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The family is the first and main environment for a child to receive education, guidance and instill different values ​​and norms and develop various behaviors that are important for personal life, family and the environment. Parental division will lead to arguments and anger so that these emotions will tend to dominate the child's emotions. Based on the explanation above, researchers are interested in studying the impact of parental divorce on children's character. This research seeks to reveal how character formation influences children's psychology from the impact of parental divorce. In this research, descriptive qualitative methods were used. because to explore a particular case by conducting data mining to understand the case in detail (Tobing, H. et al., 2016). Researchers try to understand events or phenomena regarding the impact of parental divorce on the formation of children's character. According to Moh. Nazir (1988).

Technological developments from time to time continue to develop in a more sophisticated direction. Ease of accessing the internet and inclusive digital solutions are one of the drivers of accelerating digital transformation among society. Digital solutions in the form of applications have become one of the primary tools needed in the world of work and business. One example of the latest information system developments is in the world of mining in terms of workforce management. One of the companies that requires a workforce management information system is PT Lestari Berkat Sejahtera, because this company still uses a manual workforce management system. The author has a solution, namely by creating an employee data management application. The aim of making this application is to provide easy access for HRD staff, admins and employees to view information and manage existing human resource data.

Coal in Jambi is a problem that people continually complain about and causes traffic jams and damaged roads. Until the end of 2022, there are 51 coal mining companies operating in Jambi Province, spread across Sarolangun, Tebo, Batanghari and Muaro Jambi. The Jambi provincial government is preparing alternative coal transportation routes via land and water. This research uses quantitative research with a descriptive format, aimed at explaining, summarizing various conditions, various situations or various variables that arise in the community which is the object of the research based on what happens. Then bring to the surface the character or description of the condition, situation or variable. The results of observations from questionnaires that have been distributed by students hope that this alternative will reduce the level of traffic jams and the number of accidents that occur in the community. The Governor of Jambi, Al Haris, has made various efforts in alternative development in his province. Students hope that this alternative will reduce the level of traffic jams and accidents that occur in society. The Governor of Jambi, Al Haris, has made various efforts in alternative development in his province. One of them is controlling the use of coal transport vehicle plates to repair roads. Apart from that, the provincial government is also discussing the issue of coal transport and the construction of special roads for coal transport. The Governor also admits that his authority is limited in matters of coal transport, but various efforts have been made. carried out, including opening alternative roads and giving lambuk numbers to coal transport. Apart from that, Governor Al Haris also stated the ban on coal transport via national roads and the importance of the progress of Jambi City as a barometer for the development of Jambi province. However, despite this, we can also feel that currently the accident rate is still there.

 This article discusses the dynamics of the development of mining management policies in Indonesia. Where mining activities in Indonesia itself have been going on for a long time. The study of this article shows mining regulatory policies in Indonesia to date, which have experienced many ups and downs in several regions of Indonesia. Starting from the licensing system, utilization of natural resources, policies towards mine workers and several other things, both national and international companies. The various dynamics of these developments show that mineral and coal mining is always seen as a strategic commodity economic center so it is worth fighting over, especially Indonesia which has a lot of natural resources whether it was once by domestic or foreign entrepreneurs and even recently by the central and regional governments, and the law was then held to support these goals.

The aim of this research is to apply an a priori algorithm to determine vegetable purchasing patterns and analyze the results in order to control vegetable stocks at Sawargaloka Hydroponic Hydrofarm. The need for quality and safe food supplies is increasing along with population growth, where plants are grown without using land, but using nutrient solutions that are rich in important substances, the application of data mining using the Apriori method can provide valuable insight into the purchasing patterns of hydroponic vegetables by customers. By understanding these patterns, companies can improve marketing strategies, plan production more efficiently, and provide product recommendations to customers. The results of analytical research using the Apriori method on hydroponic vegetable purchase data at Sawargaloka Hydrofarm, it can be concluded that the application of data mining has great potential in identifying significant purchasing patternsa

