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Human resources are a company's most dominant asset, because they can play an important role in the company's business development. An outsourcing company is a legal entity and is obliged to comply with business licenses issued by the Central Government. The eligibility process for new employees is supported based on the level of ability and competency determined by the company. The existence of difficulties for companies in determining the eligibility of new employees which makes the reason for the ineffectiveness of the processes carried out by the company at this time, is used as a goal for the authors for the purposes of a study. By using the classification method in a data mining with the C4.5 algorithm (Decision Tree) and a RapidMiner application as a tool in the analysis process carried out to find a factor supporting the process of a new employee eligibility. With the data of 960 applicants used as a sample, this data was taken from 2021-2022. From the data divided into several attributes used, the highest Gain value obtained from these attributes through the results of Test 2 of 0.417152421 which will be used as the root in the process of determining employee eligibility and has the highest accuracy value of 98.44%.

KPRI KOKARNABA Baturraden faces challenges in managing increasingly complex sales data, particularly in identifying the most in-demand products to maximize profit. This study aims to analyze sales patterns using the Naïve Bayes algorithm as a probability-based classification method. The collected sales data were analyzed to identify categories of best-selling and less popular products within the cooperative. The results indicate that the Naïve Bayes algorithm has an accuracy rate of 77.56% in predicting product categories. This research is expected to assist the cooperative in optimizing stock management and improving member satisfaction.

The rapid development of information and communication technology allows society to access various information needed in daily life. The Law of the Republic of Indonesia Number 23 of 2006 concerning population administration serves as an important element in population management. Population documents are issued by official institutions and have legal legitimacy as valid evidence. The method used in this research regarding public sentiment towards e-ID card services is the survey method, which aims to collect data from a large population using a smaller sample. The steps or processes in this research using the SVM method consist of case folding, cleaning, tokenizing, normalization, stopword removal, and stemming. Based on the classification of 150 test data using SVM, the number of positive sentiments recorded is 110 opinions, while negative sentiments recorded are 40 opinions.

Abstract. This study presents a web-based system for identifying traditional herbal leaves using K-Nearest Neighbors (KNN) and image processing techniques focused on analyzing leaf shape and color. The dataset used consists of images of various types of herbal leaves, providing a basis for classification and medicinal benefit information retrieval. The system was tested with multiple leaf samples to assess accuracy, speed, and effectiveness in identifying leaf types based on visual characteristics. Results show that the system can recognize different types of herbal leaves and display information on their medicinal properties in a user-friendly interface..

Non-communicable diseases cannot be transmitted to others, but their development occurs slowly over a long period of time. One of the non-communicable diseases that is a priority in global health today is hypertension. Hypertension often causes complications such as stroke, heart disease, and kidney failure. The aim is to describe the incidence of hypertension in Posbindu PTM Bumiroso participants. The quantitative descriptive method using the total sampling technique obtained 38 respondents. The data was analyzed descriptively to describe the results of the respondents' blood pressure examinations. The results of the study based on the classification of hypertension, participants who experienced pre-hypertension and hypertension level 1 were 12 (31.58%), hypertension level 2 was 9 (23.68%) and normal was 5 (12.16%). The conclusion is that more than half of Posbindu PTM participants experience hypertension, as a suggestion, they can carry out routine checks at the nearest health facility.    

Credit approval prediction is one of the critical challenges in the financial industry, where the accuracy and efficiency of credit decision-making can significantly affect business risk. This study proposes an outlier detection method using the Gaussian Mixture Model (GMM) combined with Extreme Gradient Boosting (XGBoost) to improve prediction accuracy. GMM is used to detect outliers with a probabilistic approach, allowing for finer-grained anomaly identification compared to distance- or density-based methods. Furthermore, the data cleaned through GMM is processed using XGBoost, a decision tree-based boosting algorithm that efficiently handles complex datasets. This study compares the performance of XGBoost with various outlier detection methods, such as LOF, CBLOF, DBSCAN, IF, and K-Means, as well as various other classification algorithms based on machine learning and deep learning. Experimental results show that the combination of GMM and XGBoost provides the best performance with an accuracy of 95.493%, a recall of 91.650%, and an AUC of 95.145%, outperforming other models in the context of credit approval prediction on an imbalanced dataset. The proposed method has been proven to reduce prediction errors and improve the model's reliability in detecting eligible credit applications.

