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Flower disease detection is a common challenge in modern agriculture. Various factors, such as changes in leaf color, shape, petal structure, and environmental conditions, make it difficult to achieve high accuracy with conventional models. Transfer learning is an effective solution to improve model performance in image detection, especially when available data is limited. This study used several pre-trained models, namely VGG16, ResNet50, and EfficientNet-B0, to detect three types of flower diseases: black spot on roses, white powdery mildew, and leaf rust. The process included data processing, increasing the data volume, model training, and result verification. The results showed that the EfficientNet-B0 model provided the highest accuracy of 97.2%, significantly better than the CNN model created from scratch with an accuracy of 85.1%. This study proves that the transfer learning method is very effective in improving the accuracy of flower disease detection. These results confirm that transfer learning is effective for detecting plant diseases with higher accuracy, especially when the dataset is limited.  

Objective– This article aims to comprehensively examine the main types of food crop pests and their attack patterns through a systematic literature review approach. The research focuses on the dynamics of pest attacks, changes in ecological patterns due to climate change, and advances in modern identification technology that enable more accurate early detection. This study also highlights the significance of new paradigms of pest identification based on artificial intelligence (AI), genomics, and landscape mapping in supporting food security at the regional and national levels. Design/methodology/approach– This study used the Systematic Literature Review (SLR) method for scientific publications from 2015–2025 from reputable sources such as Scopus, Web of Science, PubMed, ScienceDirect, SpringerLink, Taylor & Francis, Wiley, AGRIS, and Google Scholar. Of the 326 articles identified in the initial stage, 30 articles in English and Indonesian were selected through a screening process based on strict inclusion–exclusion criteria. All articles were then analyzed using thematic coding techniques to produce an in-depth, evidence-based synthesis. Findings– The study produced four key findings: (1) there are five dominant pests in global food crops, namely Thrips tabaci, Spodoptera exigua/frugiperda, Helicoverpa armigera, Nilaparvata lugens and Sitophilus oryzae; (2) attack patterns are strongly influenced by temperature, humidity, pesticide resistance, and monoculture; (3) modern identification technology AI, drone imagery, multispectral sensors, and DNA Barcoding have increased detection accuracy to 94–98%; and (4) community-based early warning systems accelerate field response and reduce the risk of crop failure. Practical implications– These findings provide a scientific basis for local governments, agricultural extension workers, and farmers to gradually adopt pest identification technology and strengthen integrated monitoring systems at a regional scale. Authenticity/value– This article offers a new conceptual model of “Pest Identification Pyramid – Attack Pattern – Early Warning System” that integrates pest biology, digital technology, and community response to improve national food security.

This study aims to determine and describe the transparency of service procedures, the ease of procedures, and the ease of obtaining information at the Kota Timur District Office in Gorontalo City. Using a qualitative, descriptive approach through observation, interviews, and documentation, the study results indicate that transparency of service procedures has been effectively implemented through the provision of clear, complete, and easily accessible information to the public. Information regarding service types, requirements, completion times, and fees is published through bulletin boards, brochures, social media, and direct explanations from officers, so that the public can understand the service process without confusion. In terms of ease of procedures, the service flow has been designed to be simple, concise, and user-friendly, ensuring ease of access for service applicants and even for vulnerable groups such as the elderly. Furthermore, the ease of access to information is also evident in the use of various communication channels, both in person and digitally. Information boards, leaflets, social media, and digital displays are actively used to disseminate information so that the public can understand procedures before visiting the office and better prepare documents. Overall, these three indicators demonstrate that the Kota Timur District Office is committed to implementing the principle of transparency in public services, although further innovation is needed to ensure information reaches a wider and more equitable public.

In general, school students buy snacks in the school canteen or street vendors (PKL) around the school. 2 The types of food sold are varied, ranging from healthy snacks to unhealthy snacks so that they can attract students to consume school snacks. Healthy snacks are foods that have sufficient and balanced nutrition and do not contain (contaminated) elements that can harm or damage health. This community service activity aims to educate healthy eating patterns to prevent food and drinks containing microbial contamination at Mariana Catholic High School, Medan. The method used is an educational approach through health counseling, interactive discussions, and demonstrations of hygienic practices, especially correct handwashing techniques and the importance of maintaining personal hygiene and the school environment. This activity was attended by 40 students as participants. The evaluation of the activity focused on one main indicator, namely student participation in hygienic behavior practices as a form of direct application of the material that has been given. The results of the activity showed that all participants (100%) followed the demonstrated hygienic practices, which indicates a very high level of participation and enthusiasm. These findings indicate that educational methods accompanied by hands-on practice are effective in increasing understanding and encouraging the adoption of clean and healthy living behaviors. Community service activities at Mariana Catholic High School in Medan have been shown to increase students' knowledge about the dangers of microbial contamination and the development of hygienic behaviors in daily life. Structured and ongoing education is an effective preventive measure to create a healthy and clean school environment.

This Community Service Program (PKM) was conducted with the primary objective of enhancing understanding, awareness, and skills among youth in Parangloe District in preventing drug abuse. Drug abuse has become one of the greatest threats to the development of young generations in Indonesia, including in Parangloe District, which has begun to show indicators of increasing risk. This activity focused on education-based prevention efforts and youth empowerment through a peer educator approach, whereby youth were trained to become agents capable of disseminating information and positive influence within their communities. The program was implemented through a series of socialization sessions, seminars, interactive discussions, and peer youth training. The materials provided covered understanding various types of drugs, causal factors of abuse, health impacts, social and legal consequences, and prevention strategies applicable at the family, school, and community levels. The results demonstrated increased participant knowledge, formation of Peer Youth Groups Concerned with Anti-Drug Efforts, and growing commitment to undertake sustainable prevention measures. This PKM activity had a significant impact on strengthening social resilience in Parangloe District and building an active role for youth as pioneers of the anti-drug movement.