Residential is a place to live or everything related to a place to live and in a narrow sense can be interpreted as a residential area or residential building. In connection with the quality of residential facilities, employee satisfaction is an important aspect in improving the quality of the provided residential facilities. If the satisfaction of the residential facilities provided to employees is not met, the employees will feel uncomfortable and will sue the plantation of PTPN IV Marjandi Unit. Analyze the level of employee satisfaction with the quality of the residential provided by the plantation to its employees is The purpose of this study. One of the efforts to find out the satisfaction of employees of residential facilities is to use the C4.5 algorithm classification, where Dataset is obtained through the Questionnaire technique that will be given to employees at PTPN IV Marjandi Unit. As for the satisfaction of employees of residential facilities in terms of aspects (1) water facilities, (2) electricity facilities, (3) kitchen conditions, (4) bedroom conditions, (5) toilet conditions in dwellings inhabited by PTPN IV Unit plantation employees Marjandi. Data processing is assisted using Microsoft Excel software and to validate study data using a rapidminer tool. It is hoped that this research can provide solutions or become a reference for plantations to improve the quality of residential facilities provided to PTPN IV Marjandi Unit employees..

PT. Putra Elan Balindo is a company engaged in the mining sector specially the andesite minerals domiciled in Palu City. PT. Putra Elan Balindo located in Watusampu Village, Ulujadi District, Palu City, Central Sulawesi, which has an IUP (Mining Business Permit) with an area of 17.89 Ha. To achieve production targets set by the company using a combination of tools mechanics in the form of Excavator Komatsu PC 400 and Dump Truck Hino FM 260 JD, where there is currently only 1 Excavator while the Dump Truck is 2 are needed with a production target of 20,000 m3 per month and have 1 shift working hours. Based on the results of research carried out for one month, it shows that the productivity of the Komatsu PC 400 Excavator is 174.29 m3 / hour and the Hino FM 260 JD Dump Truck is 197.69 m3 / hour for 2 transport equipment. The cost of owning a Hino FM 260 JD Dump Truck is Rp. 476,190/hour and the cost of owning a Komatsu PC 400 Excavator is Rp. 267,857/hour while operational costs for the Hino FM 260 JD Dump Truck are Rp. 1,862,072/ hour and operational costs for a Komatsu PC 400 Excavator Rp. 2,135,421/hour.

This paper aims to explore the impact of the implementation of green accounting and environmental performance on the financial performance of companies, with a specific focus on the mining and manufacturing sectors in Indonesia. The study delves into the challenges of environmental pollution and the necessity for companies to enhance profitability while improving financial performance. The research assesses the relationship between green accounting, environmental performance, and financial outcomes, aiming to provide insights into whether companies applying green accounting can enhance profitability through good environmental performance.

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.

PT Agincourt Resources is a mining company based in Indonesia engaged in the exploration, mining and processing of gold and silver bar minerals. The company PT Agincourt Resources received rejections from the community so that the demonstration occurred due to the disposal of waste which would be directed to the Batangtoru River and other issue that could cause a decline in the company’s image. So that from this incident the Community Relations departement formed a Socializations and Communication Program as a bridge and forum for the community so that misunderstandings in communications and cons from the public against the company do not occur. The aim of the Socialization and Communications Program is to provide positive informations to the community related to mining through socialization activies which explain that the waste dischargerd into the Batangtoru River is not waste but residual water from the processing process.

This research explores the use of Text Mining Methods as an innovative approach to extract important information from research report text. With a strong conceptual foundation from the literature review, this research details the key concepts of Text Mining, such as tokenization techniques, sentiment analysis, and entity extraction. The steps of applying Text Mining Methods to research reports are explained in depth, with a focus on using such techniques to improve the efficiency and accuracy of information extraction. Through the evaluation of the method's performance, the research demonstrates a significant improvement in analysis speed and information extraction accuracy compared to conventional methods. The research conclusions provide a holistic picture of the potential of Text Mining Methods in improving the effectiveness of the research report text analysis process. The implications of this research stimulate thoughts on the applicability of this technology in various disciplines that rely on research reports as a primary source of information. Thus, this research makes a positive contribution to the understanding and development of text analysis techniques to support more efficient decision making.