This study is motivated by the status of Surah Yusuf as ahsanul qashash, which has special characteristics in terms of balagah, particularly the use of kinayah to convey sensitive narratives in a polite manner. This study aims to identify the classification of types of kinayah and reveal the pragmatic functions behind their use in the text. The research method used is descriptive qualitative with heuristic-semiotic analysis techniques, where the primary data is sourced directly from the verses of the Qur'an. Surah Yusuf predominantly uses kinayah 'an al-maushuf to refer to certain entities or positions in order to maintain the dignity of the narrative, in addition to the use of kinayah shifah and nisbah to describe the emotional turmoil of the characters. Functionally, this style of language plays the role of ihtiraz (preventive), mubalaghah (emphasis of meaning), and ta'dzim (respect). The implications of this study confirm that the use of kinayah is not merely linguistic aesthetics, but a medium of moral education that promotes polite interpersonal communication and is relevant to contemporary Islamic ethics.

This study aims to describe and analyze the phenomenon of phoneme transfer in Indonesian speech by Makassar speakers in Mangempang Village, Bungaya District, Gowa Regency. It focuses on identifying types of phoneme changes—substitution, omission, and addition—resulting from interference by the Makassar language as the speakers’ mother tongue. This research uses a qualitative descriptive method. The data consist of words or phrases uttered by Makassar speakers when using Indonesian, which reflect phonological variation. Data were collected through observation, recording, and note-taking techniques. Analysis techniques include identification, classification, description, and conclusion drawing. The results show that three types of phonological variation were identified. In terms of substitution, phoneme changes include: /k/ to /s/, /b/ and /k/ to /t/, /i/ to /e/, /l/ to /k/, /f/ to /p/, and diphthongs /ai/ to /e/ and /au/ to /o/. Additions include inserting a glottal stop [?] at word-final positions, adding /n/ and /m/ to form /ng/, and lengthening or emphasizing syllables. Omissions involve abbreviations, dropping certain phonemes, or replacing them with different sounds. These findings illustrate how native language interference affects the phonological structure of Indonesian spoken by the Makassar-speaking community in this region.

The synthetic unit hydrograph methods of Nakayasu, HEC-HMS (Snyder), SCS, ITB-1, and ITB-2 are used to calculate peak discharge and flood hydrograph shape in this Kadumalik Dam study. The maximum daily rainfall data analysis used the Thiessen Polygon and Arithmetic Mean methods. Of these two frequency analysis methods, the Thiessen Polygon method was chosen. Rainfall transformation into runoff using the FJ MOCK and NRECA methods has been applied in the Kadumalik Dam analysis. Compared to NRECA, the FJ MOCK method with the Thiessen Polygon method for frequency rainfall analysis provided a better performance rating with calibration values of 0.911 for R2, 0.627 for NSE, 0.606 for RSR, 18.141 for RMSE, and 30.764 for PBIAS. The validation values were 0.911 for R2, 0.661 for NSE, 0.582 for RSR, 16.086 for RMSE, and 34.420 for PBIAS. The Kadumalik Dam uses a side-channel spillway model with an ogee spillway crest type. Technically, it is planned based on the design flood discharge Q100 and controlled by discharging the flood discharge Q1000 and QPMF. The purpose of this study is to determine the hydraulic flow behavior that occurs in the numerical model based on CFD with ANSYS Fluent and CFX, along with Flow 3D in the diversion, regulation, and launching channels, to obtain the optimum design of the structures, where the flow classification is steady and transient. From the numerical analysis results, it was found that the water velocity streamline in the launch channel for Q100 with steady flow is 0.1644 – 0.2643 m.s-1, for Q1000 it is 0.2176 – 0.2869 m.s-1, and for QPMF it is 0.1592 – 0.2262 m.s-1. For transient flow, the water velocity streamline in the launch channel for Q100 is 0.1555 – 0.2250 m.s-1, for Q1000 it is 0.1541 – 0.2232 m.s-1, and for QPMF it is 0.1559 – 0.2255 m.s-1. Wet, normal, and dry hydraulic conditions are used in the analysis of the Kadumalik Dam operation pattern. The wet hydraulic condition before the reservoir had an average discharge of 25.51 m3/s, and after the reservoir, the average discharge was 26.89 m3/s, an increase of 5.125%. The normal hydraulic condition before the reservoir had an average discharge of 15.54 m3/s, and after the reservoir, the average discharge was 18.75 m3/s, an increase of 17.105%. The dry hydraulic condition before the reservoir had an average discharge of 1.74 m3/s, and after the reservoir, the average discharge was 7.97 m3/s, an increase of 78.157%.

