclosure with Company Size as variable moderation. Population in this study is company Mining listed on the Indonesia Stock Exchange in 2019-2022, Samples obtained as many as 48 of 12 companies, taking sample use technique Purposive Sampling. Data used on study This is secondary data. Data analysis study this using an alternative structural equation modeling (SEM) using SmartPLS. The results of this study show Size Board Commissioner have a positive significant on CSR disclosure with level significant of 0,041<0,05. Institutional Ownership and Leverage have no effect on CSR disclosure. Company size cannot moderate Institutional Ownership, Leverage and Board of Commissioners Size on CSR disclosure.  

Divorce cases in West Java Province have increased every year. The profile map of divorce cases that occurred in each region is not yet known, so efforts to provide guidance to minimize divorce cases are not optimal. Divorce case data is also not equipped with a visualization feature that makes it easier for authorized officials to easily understand and analyze data. This study analyzes divorce cases in regencies/cities in West Java Province, using the K-Means Algorithm Clustering data mining method. The clustering method is grouping data based on the same characteristics. In determining the number of clusters, that is by using the value of the Davies Bouldin Index. The results of this study obtained the best cluster of grouping divorce cases, there were 2 clusters, namely cluster 0, there were 5 regencies and 9 cities, while in cluster 1 there were 13 regencies, with a Davies Bouldin index value of 0.168 and an avg.within centroid distance value of 5,870. Cluster 0 is the city/district with the lowest divorce cases and cluster 1 is the city/district with the highest divorce cases.

Indonesia and Malaysia are two countries that have historically disputed with each other. One of the disputes between Indonesia and Malaysia is the Ambalat Block boundary dispute. The Ambalat Block is a sea area of ​​15,235 square kilometers which is in the Sulawesi Sea or the Makassar Strait. The Ambalat Block is estimated to contain oil and gas that can be utilized for decades to come. Ambalat, is near the border line of Indonesia and Malaysia. In this area as a fishing area in Sebatik waters. This water area is recorded to be rich with potential for reef and demersal fish. Ambalat is not only rich in fish potential. This area, which is located in North Kalimantan, has long been a dispute between Indonesia and Malaysia. One of them, because it has the potential of oil and natural gas. Geological Survey Center - Geological Agency of the Ministry of Energy and Mineral Resources (ESDM) has identified this potential. Based on G&G study data around the East Ambalat area, this potential is in the Tarakan basin and its surroundings. The naming of the marine block contained in the Ambalat block is based on the interests of exploring marine and underwater wealth, especially in the oil mining sector. Tensions between Indonesia and Malaysia are increasing due to the ownership claims of each country over the Ambalat block area, the Ambalat block area which is now a dispute between the States of Indonesia-Malaysia is not a land area but is located at a sea depth of 2500 meters on the continental shelf geographically, block Ambalat is a natural continuation of the Indonesian Kalimantan mainland which is in the Tarakan Basin spreading area which has the potential as oil and gas.

Lot of problems arise in selecting scholarship recipients in a large number of submissions, the existence of several searches used, and the selection of files for scholarship applicants is still manual, so a system is needed that can speed up, help, and make it easier in the decision-making process to lighten work. student section. In supporting decisions this system will use the Naïve Bayes Classifier Method to determine what is acceptable and not acceptable. The NBC method can analyze and make improvements to old data, and the resulting data will provide simpler probability values that can later be used to make decisions. From the results of the research that has been carried out, it can be realized that the application of the data mining algorithm using the Naïve Bayes Classifier can be carried out to select scholarship recipients at Stikubank University Semarang. The result of the selection of Unisbank Semarang scholarship recipients is the accuracy value. 72% of the 135 data which is divided into 100 training data and 35 test data.

