The rapid development of information and communication technology has driven the need for information services that are more relevant and adaptive to user behaviour. This research aims to integrate data analytics in the study of user behaviour to support the development of effective information services. The dataset used is Kaggle's Online Retail Dataset, which includes sales transaction data of online retail companies in the UK from December 2010 to December 2011. The analysis was conducted through customer segmentation using K-Means Clustering algorithm and predictive analysis with Association Rule Mining. The segmentation results successfully grouped customers into four main clusters, namely loyal customers, potential customers, passive customers, and low-spending customers. Model evaluation showed optimal performance with an accuracy rate of 85%, precision of 82%, recall of 78%, and F1-Score of 80%, and Silhouette Score of 0.62, indicating effective customer segmentation. The findings prove that the application of data analytics can provide deep insights into customer behaviour and support the development of more personalised and adaptive information services. This research is expected to be a reference in designing data-driven information service development strategies in various sectors.

Birth certificate data management is an important aspect of population administration. In the digital era, the need for efficient systems is increasing to overcome various challenges, such as manual errors, slow administrative processes, and difficulties in searching for data. This research focuses on designing a data management system for Indonesian citizens' birth certificates at the Batu Bara Regency Population and Civil Registration Service (Dukcapil). This system was designed using a systematic approach, starting from needs analysis to the implementation stage. The method used involves collecting data through interviews, literature study, and direct observation in the field. The result of this design is a digital-based system that makes it easier to record, store and manage birth certificate data efficiently. By implementing this system, it is hoped that it can improve the quality of public services, minimize data errors, and support the government's digitalization program.

The Jayapura City Transportation Agency faces significant challenges in managing traffic violation data due to rapid population and economic growth. The use of Excel-based systems has proven inadequate, so a more integrated and efficient information system update is needed. Thus, the research and development method to design a web-based data archiving information system application with a waterfall methodology approach. It is hoped that this application can improve the efficiency of filing and searching for violation data, as well as support better traffic control in Jayapura City.

This research aims to examine and analyze the work system implemented by the archives management section at the Batu Bara Regency Library Service. Archives are an important source of information to support the smooth running of administration and public services, so their management requires an efficient and organized system. This research uses a qualitative descriptive approach, with data collection through interviews, observation and documentation studies. The research results show that the archive management work system at the Batu Bara Regency Library Service still faces several obstacles, such as limited facilities and infrastructure, as well as a lack of human resources trained in the field of archive management. However, the archives management department attempts to overcome this problem by implementing a system that is in accordance with existing procedures. It is hoped that the results of this research can provide recommendations for improving the records management work system in related agencies, in order to increase efficiency and effectiveness in public services.

Puskesmas Kosambi employs Non-PNS staff whose discipline, particularly regarding attendance and work location, needs to be evaluated. The previous manual attendance system was found to be ineffective in monitoring staff discipline. This study aims to develop a mobile-based attendance system equipped with GPS radius and selfie photo features to improve the accuracy and management of attendance. The GPS radius feature ensures that staff can only clock in within the designated area, such as the Puskesmas area, while the selfie photo feature verifies the identity of the staff member clocking in. This study involved 24 Non-PNS staff members and used the K-Means Clustering algorithm to group staff based on their discipline levels. The results showed that the system was effective in improving staff discipline, with 11 employees categorized as highly disciplined, 10 as moderately disciplined, and 3 as lowly disciplined. The implications of this study suggest that the implementation of a mobile-based attendance system can improve attendance monitoring and enhance work discipline at Puskesmas Kosambi.

In  recent  years,  air  quality  has  become  an  increasingly  important  issue  in  various  cities  around  the  world.  Real-time  air  quality  monitoring  is  essential  for  identifying  pollution  problems  and  taking  appropriate  actions.  This  article  discusses  the  design  of  an  Internet  of  Things  (IoT)-based  air  quality  monitoring  system  using  the  prototype  method.  The  system  is  designed  to  monitor  air  quality  parameters  such  as  PM2.5,  PM10,  CO2,  and  temperature  in  real-time  and  present  the  data  to  users  through  a  web-based  application.

The rapid development of information technology has provided great opportunities for the service sector to improve efficiency and convenience, including in vehicle washing services. This research aims to develop a web-based system using the Laravel framework, which is designed to simplify the online ordering process and overcome queuing problems. The system features user authentication, location-based booking, payment gateway integration for real-time transactions, and an interactive dashboard for service providers. The case study was conducted at Carenmore, a vehicle wash service in Krian. The implementation results show that the system is able to reduce customer waiting time, provide a better user experience, and improve service efficiency. Further development is recommended to add a variety of features, improve interface design, and increase the system's ability to handle larger user loads.

Technological developments in the agricultural sector, especially in the hydroponic method, provide solutions for optimizing plant growth in urban environments. This research integrates ESP32 microcontroller technology with a DS18B20 temperature sensor and TDS sensor to monitor and control temperature and nutrient quality in a hydroponic system. In addition, the Sugeno fuzzy logic method is used for automatic water quality monitoring.

Assembling a personal computer and installing the Windows operating system are important activities in mastering information technology. This research aims to provide an in-depth understanding of the computer assembly process and operating system installation. The methods used include a Research and Development (R&D) approach, hands-on practice, and question-and-answer sessions. The research results show that systematic assembly steps and proper installation can produce a well-functioning computer. In addition, initial testing after assembly is crucial to ensure that all devices are detected correctly. It is hoped that this research can serve as a reference for information technology education and enhance students' practical skills in the field of computers.

Task scheduling in cloud computing environments is a crucial aspect in optimizing resource allocation and improving system efficiency. This research aims to analyze trends in task scheduling algorithms in cloud computing using a Systematic Literature Review (SLR) approach on various scientific publications published between 2018 and 2025. The results of the study show that Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Genetic Algorithm (GA) algorithms are the most commonly used methods in solving task scheduling problems. PSO stands out as an effective algorithm due to its ability to find global optimal solutions, handle non-linear and multimodal problems, and its efficiency in managing computational resources. Additionally, various studies have shown that optimization of scheduling algorithms can be achieved through a combination or modification of existing methods to improve system performance. This study provides in-depth insights into the development of scheduling algorithms in cloud computing and opens up opportunities for further research in developing more innovative and adaptive approaches.