Publication Search

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  

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%.

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.

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.

The goal of this data mining C4.5 implementation is to improve student performance in academic coursework in the computer science department at Teknik Fakultas and Pancasakti University in Tegal. Use a limited number of dimensions to assess the following: nyata, jaminan, keandalan, empatia, dan bukti nyata. It is difficult to determine which quality standard has to be raised because the aforementioned kelima aspek cannot be changed in an objective manner. Utilizing the algorithm C4.5 method, the authors consider reducing the sample size to the point where the keputusan is reduced. After manual perhitungan, pembuktian is also carried out using an application called RapidMiner.The analysis's conclusions show that the most important factor in determining the mahasiswa's tingkat kepuasan is the style of teaching.

The profitability of a company is used to evaluate or measure whether profits have increased in relation to the seller's total assets and equity capital, whether the company makes a profit, and the profits earned. Company profits are used for the welfare of the company itself. Apart from that, profit also plays an important role in determining the success of a business and as a tool for managerial decision-making. The three objectives of this research are: the effect of asset growth on company profitability; the effect of capital structure on company profitability; and the effect of liquidity on company profitability; In this study, 87 companies registered in oil, gas and geothermal mining were listed on the Indonesia Stock Exchange from 2018 to 2022. Samples taken according to the criteria were collected using a purposive sampling technique. The samples collected included 42 companies, and a total of 210 data were processed. This research analysis uses multiple linear regression analysis, along with descriptive statistical tests, classical assumption tests, and hypothesis tests. The analytical tool used is SPSS version 25. The research results show that only one factor influences the company's profitability, namely asset growth. Capital structure and liquidity, on the other hand, do not affect a company's profitability. Asset growth has a positive impact, while capital structure and liquidity have a negative impact.

The purpose of this study is to determine the influence of independent boards of directors and commissioners on the disclosure of sustainability reports on mining companies listed on the Indonesia Stock Exchange (IDX). The research time period used is 4 years, namely the 2018-2021 period. The population in this study includes all mining companies listed on the Indonesia  Stock  Exchange  (IDX)  for  the  2018-2021  period.  The  sampling technique uses purposive sampling techniques. Based on the criteria that have been set in the acquisition of 10 companies. The type of data used is secondary data obtained from  www.idx.co.id site, the analysis method used is panel data regression analysis. The results of this study show that the board of directors has an effect on the disclosure of the sustainability report, then the independent commissioner has an effect  on  the disclosure  of  the sustainability  report.    

The purpose of this study was to determine the effect of Corporate Social Responsibility, Intellectual Capital Disclosure, and Business Risk on Firm Value variable in mining sector manufacturing companies listed on the Indonesia Stock Exchange (IDX). The research time period used is 5 years, namely 2017-2021. The population in this study includes mining sector manufacturing companies listed on the Indonesia Stock Exchange for the period 2017-2021 with a sampling technique that uses purposive sampling. The type of data used is secondary data obtained from the official website of the IDX and the company. The data analysis technique used is panel data regression. The results of the study stated that Corporate Social Responsibility and Intellectual Capital Disclosure had an effect on firm value.    

The purpose of this study was to determine the effect of intellectual capital, inventory turnover and profitability on financial distress in mining sector companies listed on the Indonesia Stock Exchange (IDX). The research time period used is 5 years, namely the period 2017 - 2021. The population of this study includes all mining sector companies listed on the Indonesia Stock Exchange (IDX) for the period 2017 - 2021. The sampling technique in the study used purposive sampling technique. Based on the predetermined criteria, 13 companies were obtained. The type of data used is secondary data obtained from the Indonesia Stock Exchange website. The analysis method used is panel data logistic regression analysis. The results showed that intellectual capital and inventory turnover had no effect on financial distress. While profitability has a significant negative effect on financial distress, and intellectual capital, inventory turnover and profitability jointly affect financial distress.  

The purpose of this study is to determine the effect of company size and sales growth on corporate social responsibility in mining companies listed on the Indonesia Stock Exchange. The research time period used is 5 years, namely the 2017-2020 period. The population of this study includes all mining companies listed on the Indonesia Stock Exchange (IDX) for the 2017-2020 period. The sampling technique used purposive sampling technique. Based on the predetermined criteria obtained 9 companies. The type of data used is secondary data obtained from the Indonesia Stock Exchange website. The analytical method used is multiple linear regression supported by the SPSS 25 program. The results show that company size have effect on corporate social responsibility and sales growth have no effect on corporate social responsibility.   Keywords: company size, sales growth, corporate social responsibility  

This study aims to determine the best selling food and beverage products at Caffe Kopi Kito. Data mining is the process of extracting useful information and patterns from very large data. Data mining includes data collection, data extraction, data analysis, and data statistics. The Apriori algorithm is a classic algorithm in data mining. This algorithm is used to see the intensity of occurrence of the relevant itemset or frequent items or association rules. This study uses consumer transaction data for 30 days in January 2023. Transaction data will be collected first based on the day and number of transactions, then the transaction data that has been collected will be grouped according to each item, the data that has been grouped will be carried out a priori algorithm process to determine the most dominant product. Then a system design will be carried out whose result will be a website. The results showed that using the website-based a priori algorithm could determine the most dominant product at Caffe Kopi Kito and make it easier for users to determine the most dominant product. Based on the results of product sales analysis at Cafee Kopi Kito, it can be concluded that working on the a priori algorithm on Caffe Kopi Kito using a website can be said to have the result of a product combination and in the future it can be used to create the best-selling menu packages at Cafee Kopi Kito.

The PTUN’s decision are often not obeyed and implemented by state administrative officer. When the decision of PTUN doesn’t have executorial effect, judicial control which is owned by the PTUN as a form of implementing good governance in Indonesian state administration will be unclear. One of the problem occurs in the realm of mining business license. Government as the publisher of mining business license is often reluctant to comply with PTUN decisions to revoke decree on business license that violate the law. The purpose of this study is to determine the compliance level of the Minister of Energy and Mineral Resources and PT. Tambang Mas Sangihe (PT. TMS) to PTUN decision. The method of this study uses a normative juridical research model. While the data collection technique of this study uses library method. The results of this study shows that the  disputed object “Decree of Minister of Energy and Mineral Resources Number: 163.K/MB.04/DJB/2021” is considered that have violated the law and general principle of good governance. As consequence, in PTTUN Jakarta's decision, the Minister was ordered to revoke the decree of mining permit for PT. TMS. However, the decision was not implemented by the Minister and PT. TMS.   Keywords : Administrative court, Administrative court decision, executive power.