This data mining association processes 1224 Gamefantasia ticket redemption transaction data. The goal is to find a pattern of association between goods as a recommendation for structuring the display of goods at the cashier counter and increasing ticket exchange transactions. Modeling uses a comparison of two algorithms, namely the Apriori algorithm and FP-Growth. The data analysis method with the CRISMP-DM method is then processed by RStudio software. The results of the study with the same parameters support 0.02 and confidence 0.1 FP-Growth algorithm formed 53 rules, the strength of the association rule 6.2%, the accuracy was1245%. Whereas the Apriori algorithm forms only 12 rules, the strength of the association rules is 2.1% and the accuracy is 7.8%. Thus, it can be concluded that the use of the FP-Growth algorithm has better results than the Apriori algorithm because it has the highest accuracy in finding transaction patterns.

Pengelolaan data bisnis merupakan hal yang sangat penting bagi perusahaan, khususnya dalam era digital yang semakin berkembang. Dalam mengelola data bisnis, teknologi database menjadi salah satu pilihan yang paling efektif. Teknologi database memungkinkan perusahaan untuk menyimpan, mengelola, dan memproses data secara terstruktur dan efisien. Artikel jurnal ini bertujuan untuk menjelaskan konsep dasar tentang teknologi database, manfaat yang didapat dari penggunaan teknologi database dalam pengelolaan data bisnis, serta tantangan dan solusi yang terkait dengan penggunaan teknologi database.Pengelolaan data bisnis menjadi aspek yang sangat penting dalam operasi perusahaan modern. Dalam era digital ini, teknologi database telah menjadi landasan utama dalam menyimpan, mengelola, dan memanipulasi data bisnis. Jurnal ini bertujuan untuk menyajikan tinjauan tentang penerapan teknologi database dalam pengelolaan data bisnis.Pertama, jurnal ini akan membahas tentang konsep dasar teknologi database, termasuk jenis-jenis database, seperti database relasional, database berorientasi objek, dan database NoSQL. Penjelasan tentang struktur dan fungsionalitas masing-masing jenis database akan disajikan untuk memberikan pemahaman yang komprehensif.Selanjutnya, jurnal ini akan menggambarkan manfaat penerapan teknologi database dalam pengelolaan data bisnis. Dengan menggunakan teknologi database, perusahaan dapat menyimpan dan mengelola data bisnis mereka dengan lebih efisien, memfasilitasi akses cepat dan mudah terhadap informasi yang relevan, serta meningkatkan integritas dan keamanan data.Selain itu, jurnal ini akan membahas berbagai fitur dan kemampuan teknologi database yang mendukung pengelolaan data bisnis, seperti pemrosesan transaksi, analisis data, penggalian data (data mining), dan integrasi dengan aplikasi bisnis lainnya.Selanjutnya, akan dipaparkan beberapa contoh nyata tentang penerapan teknologi database dalam pengelolaan data bisnis. Contoh-contoh ini akan melibatkan implementasi sistem manajemen basis data (Database Management System/DBMS) khusus, serta penggunaan bahasa SQL (Structured Query Language) untuk mengambil dan memanipulasi data bisnis.Selanjutnya, jurnal ini akan membahas tantangan dan tantangan yang mungkin muncul dalam penerapan teknologi database dalam pengelolaan data bisnis, seperti keamanan data, skalabilitas, dan konsistensi data. Solusi dan strategi untuk mengatasi tantangan ini juga akan dibahas.Terakhir, jurnal ini akan memberikan kesimpulan dan memberikan pandangan ke depan tentang peran teknologi database dalam pengelolaan data bisnis. Diharapkan bahwa jurnal ini akan memberikan wawasan yang berguna bagi para profesional, peneliti, dan praktisi yang tertarik dalam menerapkan teknologi database dalam konteks pengelolaan data bisnis.

