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Traditional association rule analysis is effective at uncovering co-purchase patterns but fails to provide a global structural view of the market, which often results in fragmented and isolated insights. This study proposes a hybrid framework that integrates the Apriori algorithm with a Minimum Spanning Tree (MST) in order to validate and contextualize association rules within a single structural backbone. Transaction data from a retail store are transformed into a weighted, undirected product graph using an inverse-support function, and an MST is then extracted to represent the market backbone, while frequent itemsets and strong rules are obtained using Apriori. Experimental results on 236 multi-item transactions show that the MST backbone comprises 10 products and 9 fundamental links, with 66.67% of these links being confirmed by strong association rules, indicating a substantial coherence between statistical and structural evidence. The proposed model identifies 41 Apriori patterns that can be embedded in the MST and ranks them using a new metric, Structural Distance, which enables the categorization of Core Patterns, Bridge Patterns, and Complex Patterns according to their structural tightness. This hybrid perspective distinguishes dense, strategically meaningful bundles from anomalous but frequent combinations that are structurally peripheral, thereby offering a more holistic and actionable alternative to conventional Market Basket Analysis. The validated framework can support various applications, including store layout optimization, cross-selling strategies, and the design of path-based recommender systems, and it opens avenues for future extensions based on dynamic graphs and Graph Neural Networks.

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.

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 problems in rice fields are complex and varied, depending on geographic location, rice variety, and growing season. Pests often cause serious economic losses. The Solar Sonic Repeller is an innovative portable pest control device designed to address pest problems by utilizing renewable energy, specifically solar energy. This product aims to offer an environmentally friendly and efficient solution. It works by emitting ultrasonic sound waves with a frequency of 30,000–40,000 Hz. The device's advantages lie in its portability and energy independence, thanks to the use of a charging module powered by an integrated photovoltaic (PV) panel with automatic battery charging during the day. The first test measured the output frequency using an oscilloscope to verify that the oscillator circuit produced waves at the specified frequency. The second test measured the device's effectiveness by examining the pest response to the device at various distances. This test was effective within a maximum radius of approximately 14 m from the center point, covering a rice field area of ​​250 m2.

Indonesia has extraordinary resources and potential in developing renewable energy sources (RES), but various obstacles must be overcome in implementing RES. The purpose of this study is to analyze the gap in the application of RES. This gap includes energy knowledge, community participation, battery waste management, service quality, regulation, and legal policy. This study uses a mixed-methods approach, by conducting a structured questionnaire in quantitative data collection, while qualitative data collection through special interviews, focused group discussions, and conducting policy regulation analysis. The results show that 62% of people do not understand RES, 28% are involved in project planning, and 74% are unaware of SOP (standard operating procedures) regarding battery waste recycling. The results of the correlation analysis reveal a positive relationship between the level of knowledge and interest in RES (R = 0.56). Also, the developed community-based participation model includes initial involvement, transparency of information, and local incentives. These findings further strengthen the compatibility of the innovation diffusion theory, planned behavior theory, SERVQUAL, and the theory of public interest. This study will make a practical contribution through evidence-based strategies in increasing resilience, especially for policymakers and energy service providers. The impact of the policy aspects includes the need for large reforms, education, public campaigns, and the realization of battery waste management systems. This study also provides an opportunity for further study by expanding the geographical scope and related industrial sectors.

Barru Regency tourism has a variety of tourist attractions, but information related to the location and potential of tourism has not been digitally integrated, making it difficult for tourists and the government to access data. This study aims to design and build a web-based Geographic Information System (GIS) that can map the location of tourist attractions in Barru Regency interactively, easily accessible, and equipped with supporting information in the form of descriptions, types of tourism, photos, and travel routes. The research method used is Research and Development (R&D) with the stages of tourist attraction surveys, interface design, feature development, and system testing. The results of the study are in the form of a website "Web-Based Geographic Information System for Mapping Tourist Attractions in Barru Regency" which is able to present tourist information systematically and easily understood. The conclusion of this study shows that the developed system can be a supporting medium in disseminating tourism information, helping tourists find tourist locations, and supporting the local government in managing and developing the tourism sector based on spatial data. This application also has the potential to be an educational and promotional tool to increase tourist visits to Barru Regency