ABSTRACT This research delves into theipinfluenceipof profitability, ipcompanyipsize, ipand iptax rates on the capitalipstructure of mining sectoripcompanies listedipon the Indonesian Stock Exchange between 2019 and 2022. The sample selection involved the purposive sampling method, yielding 112 samples for analysis. Theipfindingsiprevealithat profitability and firmisize significantly affectitheicapital structure,iwhile tax rates do not exhibit a significant impact. Data collection was performed quantitatively, and multipleislinearisregression analysis was employed for data processing. The financial reports used for analysis were obtained from theiIndonesiaiStockiExchange via the idx.co.id website and processed using SPSS  

Based on data from the West Sumatra energy and mineral resources service, it is stated that Limapuluh Kota Regency has the potential for rocks (andesite, granite, limestone, marble) and metallic minerals (gold and lead). This huge natural potential requires good management so that it can develop and requires potential human resources as well. This is the background for socializing opportunities and potential job opportunities in Limapuluh Kota Regency. The socialization explains what potential mining resources exist in Limapuluh Kota Regency along with the job opportunities that exist in managing these resources. The target of this socialization is to open the minds of high school students in terms of the natural potential that their region has and to open up the students' insight in choosing the science they will study in college, so that as sons/daughters of the region they can contribute to the management and development of their region.

Data mining is a technique to extract new information from the data warehouse, information is considered very important and valuable because by mastering the information so easily to achieve a goal, this makes everyone competing to obtain information, as well as on trading businesses such as bag store BRANDED. store is located close to the home of the population, this certainly affects the level of sales, with the daily sales activities, sales transaction data will continue to grow, causing data storage is greater. Sales transaction data is only used as an archive without being put to good use. Basically the data set has very useful information. The analysis of market basket with Apriori Algorithm is one method of data mining which aims to find the pattern of association based on consumer spending pattern, so that it can be known what items are purchased simultaneously. The result of this research found that the highest support and confidence value is Ysl and Chanel with a support value of 50% and confidence of 75%.

WiFi networks are very crucial in today's corporate industry. Because the WiFi network contains the internet which acts as a data transfer and communication route to support the company's operations. PT. Bukit Baiduri Energi (PT. BBE) as a company operating in the coal mining sector relies heavily on the internet to carry out company operations. Every day there is always an exchange of data and communication from employees to monitor the process of carrying out existing tasks and work, in responding to problems faced during the internship at PT. Bukit Baiduri Energi, our team takes the right steps to find the optimal solution. The first step taken was to identify the company's needs and formulate the idea of ​​creating a web company profile as a Mikrotik Hotspot captive portal. The website development process involves utilizing HTML, CSS, and JavaScript to create an attractive appearance and ensure functionality. The results of the project during the internship were to create a web company profile as a captive portal for PT Mikrotik Hotspot. Bukit Baiduri Energy. During the internship period at PT BBE, our team succeeded in completing the captive login hotspot project on Mikrotik devices by changing the design of the hotspot login portal and adding a brief company profile page. This project provides important benefits for companies in improving the security of their Wi-Fi networks and introducing the company to users through profile pages. The result is a positive step in supporting the growth and image of companies in the coal mining sector.

Mushrooms are very diverse with characteristics of each type, there are 1,433,800 types of mushrooms that have not been recognized. In this study, researchers used the Neural Network and Deep Learning Inception V3 methods as a feature extraction process in images to classify mushroom images based on genus with the Orange Data Mining application. There are 9 genera of mushrooms used in this study, namely Agaricus, Amanita, Boletus, Cortinarius, Entoloma, Hygrocybe, Lactarius, Russula, and Suillus. The total dataset used is 2,700, with 300 images for each genus. The test uses the cross-validation method which is applied to the confusion matrix to get precision, recall, F1-score, and accuracy values. In this study, the final classification results were obtained with an accuracy of 82.5% and the genus Boletus mushroom obtained the best results with an accuracy of 98.9%.