Pengelolaan data bisnis merupakan hal yang sangat penting bagi perusahaan, khususnya dalam era digital yang semakin berkembang. Dalam mengelola data bisnis, teknologi database menjadi salah satu pilihan yang paling efektif. Teknologi database memungkinkan perusahaan untuk menyimpan, mengelola, dan memproses data secara terstruktur dan efisien. Artikel jurnal ini bertujuan untuk menjelaskan konsep dasar tentang teknologi database, manfaat yang didapat dari penggunaan teknologi database dalam pengelolaan data bisnis, serta tantangan dan solusi yang terkait dengan penggunaan teknologi database.Pengelolaan data bisnis menjadi aspek yang sangat penting dalam operasi perusahaan modern. Dalam era digital ini, teknologi database telah menjadi landasan utama dalam menyimpan, mengelola, dan memanipulasi data bisnis. Jurnal ini bertujuan untuk menyajikan tinjauan tentang penerapan teknologi database dalam pengelolaan data bisnis.Pertama, jurnal ini akan membahas tentang konsep dasar teknologi database, termasuk jenis-jenis database, seperti database relasional, database berorientasi objek, dan database NoSQL. Penjelasan tentang struktur dan fungsionalitas masing-masing jenis database akan disajikan untuk memberikan pemahaman yang komprehensif.Selanjutnya, jurnal ini akan menggambarkan manfaat penerapan teknologi database dalam pengelolaan data bisnis. Dengan menggunakan teknologi database, perusahaan dapat menyimpan dan mengelola data bisnis mereka dengan lebih efisien, memfasilitasi akses cepat dan mudah terhadap informasi yang relevan, serta meningkatkan integritas dan keamanan data.Selain itu, jurnal ini akan membahas berbagai fitur dan kemampuan teknologi database yang mendukung pengelolaan data bisnis, seperti pemrosesan transaksi, analisis data, penggalian data (data mining), dan integrasi dengan aplikasi bisnis lainnya.Selanjutnya, akan dipaparkan beberapa contoh nyata tentang penerapan teknologi database dalam pengelolaan data bisnis. Contoh-contoh ini akan melibatkan implementasi sistem manajemen basis data (Database Management System/DBMS) khusus, serta penggunaan bahasa SQL (Structured Query Language) untuk mengambil dan memanipulasi data bisnis.Selanjutnya, jurnal ini akan membahas tantangan dan tantangan yang mungkin muncul dalam penerapan teknologi database dalam pengelolaan data bisnis, seperti keamanan data, skalabilitas, dan konsistensi data. Solusi dan strategi untuk mengatasi tantangan ini juga akan dibahas.Terakhir, jurnal ini akan memberikan kesimpulan dan memberikan pandangan ke depan tentang peran teknologi database dalam pengelolaan data bisnis. Diharapkan bahwa jurnal ini akan memberikan wawasan yang berguna bagi para profesional, peneliti, dan praktisi yang tertarik dalam menerapkan teknologi database dalam konteks pengelolaan data bisnis.

The purpose of conducting this research is to analyze and find out how the influence of return on assets and earnings per share has on mining sector stock prices listed on the Jakarta Islamic Index for the period 2016 – 2021. This research uses quantitative methods and panel data regression analysis methods. The samples used were 7 companies with a total of 6 years of data, namely 42 data, using a purposive sampling technique. The results showed that the variable return on assets partially has a significant effect on stock prices, while the earnings per share variable partially has no significant effect on stock prices. Simultaneously, the variables return on assets and earnings per share have a significant influence on the mining sector stock prices listed on the Jakarta Islamic Index for the period 2016–2021 with a coefficient of determination for this model of 93.61%.

This research is motivated by the progress of science, especially in the field of technology which is very fast, along with competition in the industrial sector which is getting tougher where companies have used sophisticated and modern equipment in carrying out their production activities. The research was conducted to examine the Effect of Green Accounting on Economic Performance. The quantitative approach method used uses data processing simple linear regression analysis. Return On Assets (ROA) is used to measure research variables. The sample companies for this research are 7 companies in the mining industry sector and the chemical industry sector which are listed on the IDX for the 2017-2021 period. The results of the study show that the Green Accounting variable has no positive effect on Economic Performance, as tested through the T-Test.

