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The development of renewable energy, particularly Solar Power Plants (PV), requires a reliable, real-time, and easily accessible electrical energy monitoring system to ensure optimal system performance. This study aims to design and implement an Internet of Things (IoT)-based electrical energy monitoring system for PV using the NodeMCU ESP32 microcontroller, the PZEM-004T sensor for measuring electrical parameters, and the Node-RED platform as the data visualization interface. The developed system is designed to monitor voltage, current, power, energy, frequency, and power loss in real time, and then display the data in the form of numerical values, graphs, and indicators on a dashboard accessible through a local network. The research method includes hardware design, software development (sensor reading, data processing, and communication), integration with Node-RED, and system testing on a small-scale PV installation. The test results show that the system is capable of monitoring electrical parameters in a stable and responsive manner. Variations in sunlight intensity were found to affect the current and power produced by the solar panels, whereas the inverter output voltage tended to remain within normal operating ranges. The Node-RED dashboard display was considered informative and helpful for users in monitoring and analyzing PV performance. Based on these results, it can be concluded that the IoT-based electrical energy monitoring system designed in this study functions well and is feasible for application in residential or educational-scale PV installations. The system still has the potential for further development through cloud service integration, the addition of environmental sensors, and enhancements to data analysis features and user interface design.

Tourism is one of the sectors that plays an important role in boosting economic growth through travel activities and destination exploration. Tourists' preferences for nature-based tourism options, such as mountain hiking or beach tourism, are influenced by various factors, ranging from personal experiences and recreational interests to social characteristics. Therefore, a technology-based approach is needed to predict destination choice tendencies more accurately. As artificial intelligence technology develops, deep learning methods have been widely used in classification processes due to their ability to process large amounts of data and recognize complex patterns. In this study, a Multilayer Perceptron (MLP) model is used to classify tourists' preferences between mountain or beach destinations based on a survey dataset. The research stages include data processing, data splitting using a train-test split, model training, and performance evaluation using accuracy, precision, recall, and F1-score. The test results show that the MLP model is capable of achieving an accuracy rate of 99%, confirming that deep learning methods are effective in automatically mapping tourism preference trends. This research is expected to serve as a basis for the development of more personalized travel destination recommendation systems, as well as to support tourism management in formulating targeted promotional strategies.

Relational databases store information in interconnected tables and are widely used for data management and retrieval. However, in certain environments, the original values stored in a relational database cannot be exposed during data retrieval. This limitation creates a challenge because common encryption methods only transform data for storage and do not support mathematical operations needed for value matching. Partially Homomorphic Encryption is a cryptographic approach that allows specific mathematical operations to be performed directly on transformed data without restoring it to its original form. This study proposes the use of Partially Homomorphic Encryption to enable value-based data retrieval while keeping all stored values in their transformed form throughout the entire process. The method relies on homomorphic properties that allow mathematical comparison to be conducted on encrypted data, making the retrieval process possible without revealing the original values. The results show that this approach can perform data retrieval operations in a relational database while preserving the transformed structure of the stored data. The proposed method offers an alternative for environments that require data retrieval without exposing original values and demonstrates the potential of homomorphic techniques in supporting secure and functional data processing in relational database contexts.

The management of service centers at the Indonesian Rede Cross (PMI) in East Jakarta is still conducted manually, which slows down service processes and increases the likelihood of data processing erorrs. This research aims to design a Java-based application to automate patient registration, admission, handling, emergency services, available ambulance data, and the preparation of reports as quickly as possible. The application was developed using the Java programming language with a prototype model approach in software development. Testing results indicate that this application successfully enhances the efficiency and accuracy of PMI East Jakarta’s operations, particularly in managing data related to patients, actions, personnel, and ambulance availability. It is hoped that this application can be integrated with other PMI regions to establish a more structured and connected service management system.

Most dairy farmers in our country still rely on human labor to monitor the condition of their farm areas. The current problem is the manual security system for barns, meaning that the barns need to be constantly checked around the area at all times. This is especially risky at night, when livestock theft is more likely to occur. This research implements PIR sensor technology to monitor movements around the barn, MC-38 magnetic sensors for gate security, and utilizes Android smartphones as devices to display barn data processing results, allowing real-time monitoring of barn security. The research is conducted using the Research and Development (R&D) method by Borg & Gall, encompassing only six steps. The results of the system evaluation by experts show a score of 3, falling between 2.1 – 3.0, categorized as Valid. User validation results show a score of 27.2, also falling between 2.1 – 3.0, categorized as Effective.

Sistem Informasi Rencana Umum Pengadaan (SIRUP) Lokal is a web-based application utilized by the Government of Central Java Province for procurement planning of goods and services. Of course, evaluation is needed to measure the usability level of the SIRUP Lokal and as input for future development purposes. The respondents of this research are active users of SIRUP Lokal, totaling 100 people. This research is quantitative in nature with descriptive analysis. Data collection is done through questionnaires. Data processing and analysis utilize statistical tools, namely SPSS. The results of this research indicate that SIRUP Lokal is perceived to be highly beneficial for users, especially 1) The system’s performance is considered superior, excelent, and well-received by users 2) Users tend to recommend the system to others. 

