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Telecomunications plays in important role in everyday life, and signal crisis is a major challenge in many parts of Indonesia. This study aims to create a detailed map of areas effected by the signal and  internet traffic crisis using a Geographic Information System (GIS) based approach. The study includes data collection of communication signals and their determinations from various regions, providing a comprehensive picture of the network situation in Indonesia. A GIS analysis approach was used to create a map of the distribution of signal crisis areas, allowing the identification of spatial patterns that may be the root cause of this problem. The study focused on the geographical structure, signal interference and mobile internet data usage in each household as factors to consider when investigating the causal factors. The results show that there is a significant relationship between certain factors and crisis signaling. An in-depth understanding of the spatial data and causes of the signaling crisis is the basis for developing more effective improvement strategies. The practical implications of this study include recommendations for improved telecommunications infrastructure and better mitigation strategies. Therefore, this study not only presents the problem but also provides detailed insights to guide policies and measures needed to improve the quality of telecommunication services in Indonesia.

The use of deep learning models has become a major focus in optimizing the efficiency of machine learning applications. This research discusses various deep learning models that can be applied to improve efficiency in the context of machine learning applications. These models are designed to handle the complexity of machine learning tasks with a high level of accuracy while still considering aspects of computational efficiency. This article involves an in-depth look at several deep learning models that have proven effective in various application domains. Discussion includes the use of convolutional neural network (CNNs) models for image processing, recurrent neural networks (RNNs) for sequential data, and transformer-based models for natural language processing tasks. In addition, deep learning model tuning and optimization strategies, such as pruning and quantization, are also discussed to improve the efficient use of computing resources. This research identifies challenges and opportunities in integrating these deep learning models into machine learning applications with maximum efficiency. By considering the need for accuracy and limited computational resources, this research provides a holistic view of the approaches that can be applied to deal with complexity in diverse machine learning scenarios. The results are expected to provide a significant contribution to the development of efficient and effective machine learning applications.

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.

In this mini service project, the focus partner is a private university, namely Nurul Jadid University. The problem faced by partners is that the process of controlling the production equipment used at Nurul Jadid University is still manual, causing less than optimal efficiency and a fairly high error rate. The form of service that will be carried out is by implementing an Automatic Switch Control system using Internet of Things (IoT) technology at Nurul Jadid University. This system will replace manual processes with automation methods that can monitor the condition of production equipment and control it in real time. The proposed solution will involve installing sensors connected to an IoT (Internet Of Things) network on each production equipment. Data from these sensors will be sent to the control center which will control the Automatic Switch to regulate and monitor equipment performance in real-time.

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%.

Dalam mengatasi masalah rendahnya kesadaran masyarakat dalam pemeriksaan kesehatan gigi dan mulut, machine learning dapat menjadi solusi praktis untuk mengatasi masalah tersebut. Solusi yang dapat diberikan berupa aplikasi yang dapat mengklasifikasikan dan mendeteksi secara dini gambaran penyakit gigi dan mulut. Ada banyak jenis pendekatan yang dapat digunakan untuk melakukan klasifikasi dan deteksi, namun yang paling banyak diteliti dan diterapkan adalah metode convolutional neural network yang merupakan salah satu dari beberapa jenis metode dari algoritma deep learning. Komputasi tanpa server dapat dilakukan dalam lingkungan yang terisolasi, ini dapat digunakan untuk menguji beberapa hipotesis secara paralel yang menguntungkan bagi pengembang, tetapi tantangan tetap ada pada komputasi tanpa server seperti jangka waktu dan kapasitas memori yang perlu ditangani, tetapi untuk saat ini komputasi tanpa server tampaknya telah menjadi alternatif yang layak untuk model proses pelatihan.

The implementation of this community service involves this Partner Village located in Randutatah Village, Paiton District, Probolinggo Regency. This group has various businesses, processed seafood. Technology development in the digital era has brought significant changes in various aspects of life, including in business and marketing. E-commerce is one form of technology utilization that is growing rapidly, providing new opportunities for business actors, including farmers and fishermen in Randutatah Paiton Village. However, obstacles such as limited internet access, lack of e-commerce knowledge, low marketing networks, and intense competition on e-commerce platforms are the main challenges.To overcome these obstacles, a training program on e-commerce utilization was conducted.  This training program involves business owners and workers, with an implementation method that includes planning, implementing activities, and monitoring and evaluation. The purpose of the implementation of this community service is to apply e-commerce to the sale of various MSME products in Randutatah Village with the intention of introducing and increasing their sales turnover, while the method used is to use participatory methods, counseling, mentoring and training. The results obtained from the implementation of this community service are that with the help of training and e-commerce applications, it can reduce the sales turnover of MSME products in Randutatah Village.