Numerous businesses are capable of implementing a wide range of tax planning techniques. Tax avoidance, or legally lowering taxes, is one tax planning tactic. Tax avoidance strategies typically use loopholes in the tax code without breaking any of them. In addition, they use tax law gaps to perpetrate tax evasion. While this tax evasion tactic is legal, the corporation using it is still receiving funding from the state. In 2013, 832 foreign investment companies were suspected of engaging in tax fraud in Indonesia due to their five consecutive years of loss reporting and nonpayment of taxes. This study aims to investigate and evaluate the effects of capital intensity, profitability, leverage, and majority share ownership on tax evasion. The Current Effective Tax Ratio is used in this study to generate tax avoidance. Mining businesses that are listed on the Indonesia Stock Exchange for the period of 2017–2021 make up the population and sample for this study. With 37 observational data points, 7 mining companies make up the research sample. A multiple linear regression model is the research methodology employed in this study. Version 22 of the IBM Statistical Package for Social Science was used to process the data for this study. The study's findings demonstrate that tax evasion is not much impacted by profitability or leverage. Conversely, capital intensity and majority share ownership have a detrimental impact on tax evasion.    

Indonesia is one of the world's largest coal exporters. One of the means of sea transportation to transport coal is tugboats and barges. PT. Patria Maritime Lines is a shipping company that focuses its services on the transportation of coal and other energy from mining concessions and various commodities. PT. Barito Samudra Sejahtera is a company that provides ship agency services which currently supports the ship operations of PT. Patria Maritime Lines. The duty of the shipping company, PT. Barito Samudera Sejahtera, namely taking care of Clearance In and Clearance Out documents for tugboats and barges that will dock at the Unloading Port and unload or load goods. This study aims to determine the procedures and supporting documents required for Clearance In and Clearance Out. This study uses observation, interviews, documentation, and literature study as qualitative methods. It was found in this research that As an agent, PT. Barito Samudra Sejahtera must know the Clearance In and Clearance Out procedures and what documents can be returned, especially those on the ship or tugboats and accompanying barges.

Keerom Regency is one of the areas that has the potential for Batugamping mineral resources which is quite potential, this is evidenced by the existence of several mining business actors who are carrying out mining activities in the area. Based on the geological map of the Jayapura sheet (Taritatu Sheet) the distribution of limestone potential is quite evenly distributed in the Keerom Regency area. The distribution of limestone potential in Keerom Regency is spread in the Arso 1, Arso 4, Arso 10, Arso 13 areas to Senggi. Based on the results of the initial survey, mining activities in Keerom Regency have not been managed properly, because some mining sites have carried out mining activities but do not yet have legality, namely a mining permit (SIP), do not have a good and correct mine processing plan based on the mining stages, there are still locations where limestone is not yet known distribution, volume and even the amount of resources and reserves. The potential for limestone is a good investment opportunity if it is developed into a community mine that can provide added value to the community. Therefore, it is necessary to have geological mapping activities and also the calculation of resource values. In this case, it concerns the quantity and quality of deposits to be able to provide information as a mineral database for the community as land owners and is also very useful for the Keerom Regency government. This research aims to determine the amount of limestone volume which can later be used as data base information during mining activities. The research also utilized the Surfer 11 application for the creation of topographic maps and to calculate the number of limestone volumes. The research method that will be carried out is the Cross Section Method which is a special Method for types of rock minerals        

Malnutrition has always been a global problem and is the main cause of child mortality in developing countries. Nutritional status is a measure of success in meeting the nutritional needs of toddlers which can be seen from the achievement of toddler's weight. The short-term effects of malnutrition on toddlers are physical growth disorders in children, metabolic disorders, brain development disorders, and intelligence disorders. In the long term, malnutrition will cause a decrease in learning outcomes and cognitive abilities, decreased immunity, the risk of developing diabetes, heart and blood vessel disease, obesity, stroke, cancer, and disability in old age. To find out about the growth and development of early childhood, especially in relation to the development of early childhood nutritional values, regular measurements of the height and weight of toddlers from an early age are carried out through Posyandu activities. Toddler height and weight data will be grouped according to the nutritional characteristics of each toddler. In this study, infants will be clustered based on their nutritional characteristics using the K-Means algorithm clustering method. Based on the evaluation results, the number of clusters 3 is more optimal than the number of clusters 5 in the toddler dataset used in the study. It is hoped that the research results obtained can serve as a basis or recommendation material for posyandu throughout Indonesia to determine the nutritional status of the under-five age group, so that the handling is more appropriate and can help prevent malnutrition in under-fives.