The manual employee attendance process at the Perjuk Village government level often results in inaccurate data, delayed recapitulation, and difficulties in real-time attendance monitoring. This study aims to develop an Internet of Things (IoT) and Radio Frequency Identification (RFID)-based village employee attendance system to simplify the administrative process and improve the efficiency of attendance recording. The development method used is the Research and Development (R&D) model with stages including needs analysis, system design, validation, field trials, and product revisions. The system was built using an ESP32 microcontroller, an RC522 RFID module, and a Wi-Fi connection to transmit attendance data to a web-based server. Testing was conducted using the black box method to ensure all system features run according to design. The results of the black box test show that all features run according to design. The system records attendance automatically with 100% accuracy, saves data to the server database, and displays reports in the form of tables, graphs, and statistical cards. The study concludes that this IoT and RFID-based attendance system is able to improve the accuracy, speed, and efficiency of recording compared to manual methods, and is in accordance with operational needs at the Perjuk Village Office.

Terrestrial digital television transmitter stations are the main facilities in the transmission of digital television broadcasts to the public. The quality of the transmitted signal is expected to reach the Central Java-1 service area well so as to provide optimal and reliable quality of digital television broadcast performance according to the needs of the community, but currently, complaints about signal problems such as service coverage and reception quality still occur a lot, coverage and signal quality received by community-owned television transmitters cannot be separated from the influence of the quality performance of digital television transmission stations. The purpose of this research is to analyse the coverage performance of digital television services of digital television transmitter stations using the K-Means Clustering Method, identify areas with the best signal coverage and group areas based on the level of signal performance. The data used includes field strength parameters collected through field measurements at 25 service area location points, topography factors and transmitter distance were found to be the main causes of signal quality differences. Data analysis shows that the K-Means Clustering method effectively clusters areas with signal reception quality categories of very good cluster 3 areas, good cluster 8 areas, fair cluster 5 areas and poor cluster 9 areas. The results of this study can be recommended in the evaluation and optimisation of tele-transmitting station networks.

Technological advancements have brought fundamental changes in the way we interact with digital images and photography. One significant milestone in this development is the Photoshop Express Photo Editor, which has become a primary platform for image processing and editing. Datasets are used to analyze sentiment and are utilized during the accuracy testing phase. Based on the testing results, the Convolutional Neural Network (CNN) algorithm achieved an average accuracy value of 86.50%, compared to the Naïve Bayes (NB) algorithm, which achieved an average accuracy value of 75%. The results of the research conclude that the choice of sentiment analysis method should be tailored to the needs and limitations of the system. If a fast, light, and easy-to-understand process is required, the Naive Bayes method is the right choice. However, if accuracy and context understanding are the top priorities, then CNN is a superior approach, although it requires more resources. Additionally, based on the Wordcloud data, it is known that the majority of comments are positive, indicating that the reviews or texts analyzed contain many positive expressions related to quality, usability, and ease of use.

Current technological advances have made the need for information technology very necessary. With the existence of web-based geographic information system technology, it can help PT. Telkom Indonesia Tbk Prabumulih City Branch to digitize every Indibiz customer and target area for Indibiz products. The aim of this research is to create a web-based Indibiz customer mapping information system and to improve technician performance in matters concerning Indibiz. The research method used is descriptive qualitative, the Waterfall method as a system development method and UML as a design tool. The application was built using a website with the php programming language, a mysql database, and printing data using pdf files.

The insurance business within an insurance company offers insurance products owned by the insurance company. In every insurance product there is a premium payment and the premium is the income of an insurance company at the rate of the amount insured. The problem that PT BNI Life Insurance has is that there are many stops in premium payments such as policy redemptions due to errors in the benefits received or incorrect selection of the insurance product, this can reduce the achievement of targets for an insurance company. The aim of this research is to find out the best classification algorithm compared between K-Nearest Neighbor and Naive Bayes to predict the type of insurance product that customers will choose. In this research, data mining methods are applied to compare two different methods, namely the K-Nearest Neighbor method and the Naïve Bayes method. The level of accuracy results for the K-Nearest Neighbor method is 80% and the Naïve Bayes method is 70.53%, which means that the K-Nearest Neighbor method is the best method to apply to an insurance product classification system based on the demographics of prospective customers.