Banjarwaru Village known as bamboo crafts village. Originally it was just a household product, it began to develop into a product that has aesthetic value. Sales of handicraft products are also starting to grow, they are starting to spread to other areas. Then the problem arises, namely inconsistent sales levels. To overcome this problem, the Cilacap State Polytechnic carried out Community Service activities by conducting Focus Group Discussion (FGD) activities by inviting resource persons from business actors to discuss with Banjarwaru village craftsmen. The aim of this activity is that Banjarwaru village craftsmen can find solutions to increase the level of sales of their craft products. From the results of the FGD, it was found that steps that can be taken to increase sales levels are carrying out business legality, building networks with the government, consumers, and fellow business actors, and increasing promotions through digital platforms.

Butterflies’ recognition serves a crucial role as an environmental indicator and a key factor in plant pollination. The automation of this recognition process, facilitated by Convolutional Neural Networks (CNNs), can expedite this task. Several pre-trained CNN models, such as VGG, ResNet, and Inception, have been widely used for this purpose. However, the scope of previous research has been somewhat constrained, focusing only on a maximum of 15 classes. This study proposes to modify the CNN InceptionV3 model and combine it with three data augmentations to recognize up to 100 butterfly species. To curb overfitting, this study employs a series of data augmentation techniques. In parallel, we refine the InceptionV3 model by reducing the number of layers and integrating four new layers. The test results demonstrate that our proposed model achieves an impressive accuracy of 99.43% for 15 classes with only 10 epochs, exceeding prior models by approximately 5%. When extended to 100 classes, the model maintains a high accuracy rate of 98.49% with 50 epochs. The proposed model surpasses the performance of standard pre-trained models, including VGG16, ResNet50, and InceptionV3, illustrating its potential for broader application.

This paper proposes a method based on the Lagrange optimization function and local search technique for minimizing the total cost of two power systems. The first system comprises ten multiple fuel thermal units (MFTUs) while the second system combines the first system with renewable energies, solar and wind power. The proposed method has advantages over its conventional method without a local search technique, called the conventional Lagrange function-based method (CLM), such as having the same parameters and exploiting other search spaces after getting convergence. The proposed method is more effective than CLM for the first system with the last case of load demand. In addition, the proposed method has better costs than previous algorithms, such as the Hierarchical numerical method (HNUM), Hopfield neural network, Adaptive Hopfield neural networks (AHNN) and modified Lagrange neural network (MLANN). Especially, the proposed method can find smaller costs than them, up to $6.78, corresponding to 1.4% for Case 1, and up to $2.43, corresponding to 0.4% for Case 4. Only the proposed method is tested on the second test system. The simulation results indicate that the method is very efficient for the problem with solar and wind energies and multiple fuel thermal units.

Terate village, which is located near the PTPN XII Kotta Blater plantation company, is facing serious problems related to poor internet networks and electricity supplies. The aim of this research is to study the dynamics of conflict, how retarded access impacts people's lives. The analysis is based on Ralf Dahrendorf's conflict theory to understand inequality of access. This study will look at what caused conflict during the construction of internet and electricity network infrastructure in Terate Village, with special emphasis on the role of the economic power of PTPN XII Kotta Blater in causing conflict. In addition, we will investigate how limited access affects education, economic growth and social life in Terate Village. This research will use approaches such as interviews and surveys with the community to gain a better understanding of the dynamics of conflict in Terate Village. In addition, this research is expected to provide insight into the complexity of conflict and also provide recommendations with the aim of improving equality of access and quality of life.