The purpose of the research conducted was to design an Academic Information System (SIAKAD) at SMA Negeri 2 Rambang Dangku. Data processing at SMA Negeri 2 Rambang Dangku has not utilized the use of information technology to support operational activities, data processing is still recorded manually, such as in processing student assessment data, teacher data, lesson schedule data and student final report data (Raport) and data storage is still done conventionally using paper and cabinets. In collecting data, researchers used qualitative descriptive methods including conducting interviews, direct observation, and literature study. The system development method uses the Prototype method. At the design stage using the Unified Modeling Language (UML) modeling which consists of use case diagrams, class diagrams, and activity diagrams. This system is built using PHP, Mysql, Xampp, and database. The results of this study are a web-based academic information system using the Codeigniter Framework. From this application it is hoped that it will make it easier to process Academic data for SMA Negeri 2 Rambang Dangku so that it is faster and more detailed, and makes it easier to make final data reports on student scores (Rapot).

Data Processing PT. Daya Cipta Karya Sempurna regarding the entry and exit of goods at PT. Daya Cipta Karya Sempurna still uses a semi-manual system where when the ordered goods arrive, the items will be recorded in the warehouse using Microsoft Excel. Likewise with the items that come out are also recorded in the warehouse using Microsoft Excel. In addition, this information only exists in the warehouse so that when other parts or want to know the inventory of existing goods, other parts cannot access it directly. The section must ask the warehouse to find the state of the desired supply and must wait to get the answer. As a solution to the problems above, it takes an inventory system at PT. Daya Cipta Karya Sempurna Power that can be used to manage goods group data, goods data, user data, incoming goods data and outgoing goods data as well as display reports

ABSTRACT A web-based futsal field reservation system was developed to help facilitate the process of booking or leasing a futsal field. The system uses PHP and HTML programming languages by using MySQL as data storage. The purpose of designing this system is to make it easier for users to rent futsal fields. With the futsal field reservation system is expected to facilitate in data processing, scheduling and registration of members or customers. In the end, this system is expected to help the company's performance, and can also facilitate customers in the ordering process.

Academic means the teaching and learning process carried out in the classroom or school world. Academic information systems at SMAN 1 Ketungau Tengah previously still use manual management systems, such as the calculation of final manual values ​​as a result can cause delays in giving value, the data received is still in the form of paper files that can be lost or damaged, and not connected to the network from one computer to another computer so that the process of moving data still uses a flashdisk. The system certainly has a lot of weaknesses, the implication of which is the weakness of the administrative system, the waste of energy, the less optimal service, for example the distribution of report cards which are sometimes late, slow data processing and calculation errors. The system created aims to help ease calculations, can enter data more effectively and efficiently. The system development method used is SDLC (Sytem Development Life Cycle) which consists of planning, analysis, design, implementation and maintenance. Using the PHP programming language in its creation and MySQL as the database. The results of this study are a Mobile Web-based Academic Information System that helps the admin (staff) in managing data and printing report cards, teachers in managing values, students and parents / guardians in looking at schedules and grades.

Diabetes is a serious chronic disease that occurs because the pancreas does not produce enough insulin (a hormone that regulates blood sugar or glucose), or when the body cannot effectively use the insulin it produces. WHO data shows that the incidence of non-communicable diseases in 2004 reached 48 , 30% is slightly higher than the incidence rate of infectious diseases, namely 47.50% [1]. According to the Ministry of Health in 2012 diabetes caused 1.5 million deaths. Some Indonesian people, this disease is better known as diabetes or blood sugar. This research was developed through secondary data processing from the Pima Indians Diabetes Dataset health database which was taken from the Kaggle dataset and can be accessed through https://www.kaggle.com/uciml/pima-indians-diabetes-database. Where the data itself consists of 768 records with several medical predictor variables (Pregnancies, Glucose, Blood Pressure, Skin Thickness, Insulin, BMI, Diabetes Pedigree Function, Age and Outcome). Then the data will be processed using the Particle Swarm Optimization (PSO) feature selection to increase the accuracy value and the Naive Bayes algorithm to determine the accuracy results of the diagnosis of diabetes. From the results of research that has been done for the accuracy of the classification algorithm Naive Bayes is 74.61%, while the accuracy of the classification algorithm with Particle Swarm Optimization is 77.34% with an accuracy difference of 2.73%. So it can be concluded that the application of the Particle Swarm Optimization technique is able to select attributes in the Naive Bayes Algorithm, and can produce a better level of diabetes diagnosis accuracy than using only the individual method, namely the Naive Bayes algorithm. Keywords: Diabetes, Particle Swarm Optimization, Naive Bayes Algorithm

One of the survey activities carried out at the Baitul Giradh Baburrayyan Cooperative was regarding the coffee production of members who are members of the Baitul Oiradh Baburrayyan Cooperative organization, which aims to speed up the data processing process and make it easier to produce reports on production. To carry out these activities quickly and precisely, it is necessary to make an application as a tool in the data processing and presentation of data that will be needed by data users. This data processing application is made using the gambas programming language.