In buying a laptop, you need to look at the specifications and standards that are tailored to your needs and requirements. Some of the standards and requirements include looking at several aspects of the criteria including the price of the laptop, RAM (random access memory), processor, hard drive capacity, screen size, VGA (video graphic adapter), battery power, weight, length of warranty, availability of spare parts, service range center. The fuzzy method is a method that makes it easy to find a value that is still vague and also linguistic, the use of the sample additive weighting (SAW) method is used to assist calculations in supporting decision making. The choice of using the SAW method is simpler in calculations, but the results of the calculations are accurate. From the results of calculations using the SAW method, it is calculated that between laptop 1 to laptop 7 with a price preference weight of 30, RAM 10, processor 10, hard disk capacity 10, screen size 5, VGA 3 (video graphic adapter), battery power 7, weight 5 , length of warranty 10, availability of spare parts 5, distance to service center 5, the highest order starts from laptop 1 with a total value of 18.4, laptop 7 with a value of 16.6, laptop 6 with a value of 13.6, laptop 5 with a value of 13.5, laptop 3 with a value of 13.2, laptop 4 with a value of 11.2, laptop 2 with a value of 8.9. The results of the assessment can change according to the needs of laptop buyers, who are more concerned with which criterion has the most important weight.

The search is often used to search for the shortest route, the Hill Climbing Method is a part of the test that uses heuristic functions. The problem that is often encountered is in the form of miscalculations in calculating the distance so that it requires long distances, costs a lot and takes a very long time. To solve this case, it can be solved by making a structure graph by looking at the city points from the two sides of the point to be passed. Using an algorithm can help make it easier to find a location and save time and travel costs that will be passed. This advantage is that all points will be obtained and checked from the right and left sides one by one so as to obtain effective and maximum results. The Hill Climbing method that will be used has the concept of a geographic information system as a guide and is used as a system for decision making. The heuristic search method is one of the methods commonly used in finding a way

This research was made with the aim of developing the application of determining the recipient of Rastra (Rice Prosperous) aid in Tobu Village. South middle Timor district by applying the exponential comparison method. Variables or criteria used in this study are work, income, number of dependents, building area and housing conditions and detailed criteria on each variable. This research succeeded in developing an application ranking community beneficiaries of Rastra in Tobu village by using the exponential comparison method (MPE). In this application provides a graphical display feature, print reports that will be used to print and view the results of the ranking of people who are entitled to receive Sejahtera ria. 

The infrared detector (or IR detector) is an optoelectronic component and represents the core element of gas analyzers, flame sensors, devices of spectral analysis, as well as non-contact temperature measurement. pyroelectric infrared detectors work with  stabilization time  in a wide operating temperature range (-55 ... 85) °C, capable of measuring the slightest amounts of infrared radiation (as little as a fraction of a nW) with wavelengths between 1 µm and > 25 µm. The difference of the good pyroelectric or No good (NG) devices shown by graph of voltage offset operating that can check by manual using Digital Multi Meter or semi auto by using microcontroller One of importance measuring of IRD sensors  is Offset Voltage, stabilization of offset voltage indicate the sensor is stable with certain level value. Stabilization value measurement during measuring time means the average value not so much different with fluctuation value.  10 bit ADC on Atmega 328 that main microcontroller on Arduino Uno is capable to measure the Offset Voltage of IRD sensor and check the measurement values is within specification of IRD sensor.

At present the information of schools in various fields of education in the Tugu sub-district is still incomplete that only covers the TK / RA and SD / MI levels so that the wider community has not been able to obtain information on the level of education at SMP / MTs, SMA / SMK / MA and Higher Education, and to get this information the public must come directly to the Semarang City Education Office to find the data needed. The public cannot know quickly if there is a change in data or if there is a construction of a new school because the information is only written on the sub-district bulletin board. Tugu sub-district is a sub-district in the city of Semarang, Central Java province. Tugu sub-district region is bordered by the Java sea in the north, in the east by West Semarang Sub- district, in the south by Ngalian sub-district, and in the west by Kendal district. Tugu sub-district has an area of ± 3.444,22 Ha hectares, consisting of 7 kelurahan, namely Jrakah, Tugurejo, Karanganyar, Randugarut, Mangkang Wetan, Mangunharjo and Mangkang Kulon [7] Various suggestions appear to help equip human work to be more efficient and productive, we need a system that can help the work needed by a web-based Geographic Information System. Geographic Information System is a computer-based system for processing data or information that has a geographical dimension [1]. The program used in research uses the PHP programming language, JAVA SCRIPT because this program can be run on a server and is quite reliable using a MySQL database. [3]