Empowerment has an important role in educational institutions which makes a real contribution to improving human resources. This includes empowering Islamic boarding school graduates in improving the quality of human resources. The aim of this service is to understand the process of empowering the Al-Qur'an Al-Asy'ariyyah Alumni Association (IKMAAL) in Kalibeber Village, Wonosobo Regency. The empowerment strategy includes four strategies, namely: preparation, work meetings, follow-up, and building togetherness. The results of this activity show that the working meeting of the Al-Qur'an Al-Asy'ariyyah Alumni Association (IKMAAL) in Kalibeber, Wonosobo district produced important points that show the alumni's gratitude towards the Islamic boarding school, namely: 1) making a coupon for land purchasers for development foundation, 2) creating an al-Al-asyariyyah coin program in each branch for the benefit of members, 3) planning a joint Umrah within the IKMAAL association, and in 2025 holding a Javanese and Madurese Qur'an hamatul. This contributes to increasing human resources for society within an institutional framework. The conclusion focuses on the importance of ties in realizing a goal and its implications for expanding the alumni network.

The development of technology forces humans to always innovate, including in terms of buying and selling. Nowadays, the proliferation of internet usage has implications for new buying and selling models. One form of buying and selling that was born due to the emergence of the internet network is online buying and selling.  Online buying and selling is a buying and selling activity where the seller and buyer do not have to meet to negotiate and transact and the communication used by the seller and buyer can be through communication tools such as chat, telephone, sms, Whatsapp and so on. Based on the background of the problems described above, the main problems can be identified including: How is the practice of buying and selling online with the Cash On Delivery (COD) system?, How is the fiqh muamalah review of the practice of buying and selling online with the Cash On Delivery (COD) system? The research method used in this writing is a legal research method, where normative/legal theory studies are legal studies by placing law as a construction of a system of laws and regulations and behavior. The preparation of this article uses a statutory approach, conceptual approach, and case or agreement approach. From the entire discussion of this thesis, the author can finally draw the following conclusions, In the implementation of buying and selling onilne COD (Cash On Delivery) system can be done with these steps; open the application or web from the online buying and selling platform you want, if you don't have an account then create an account first. Search for the item you want in the search field, then put the item in the shopping cart.

One of the businesses that is growing rapidly in Indonesia today is the multi-level marketing (MLM) business. MLM is a method of marketing goods or services from a system of selling goods directly through a marketing program in the form of more than one level, where business partners get sales commissions and sales bonuses from the sale of goods or services carried out by themselves and network members in their group. In general, this thesis discusses the multi-level marketing (MLM) business at PT.Melia Sehat Sejahtera in Jember district, with problems namely (1) how is the bonus system at PT.Melia Sehat Sejahtera in Jember district, (2) how is the review of Sharia Economic Law against the bonus system at PT. Melia Sehat Sejahtera in Jember district. This study uses a field research method with a descriptive approach which is useful for providing information, facts and data regarding the network bonus system at PT.Melia Sehat Sejahtera in Jember district. Then the data was analyzed using qualitative methods to uncover events, phenomena, facts and circumstances that actually occurred in the field. From this study it can be concluded that the bonus system at PT. Melia Sehat Sejahtera in Jember district has five types of bonuses, namely: sponsor bonuses, leadership bonuses, retail bonuses, retail group bonuses and unilevel bonuses. Meanwhile, according to Sharia Economic Law, the bonus system at PT. Melia Sehat Sejahtera in Jember district isThis can be done because it is in accordance with Islamic law.

This study aims to analyze and describe students' perspectives on E-learning and the difficulties faced by students during online learning. Researcher use qualitative methods. Data collection techniques used in this study were observation, interviews by distributing questionnaires. From the results of an analysis of students' perspectives on online learning during the Covid-19 period, it was found that students felt that online learning made them quite bored and reduced interaction between teachers and students. Online learning also makes students less understanding of the material provided, so that it has an impact on the level of student focus. The difficulties faced by students in e-learning-based online learning are network access that is not power full, internet quota and facilities such as mobile phones do not yet exist. Based on the explanation above, the researcher concluded that students' perspectives on e-learning can reduce student learning levels and the ability to understand learning.

