This study discusses 5G network security regulations and policies from a national and international perspective, with a focus on the challenges and handling of global cyber threats. Given the cross-border threats, security and regulation are important issues in the implementation of 5G technology. The approach used is qualitative interpretive with additional limited experiments, including cyber attack simulations. The result of the study show that cyber policies in Indonesia are not yet fully coordinated, unlike countries such as the US, the European Union, and China which have more comprehensive regulations. Experiments prove that the implementation of protocols such as IPSec and TLS can reduce risks in 5G networks. Therefore, Indonesia is advised to form more integrated regulations that comply with international standards. This study also suggests further research in real scenarios and the development of a more in-depth policy evaluation system.

The development of the Smart City concept demands a reliable, flexible communication network infrastructure capable of covering the entire urban area. This study designs a wireless network based on mesh topology as a communication solution to support various Smart City applications. Mesh topology is chosen for its advantages in scalability, path redundancy, and fault tolerance. The research method involves designing a network simulation with varying numbers of nodes and testing performance parameters such as throughput, latency, and packet loss. Simulation results show that an increase in the number of nodes correlates with higher throughput, lower latency, and reduced packet loss. These findings indicate that mesh topology is highly suitable for meeting the real-time and stable connectivity needs of Smart City implementations. This network design is expected to serve as a foundation for future digital infrastructure development in smart cities.

Coal companies in Indonesia each year experience an increase in the amount of production that will be distributed to industries both domestically and abroad. Where some coal companies entrust other companies as contractors in terms of renting heavy equipment units to move overburden or all soil/rock that covers the coal layer. In terms of renting heavy equipment units, the contractor company will calculate the rental cost of the heavy equipment unit when carrying out mining activities by calculating the number of iterations on the heavy equipment unit used. This iteration is the number of heavy equipment work cycles in a certain time unit, sometimes the calculation of the number of iterations has a difference in calculation which results in one party experiencing a loss. Therefore, to overcome the difference in calculation, the researcher created a tool, namely the "Prototype of the Automatic IOT-Based Iteration Calculation Tool on Heavy Equipment Units" so that there is no more difference in the calculation of iterations during the mining process and the productivity of the tool will be in accordance with the planned plan.

The 5G network represents a major technological advancement driving the progress of the Internet of Things (IoT), particularly through its ability to transmit data at high speeds with near-instant response times. It enables stable connectivity for a greater number of IoT devices within a single area without compromising network performance, thereby supporting the development of advanced applications such as smart cities, precision agriculture, smart grids, and modern healthcare services. In the energy sector, 5G enhances smart grid management by enabling more efficient energy distribution. In healthcare, it allows real-time monitoring of patients through IoT-based medical devices. Meanwhile, in the agricultural domain, 5G facilitates intelligent land management and supports more accurate decision-making. Overall, 5G strengthens IoT capabilities by providing highly precise and real-time data, which accelerates analytical processes and improves operational performance. Consequently, 5G plays a strategic role in advancing digital transformation across various industrial and social sectors, boosting productivity, operational efficiency, and service quality, while also opening new opportunities for future IoT implementations.

This article discusses the design of a smart trash bin system based on a microcontroller that can provide real-time notifications via the Telegram application when the trash volume reaches its maximum capacity or when unpleasant odors are detected. The system is designed to enhance the efficiency of waste management in an elementary school environment in Central Java, Indonesia. The developed device utilizes two ultrasonic sensors to detect object proximity and trash volume, as well as an MQ4 sensor to identify methane gas as an odor indicator. The NodeMCU serves as the central controller and network interface for sending notifications to Telegram. Testing results demonstrate that the system effectively detects the trash bin's condition and delivers timely and automated notifications to cleaning personnel. This innovation is expected to serve as a practical and effective solution in supporting a cleaner and healthier school environment.