The aim of this research is to determine the magnitude of the influence of Raw Material Inventory Control on Production Results and the influence of the Production Process on Production Results among employees of the Children's Clothing Tailoring Convection in Cimahi. This research is quantitative research using the causality method with a survey approach. The data source used is a primary data source and the data was collected through questionnaires, interviews and observations. In this research, the analytical tool uses multiple linear regression analysis. In the hypothesis testing process, the F test and t test are used. The results of the research show that control of raw material supplies, production processes and production results at the Children's Clothing Tailoring Convection in Cimahi has a very good rating classification. Control of Raw Material Inventory and Production Process simultaneously has a significant effect on the Production Results of the Children's Clothing Tailoring Convection in Cimahi. Partial control of raw material supplies has a significant effect on the production results of the Children's Clothing Tailoring Convection in Cimahi. The partial production process has a significant effect on the production results of the Children's Clothing Tailoring Convection in Cimahi

This study presents the implementation of Transfer learning using the ResNet-18 architecture for classifying 10 musical instrument categories based on visual representations of audio signals. The audio waveform is transformed into image-like inputs appropriate for CNN processing, accompanied by data augmentation and ImageNet-standard normalization. ResNet-18 is utilized due to its efficient feature extraction capability enabled by residual blocks, which help overcome vanishing gradient issues. The model was trained for 10 Epochs using the AdamW optimizer and Cross-Entropy Loss. Experimental results show that the model achieved a maximum validation accuracy of 77.35%, with a stable downward trend in training loss, indicating effective feature learning. However, several misclassification cases were observed, particularly among instruments with similar spectral characteristics, such as drum–violin and tabla–sitar. These findings demonstrate that while ResNet-18 performs reliably for musical instrument classification, further improvements remain possible through deeper architectures like ResNet-50, more comprehensive hyperparameter optimization, and the use of richer audio representations such as Mel-Spectrograms. This research provides an essential foundation for developing automated music analysis systems powered by Deep Learning.

This study aims to find out and analyze the legality of foreign investment registration in the online single submission risk based approach (Oss-RBA) system in Indonesia. This research is a normative research using primary, secondary and tertiary legal materials collected by tracing or searching and documentation studies, the legal materials that have been collected are processed and analyzed in several stages, namely inventory, identification, classification and systematization. The results of the study show that (1) Law Number 25 of 2007 concerning investment has been in compliance with TRIMs. (2) Foreign investment business licenses in the Oss-RBA system are not considered to violate TRIM's because they are not regulated in the illustration of the violation of the TRIM's agreement.     