Abstract.Network anomaly detection is a situation that occurs in network traffic that causes conditions to become abnormal. This research aims to analyze the performance of various machine learning algorithms in network anomaly detection and compare the performance of single classifier algorithms with ensemble learning. This ensemble learning technique has advantages such as increased accuracy and performance, can reduce the risk of overfitting and underfitting by using different subsets and features of data, and can turn weak learning into strong learning. However, on the other hand, this ensemble learning technique also has disadvantages in its use, namely that this ensemble method may not work well with high variance models, as the ensemble method may not be optimized for anomaly detection and that this method can be computationally expensive and time consuming due to the need to train and store multiple models. Some of the techniques used are deep learning, eager learning, lazy learning, bagging, feature selection, boosting, and stacking. In addition to this, this machine learning algorithm has weaknesses, including if any of the data used is incomplete, it will result in inaccurate completion data, making the programming process quite time-consuming. This research can help develop a more effective and efficient network anomaly detection system. The results of this research show that using ensemble learning and feature selection techniques can improve anomaly detection performance by reducing the processing time of redundant data and classification, as well as increasing precision values.    

This study aims to examine the Implementation of Punishment related to Contempt and Defamation in Law Number 19 of 2016 concerning ITE (Electronic Information and Transactions). The presence of this law was initially expected to be able to answer the challenges of the times by containing a criminal formulation of individual legal relations through social networks. However, Article 27 Paragraph (3) on Contempt and Defamation is actually a rubber article that is multi-interpreted and negatively affects free speech. It is studied using normative methods and focuses on the applicable law and connects it through legal concepts to analyze legal issues. From the results of the research that has been studied, it shows that the use of absolute offenses can make ITE cases increase and there must also be revisions in some articles of defamation tend to be used multi-interpretation with the subjective authority of law enforcement officials to promote freedom of expression in public.

Accounts receivable management is an important process in business activities, especially for large companies such as Telkom Indonesia. Telkom Indonesia as the dominant telecommunications company in Indonesia has a wide customer network, so the management of receivables becomes crucial in maintaining the Company's cash flow and financial health. The application of information technology, such as accounts receivable management systems and data analysis, plays a big role in the management of receivables. The system helps manage customer data, bill tracking, and provides valuable insights into payment trends and customer behavior. Accounts receivable management by Telkom Indonesia involves various strategies ranging from careful credit policies to modern technology and an effective billing approach. These efforts help companies minimize the risk of bad receivables, maintain cash flow, and maintain overall financial stability.

Various forms of juvenile delinquency carried out by students have recently become widespread. This reality really makes parents, teachers, community leaders and even the government feel angry. To overcome this problem, the government finally established a policy of strengthening the character of education for the entire community, including the education sector. Because of the importance of enforcing educational character in schools, the author conducted research aimed at examining the role of the educational ecosystem in implementing strengthening character education for students in schools. The method used in this research is a qualitative method by conducting interviews and surveys at schools based on the results of the analysis. The results obtained are that the implementation of character values ​​by school principals, in the form of socializing school policies regarding character education, provides an example in implementing character values ​​to students, and so on, teachers, in the form of: teachers as the center of school civilization, providing opportunities for opinions equally to students, assessing and reporting learning outcomes fairly and transparently, especially those related to instilling character values, forming students' personalities, and so on , staff/educational personnel in the form of: neat appearance. Speaking politely, and so on, parents/community in the form of mediators (building networks) with other institutions or communities in the action of instilling character values ​​in schools, actively participating in school adiwiyata, holding training in schools, holding training in schools by inviting students. experts, and so on. With synergy in strengthening the character of education in schools, a conducive atmosphere will directly be created in the school environment.

This research aims to determine the effectiveness and obstacles of implementing the SIMMONA application in financial management at the Finance Office of FITK UIN SUMATRA UTARA. This research uses a qualitative approach with a qualitative descriptive research type. The data used comes from interviews with financial operators at the FITK financial office. The research results show that the implementation of the SIMMONA application in the Finance Office of FITK UIN SUMATRA UTARA has been running effectively and efficiently in assisting Finance Employees in managing the finances of the Tarbiyah and Teacher Training Faculty of UIN SUMATRA UTARA. However, in its operation there are still obstacles that do not have a significant impact, namely the system errors while being used, which hinders the data input process and disrupts network connections. The SIMMONA application has a very important influence in the FITK Finance Office, where with this system, FITK's financial management will create optimal accountability and transparency. And the SIMMONA application can also minimize recording and calculation errors.