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Crime, an unlawful act that contradicts ethics and norms, has now become a primary factor for the police in Lampung province. This presents a challenge for the police institution in predicting high crime rates. However, there are still many crimes that have not become the main focus of problem-solving at the Lampung Regional Police.This research aims to identify the types and criminal acts of crime with the highest recorded incidence in a crime dataset by performing classification using the Naïve Bayes algorithm. The data was obtained from investigators at the Directorate of General Criminal Investigation of the Lampung Regional Police, with a total of 12,034 JTP (Total Criminal Acts) and 7,518 PTP (Crime Resolution) data points for each type of crime, distributed across the Regional Police, City Police, and District Police throughout Lampung province. The classification process using the Naïve Bayes algorithm reveals the relationship between the work unit (Satker) and the type of crime handled, thereby identifying crime patterns based on the location where they are handled. The results of the research, which involved converting numerical data into binomial (binary) form using the "Numerical to Binominal" feature in Rapid miner, show that the analysis and modeling process, especially in algorithms like Naïve Bayes or decision trees, is more effective when using data in a binary format. Thus, the initial dataset can be visualized in the form of a , with the size of the text varying according to the level of each high-incidence crime; the larger the text, the more frequently or significantly the crime occurred or was reported. The application of this method can help in identifying patterns, dominant trends, and areas of focus for more targeted law enforcement efforts or crime prevention policies.

This study aims to analyze the factors that influence students' interest in continuing their education to college using a machine learning approach. Data was collected through an online questionnaire completed by 727 students between July 27 and August 22, 2025, covering 23 variables consisting of respondent identity (gender, grade level, major) as well as internal and external factors such as parental support, learning motivation, and preferred type of college. The data preparation stage was carried out through column cleaning, deletion of empty data, encoding of categorical variables, and division of the dataset into 80% training data and 20% test data. The Naive Bayes algorithm of the CategoricalNB type was used because it was suitable for the categorical nature of the data. The evaluation results showed that the model was able to predict student interest with 96% accuracy. For the class of students interested in continuing their studies, the precision, recall, and F1-score values were above 0.95, while the performance in the class of students who were not interested was slightly lower due to the smaller amount of data. These findings show that Naive Bayes is proven to be effective and reliable in classifying students' interest in continuing their studies and can be the basis for decision-making in designing more targeted educational strategies.

This study conducts a Systematic Literature Review (SLR) to explore the impact of users’ mental models on the implementation of Multi-Factor Authentication (MFA) as a strategy for mitigating password guessing risks in organizational environments. Amid the growing landscape of cyber threats, single-factor authentication has proven to be vulnerable, making MFA an essential layered security solution. However, the adoption of MFA remains slow. Existing studies indicate that expert users perceive MFA as a useful additional layer of verification, whereas non-expert users often view it as a burdensome task (a chore) and may even struggle to distinguish between different types of MFA. Dependence on mobile devices emerges as a common source of frustration for both groups. These findings emphasize that understanding users’ mental models is crucial for improving the implementation and usability of MFA. Innovations such as adaptive MFA or Single Input Multi-Factor Authentication (SIMFA) show potential as solutions to balance security requirements and user experience.

Kemajuan teknologi informasi diharapkan dapat menjadi alat yang dapat membantu proses pengelolaan data. Pengelolaan dan penggunaan data yang tersistematis dapat menghasilkan informasi yang rinci. Pengelolaan data yang baik dapat meningkatkan kualitas informasi yang diolah. Pada perancangan database, terdapat hal-hal penting yang harus diperhatikan, diantaranya adalah constraint, type data dan relasi yang dibutuhkan untuk masing-masing table yang ada pada database. Constraint, type data, dan relasi yang tepat dapat meningkatkan performasi dari database yang dimiliki. Fokus pembahasan pada paper kali ini adalah optimisasi table dari database yang digunakan pada aplikasi pencatatan keuangan digital. Optimasi yang akan dilakukan pada penelitian ini mencangkup optimasi penggunaan constraint yang tepat untuk setiap kolom untuk masing-masing table yang ada pada sistem pencatatan keuangan digital yang ada, selain constraint, hal yang dilakukan adalah optimasi untuk type data yang sesuai untuk masing-masing kolom yang ada pada setiap tabel database. Pada tahap percobaan nantinya database yang ada akan di ekspor ke dalam database MySQL menggunakan aplikasi XAMPP. Data yang akan digunakan untuk pengujian sebesar 1.585 data catatan keuangan yang dilakukan user melalui aplikasi.

Human daily life depends on air, so air quality needs to be protected especially against pollution. Decreasing air quality due to dust pollution can result in ARI. Makes it easier to measure ambient air and air temperature using internet-based technology. Designing internet-based dust and temperature measuring devices using the gp2y1010au0f type dust sensor, and DHS11 sensor as a temperature sensor, amplifier circuit, NodemCU microcontroller, and LCD (Liquid Crystal Display). The measurement application is carried out at the location of the PT. Djabus Tunas Utama Ngoro Mojokerto East Java at 10 sampling points around the mixing tube. The measurement results show the concentration carried by ambient air quality standards when the engine stops, so it is safe for employees. When the machine is mixing and the machine is not mixing (ordinary conditions) the concentration of particulates and the temperature exceeds the ambient air quality standard, for that all employees are required to use PPE.

Genetic Algorithm is a kind of search algorithm based on the mechanics of natural selection and genetics. This algorithm can  search  for a global optimum  solution using multiple path and  treat  integer problem naturally. This paper presents application of Genetic Algorithm for determining the size, location, type, and number of capacitors to be placed on radial distribution system. The objective is to minimize the peak power losses and energy losses in the distribution system considering the capacitor cost. The algorithm was implemented in Delphi programming language and tested for a realistic physically­existing feeder to show its feasibility and capabilities.

When creating databases for GIS-applications often existing maps are scanned and vectorised for used. However, vectorisation becomes obsolete when GIS-objects can be referred to both in theme and geometry in a raster environment. This article shows to use model spatial data raster and vector for GIS - applications in both the graphical and image structure. Geographical data must first be converted into a computer- readable format before it can be used in a GIS. Spatial data are "elements that can be stored in map form." These elements correspond to a uniquely defined location on the Earth's surface. Spatial data have also been describe as “any data concerning phenomenon a really distributed” in two or more dimensions. (Peuquet and Marble, I990.) Data model is the rules to convert real geographical variation into discrete objects. There are two main GIS data models - vector and raster. Each of the two data models has specific types of data, analysis and displays that can handle better than the other system. The vector model represents geographical reality as a series of discrete objects or features, classified as points, line's or areas (polygons). The geographical co-ordinates describing the locations of these features are stored in the computer database which lies at the heart of the GIS. In the raster model a regular grid of cells, or pixels, is used to encode the features found on the earth's surface. Each pixel has a number associated with it representing; the value of a geographical phenomenon, such as terrain elevation, soil type or biomass. Layers of raster grids covering the same region can be built up to represent further variables.

The passage analize about the model of DSS. Models begins step from DSS concept. After that, we must choose modeling approach, beside decision making processes. We have many types of model DSS, especially in statistical, financial and optimization. Finally, we get benefit of models.