The State, as the supreme authority over land, water, and outer space, including the natural resources within, holds the highest level of power as an entity representing the entire population. This authority includes the regulation, utilization, use, and maintenance of these resources, as well as defining the legal relationships between individuals and these resources. The primary goal of this authority is to achieve the greatest welfare for the people and to promote justice, well-being, and freedom within a society based on the principles of an independent, sovereign, just, and prosperous Indonesian legal state. In the context of Indonesian agrarian law, land is considered a part of the earth's surface and is governed by Law No. 5 of 1960 on Basic Agrarian Principles (UUPA). Land rights, such as Ownership Rights and Building Use Rights (HGB), play a crucial role in land management and use, including as collateral for credit. Mortgage Rights, regulated by Law No. 4 of 1996, provide security over land and related objects, with the right holder entitled to sell the property through public auction if the debtor fails to meet their obligations. The importance of land registration and ownership rights is regulated by Government Regulation No. 24 of 1997, which ensures legal certainty for land and property owners. Creditors, including banks, play a critical role in the economy by providing credit facilities, where collateral on land and buildings is a key aspect to ensure the security of repayment and the legal validity of transactions. The classification of creditors as separatis, preferen, and konkuren facilitates the execution of mortgage rights in the event of contract breaches, thereby providing the necessary legal protection for lenders.

The detection of computer network attacks is becoming increasingly important as the complexity and frequency of cyber-attacks threatening information systems and network infrastructure continue to rise. These attacks may lead to severe consequences, including data breaches, service disruptions, and financial losses. To address these challenges, artificial intelligence techniques have become a major focus in the development of more effective, adaptive, and reliable intrusion detection systems. Among various classification algorithms, the C4.5 decision tree has demonstrated strong performance due to its simplicity, interpretability, and high classification accuracy. This study aims to apply the C4.5 algorithm for network attack detection using a comprehensive dataset that includes multiple categories of attacks and normal network activities. The proposed methodology consists of several stages, including data preprocessing, feature selection, decision tree model construction, and performance evaluation using standard metrics such as accuracy, precision, recall, and F1-score. Data preprocessing is performed to handle missing values, normalize data, and reduce noise, thereby improving the overall quality of the dataset and enhancing classification results. The experimental results indicate that the C4.5 decision tree algorithm effectively classifies network traffic into attack and normal categories with a satisfactory level of accuracy. The model successfully identifies attack-related patterns and highlights significant features that influence detection performance. Further analysis reveals that appropriate feature selection and parameter tuning significantly contribute to improving model reliability and robustness. This research provides a valuable contribution to the development of efficient, accurate, and practical network intrusion detection systems. The proposed approach is expected to strengthen information security frameworks and support proactive defense strategies against increasingly sophisticated cyber threats, thereby enhancing the protection of critical network infrastructures.

Image classification is widely used in everyday life such as in car steering, closed-circuit television (CCTV), traffic cameras, etc. The implementation of image classification can be done using several methods, including neural network and support vector machine models. The neural network method is able to find the right weights that allow the network to show the desired behaviour while the support vector machine method has many dimensions and can overcome linear and non-linear data. In this research, feature extraction was carried out using VGG16 to increase accuracy. This research aims to find out how to implement the neural network and SVM algorithms to classify images and determine the results of analyzing the performance of the two methods. The data used in this study is secondary data consisting of 10 types of large wild cats with a total of 2339 training image datasets and 50 testing image datasets. The research stages consist of data augmentation, model design, model training, and model evaluation. Classification with the neural network model produced an accuracy of 96% and the support vector machine model produced an accuracy of 96%, which means that in a consistent training environment, the two models have the same performance.

Admission of new students to an educational institution is an activity that is always carried out every new academic year, where prospective new students always increase from year to year (Muwardah and Pramunendar, 2015). Admission of students can be held from elementary to middle school, from middle school to high school / vocational school. The focus of this research is the registration of new students at SMK. As is known, SMK is a Vocational High School or abbreviated as (SMK) and where there are many majors provided which ultimately makes prospective new students confused about which major is right for them because will take a long time.. Based on C4.5 as a Classification Algorithm: C4.5 is a popular algorithm for building decision trees. It works by dividing a dataset into smaller subsets based on attribute values, thus forming an easy-to-understand tree structure. Classification results using decision trees provide a clear visualization of the decision-making process and the variables that contribute to student choices.