The purpose of this research is to analyze and explore quantum theorems as a wireless telecommunications security solution in the future. This study uses a quantitative approach through simulation and performance analysis of QKD systems in wireless channels, by combining literature studies and comparative analysis between QKD and PQC. Meanwhile, the wireless communication simulation model, using the QKD protocol and PQC algorithm, with Free Space Optics (FSO), WiFi, and LiFi-based network scenarios. The simulation was carried out using MATLAB. This study is based on QKD, which uses BB84 and CV-QKD protocols on FSO 100m and LiFi wireless channels. And based on PQC, which uses the Kyber algorithm, with AES authentication for communication. Both models were simulated and tested based on the parameters of Quantum Bit Error Rate, Key Generation Rate, latency, and resistance to third-party attacks (wiretapping detection). Furthermore, the analysis was carried out quantitatively and comparatively to compare the performance of QKD and PQC based on the QBER, latency, KGR, and wiretapping detection of implementation. This analysis are combined with data based on the literature, to formulate optimal implementation strategies in the context of future wireless networks. The results indicate that QKD, specifically CV-QKD, has significant potential for use in attack-sensitive wireless communications, such as military, government, and industrial applications. However, this model requires more complex hardware and infrastructure investments in its implementation. Meanwhile, PQC offers a more ready-to-use and cost-effective solution for everyday communications that remains resilient to quantum attacks.

Myers-Briggs Personality Type (MBTI) is a popular personality metric that uses four dichotomies as indicators of personality traits. This study uses a public dataset from Kaggle, namely the Myers-Briggs Personality Type Dataset, the model tested is several machine learning classification models with the help of imlearn under-over sampling techniques for classifying MBTI personality types. This study aims to classify the Myers-Briggs Type Indicator (MBTI) personality type based on text from user posts on the social media platform Reddit. The dataset used in this study consists of around 8,000 posts collected from the MBTI subreddit. Several text processing methods such as tokenization, punctuation removal, and stemming are used to process the raw data before it is entered into the model. The experimental results show that the LSTM model using Adam's optimizer and a learning rate of 0.01 produces good performance with an accuracy of 80.73 compared to other machine learning models. In addition to the LSTM model, XG Boost is also a classification model with the highest accuracy based on 16 personality types producing an accuracy of 60.09 and Logistic Regression with the NS dimension as the best accuracy value of 87.21%.

Sistem pelaporan data khususnya absensi dan penilaian yang diterapkan pada SMA Attaqwa 02 Babelan saat ini masih menerapkan sistem absensi dan input nilai secara semi manual. Semua pelaksanaan dokumentasi pelaporan data absensi dan penginputan nilai siswa dilakukan tanpa adanya sebuah sistem informasi yang memiliki database terintegrasi, pelaksanaan rekapitulasi absensi dan input nilai menggunakan Aplikasi Microsoft Office. Tujuan dari penelitian yang dilakukan adalah Merancang sistem yang dapat memudahkan proses pengolahan data absensi dan input nilai siswa untuk mengurangi potensi kesalahan/kelalaian dan Mempercepat waktu proses rekapitulasi absensi kehadiran siswa dan input nilai untuk efektifitas dan efisiensi pelaporan. Metode yang digunakan dalam penelitian ini yaitu pengembangan perangkat lunak dengan metode prototype, ERD dan LRS untuk desain basis datanya. Hasil penelitian berupa prototype menggunakan desain model UML, guna mempermudah dalam merancang program pada SMA Attaqwa 02 Babelan khususnya untuk pengolahan data absensi dan input nilai.

Clustering is a data mining method that is widely used to group data based on similarity. This clustering process can be used to streamline data so as to facilitate the data ranking process. The purpose of this study was to make comparisons of distance measurements on the K-Means and TOPSIS methods to select students who would take part in industrial visit activities. The method used in this study is the K-Means Algorithm to carry out the clustering process whose results will be processed using the TOPSIS method, both of which use Euclidean, Manhattan and Minkowsky Distance. Based on the clustering process, there were 21 respondents who were eligible to be included, then with TOPSIS a ranking process was carried out. Of the three distance measurements used based on the Pearson Euclidean distance correlation test, the highest results were 0.992, Manhattan 0.982 and Minkowsky 0.980, with ratings one, two and three respectively. For the Spearman correlation, Eculidean is 0.972, Manhattan is 0.982 and Minkowski is 0.955. Thus, Euclidean distance gives the best correlation results, while for alternatives, Manhattan distance or Minkoesky distance can be used.

In writing this study aims to review the implementation of tree data structures on web blogs as learning media, starting from a discussion of the implementation of data structures. After that, it was continued with the use of blogs as an applied learning medium. The use of tree data structures is one of the most common data structures used in the development of a web. One of the efforts to streamline and provide a variation in the realm of learning media is to create a web blog, especially in the era of globalization, everyone who lives in that era should at least know about one of the results of technological and communication advances. This study will see how the description or description of the application of tree data structures on blogs as learning media. The making of this research uses a qualitative descriptive method in which the data is obtained from observation and documentation of matters relating to the topic under study. The core discussion of this research is the implementation of data structures on blogs as learning media.