The use of the Decision Tree method in smartphone price classification is the focus of this study. By using the 10 most relevant features and data normalization to achieve scale consistency, the Decision Tree algorithm delivers an average accuracy of 81%. Although some false positives and false negatives occur, the model is able to classify smartphone prices well, especially in identifying low and high prices. These results provide important insights into the features that affect smartphone prices. While there is still room for improvement, this model provides a solid foundation for the smartphone industry to determine prices based on certain specifications. The importance of relevant feature selection and data normalization was revealed in this study. Despite the accuracy reaching 81%, improvements in the classification of medium and high price classes are still possible to reduce prediction errors. This method provides an important basis for the smartphone industry to set prices based on specifications, and data mining techniques such as Decision Tree can be improved to improve the accuracy of future price predictions.

Scholarships are a form of assistance in the form of educational expenses provided by the government or foundations to students or students who are categorized as from underprivileged families. However, in datermining scholarship recipients, there are still many scholarship recipients who come from wealthy families, while those from less fortunate families do not receive this assistance. This may be due to calculations and data processing that still use manual methods, causing scholarship recipients to not be on target. The purpose of this research is to simplify and minimize calculation errors in determining scholarship recipients for the Smart Indonesia Program (PIP) at SMK Karya Medika. Therefore, for calculating and processing PIP scholarship recipients data, data mining techniques can use the calssification method using the K-NN algprithm. K-Nearest Neighbor is a data classification method that will be used for data objects based on learning data that is closer to the object. In this study using the Confusion Matrix test so as to obtain an accuracy value of 80.00%.     

Di era digital saat ini, kemajuan teknologi informasi mengalami pertumbuhan yang pesat. Salah satu perkembangan yang signifikan terjadi dalam bidang kecerdasan buatan (Artificial Intelligence), yang telah diterapkan luas di berbagai sektor, termasuk analisis data dan pengambilan keputusan. Para peneliti di bidang data mining telah menciptakan beragam algoritma klasifikasi yang meningkatkan proses klasifikasi dengan memanfaatkan atribut numerik dan nominal. Klasifikasi adalah suatu proses analisis data yang menghasilkan model untuk mewakili kelas-kelas dalam data tersebut, seperti yang terjadi pada Decision Tree yang digunakan untuk menganalisis klasifikasi dan pola prediksi data serta menggambarkan hubungan antara variabel atribut  dan variabel target  dalam bentuk struktur pohon. Python, sebagai bahasa pemrograman populer dalam pengembangan kecerdasan buatan, menyediakan pustaka dan framework yang mendukung implementasi algoritma Decision Tree. Dengan menerapkan algoritma Decision Tree untuk klasifikasi data evaluasi mobil menggunakan Python, kita dapat memanfaatkan kekuatan AI untuk memberikan solusi efektif dan efisien dalam pengambilan keputusan terkait evaluasi mobil. Menggunakan dataset Evaluation Car dari UC Irvine Machine Learning Repository, hasil penelitian menunjukkan akurasi sebesar 81%. Confusion Matrix dan laporan klasifikasi menunjukkan performa model yang baik dalam melakukan prediksi.

The tax aggressiveness importance’s have been documented by prior researchers. However, prior investigators failed to see it from an agency’s perspective. Therefore, this study determines the effect of agency related variables (women in commissioner board, managerial ownership, and debt policy) on tax aggressiveness. The object of this research is Indonesia listed operating at mining sector. The sample of this research is fifteen companies during 2016 to 2018. secondary hand collected data is employed in this study. The data is analyzed using regression analysis. The result show that Women in commissioners board has significant influence on tax aggressiveness. In addition, debt policy and managerial ownership had no relationship with tax aggressiveness. Out of three control variables, company size has a negative influence on tax aggressiveness at 10%. However, a company’s age and probability have no significant connection to tax agressiveness.