Achieving financial stability for the family is a goal that everyone has. The family is the most significant foundation for the growth of human life in Indonesia. The first and most important living environment where the personality that shapes a person's life is created is the family. The development of moral values, social justice, humanity, and religion is essentially a process decided by the family. The family is the first and main social structure that plays an important role in providing life values ​​to children who are growing and developing so that they can find purpose in their life journey. The classification of family welfare according to population data owned by the village government is the aim of this study. Based on the results of the study, fuzzy logic and the Tahani model can be used to process population data according to the level of family welfare, resulting in output in the form of family classifications such as prosperous, poor, and underprivileged families. To assess the effectiveness of incorporating fuzzy logic into the program being developed, the fuzzyTECH application is also used to test the program subdistrict.    

This study aims to determine the effect of commitment and organizational culture on employee engagement at DC Yogya Group Cikoneng Branch, Tasikmalaya. The method used is a case study, data obtained through questionnaires to the number of employees working at DC Yogya Group Cikoneng Branch. Sampling using saturated sample technique and the method of analysis used is multiple linear regression analysis method. From the results of the study indicate that commitment, organizational culture and employee engagement are included in the low classification. Simultaneously commitment and organizational culture have a significant effect on employee engagement at DC Yogya Group Cikoneng Branch. Partially, the commitment variable has a significant effect on employee engagement at the DC Yogya Group Cikoneng Branch, and the organizational culture variable has a significant effect on employee engagement at the DC Yogya Group Cikoneng Branch.  

The development of the times is accompanied by progress in various fields of life, such as science, technology, and economics. Progress is also felt in the scientific field of journalism. One of the terms in the field of journalism that is commonly known by the general public is print mass media, such as newspapers. Today's newspapers are not only printed on paper, but many newspapers have created their own blogs or pages so that news can be read online. The aim of this research is to analyze language errors based on the classification of linguistic categories, namely syntax, which includes the areas of spelling and sentence effectiveness. The data source is several news stories published on the detikNews website in the February 2024 edition. The data was then analyzed using the listening method and note-taking techniques. The results of the research showed that there were 52 errors in the use of spelling and punctuation, which were described as follows: a) there were 11 errors in writing foreign words; b) there were 8 errors in writing numbers; c) there were 13 errors in writing capital letters; d) there were 15 errors in the use of punctuation marks; e) there were 5 errors in writing pronouns. Apart from that, there were 44 errors in the use of ineffective sentences, which are described as follows: a) there were 14 errors in choosing diction; b) there are 10 sentences with no subject or predicate; c) there are 9 sentences with overlapping words; d) there are 11 long-winded sentences. It is hoped that the results of the analysis in this article will increase understanding and deeper knowledge regarding linguistics, namely syntax, including the areas of spelling and word choice and their use, knowledge about the types, as well as providing suitable teaching materials for class X high school students for them to carry out assessments and considerations. about adolescent social behavior critically.

For students, Dasar Elementary School offers a formal education pathway. Mengubah pemahaman siswa terhadap materi pembelajaran is quite important in the learning process. Perlu dicapainya, siswa atau didik adalah fungsi dari adanya seorang pendidik.This is due to the fact that in the process of teaching mathematics, understanding concepts is a foundation that is extremely important for making decisions on the solution of mathematical problems as well as daily problems. Due to a few factors that make it difficult for students to understand math lessons, they find it difficult to understand or even understand them at all. To achieve the maximum learning outcomes, education must be provided by qualified teachers. One of the most important educational resources for achieving the highest learning outcomes is a teacher. A teacher is one of the most important educational resources; learning will be more enjoyable if the teacher can implement a flexible learning model. In addition, teachers are expected to be constantly creative in their approach to teaching. Due to this, a system is required to determine the student's level of proficiency in comparison to the advanced learning environment in order to assess student learning. The collected data from the survey will be divided into two categories: training data and testing data. The model's training data results will be used to assess the accuracy of the data testing. The classification results indicate that the Naïve Bayes algorithm is a good choice for reducing student anxiety levels in foreign language learning, with a remarkably high accuracy rate of 95.24%.