Syphilis is one of the reproductive health problems that remains a challenge in Indonesia, with a trend of increasing cases, while the level of adolescent knowledge about this disease is still low. Educational efforts are needed to improve adolescent understanding, one of which is through video media which is considered more interesting because it combines visual and audio elements. This study aims to evaluate the effectiveness of video as an educational medium in improving adolescent knowledge about syphilis at SMKS Al Hikmah 2 Sirampog, Brebes Regency. This type of research is a pre-experimental study with a one group pretest-posttest design. The study sample consisted of 47 students selected using a purposive sampling technique. The research instrument was a syphilis knowledge questionnaire administered before and after the educational video intervention. Data analysis used the Wilcoxon Signed Rank Test and N-Gain calculation. The study showed that Results Before the intervention, the level of knowledge of respondents was in the good category for 24 students (51.1%), sufficient for 11 students (25.5%), and poor for 12 students (23.4%). After being given the educational video intervention, there was a significant increase with all respondents (100%) being in the good category. The Wilcoxon Signed Rank Test showed a significant difference between pretest and posttest scores (p-value = 0.000). N-Gain analysis categorized the increase in knowledge as high. The study concluded that video media has proven effective as an educational tool in increasing adolescent knowledge about syphilis, making it a viable alternative learning medium in reproductive health programs.

Gastric disease is a common health problem that can disrupt daily activities if not properly treated. To aid the initial diagnosis process, this study developed a web-based expert system capable of diagnosing various types of gastric disease based on the symptoms experienced by the user. This system uses the Dempster-Shafer method to address uncertainty in decision-making by combining a number of pieces of evidence in the form of symptoms to determine the level of confidence in a disease. The system was developed using the PHP programming language and a MySQL database and designed for easy browser access. Testing demonstrated that the system was able to provide fairly accurate diagnostic results that closely approximated the results of consultations with medical professionals. This system is expected to become an initial solution for the public in quickly and independently recognizing symptoms of gastric disease.  

The Qur’an and Hadith, as the primary sources of Islamic teachings, provide a comprehensive value framework regarding the ideal character that should be possessed by both educators and learners. Educators are required to demonstrate sincerity, patience, justice, noble character, and to serve as role models (uswah hasanah) for their students. Education is a fundamental pillar in the formation of individual character and personality. This study aims to examine and analyze the concepts of attitudes and personality of educators and learners based on the Qur’an and Hadith. The method employed is a literature review using a qualitative approach through the analysis of relevant Qur’anic verses and Prophetic traditions. The results of the study indicate that learners are individuals who strive to develop their potential through the learning process within educational pathways, both formal and non-formal, at certain levels and types of education. Among the ethics of learners toward educators are sitting politely in front of the teacher, speaking respectfully, not interrupting the teacher while speaking, listening attentively to the teacher’s explanations, asking questions gently and respectfully when something is not understood, attending school regularly, avoiding truancy and lateness without valid reasons, entering the classroom promptly before the teacher arrives, and obeying the teacher’s advice.

Podcasts as digital communication media have continued to grow and have become an important platform for delivering ideas, opinions, and public education. This study aims to analyze locutionary, illocutionary, and perlocutionary speech acts in the YouTube content Podcast Warung Kopi (PWK) entitled “Mental Dr. Tirta Turun, Gara-Gara Video Marah-Marah Dilihat dan Ditiru Sama Anaknya.” This research employs a descriptive qualitative method using listening and note-taking techniques to examine the utterances produced by the host and the guest speaker. The data consist of transcribed conversations that are classified based on Austin’s speech act theory. The findings reveal 17 speech act data, consisting of 4 locutionary acts, 9 illocutionary acts including assertive, directive, expressive, and commissive types, and 4 perlocutionary acts. These results indicate that podcasts function not only as entertainment and information media but also as effective tools in influencing listeners’ attitudes, raising awareness, and shaping behavioral responses, particularly in relation to health and social issues.

Pepper is currently not only used to meet daily needs but also as an export commodity. Indonesian pepper exports generate foreign exchange for the country. Currently, international competition for pepper exports is increasingly fierce. An evaluation of the level of market competition and the structure of the pepper market at the international level is necessary. The methods used to analyze the level of competition concentration and market structure are the Concentration Ratio of Biggest Four (CR4) and the Herfindahl-Hirschman Index (HHI). The types of pepper discussed in this study are white pepper with HS code 090411 and black pepper with HS code 090412. The results obtained indicate that both black and white pepper tend to be in an oligopoly market structure with a relatively high level of competition. Such market conditions are a distinct advantage for Indonesia, as there are not too many competitors while buyers or enthusiasts are quite high. A striking difference occurs in the international black pepper trade. In the black pepper trade, Indonesia is not classified as a country with the largest market share.

Private vehicles are a frequently used mode of transportation because they are considered more practical. However, using private vehicles carries several risks, such as traffic accidents due to drivers losing focus on the road due to other activities, such as making calls on smartphones, drinking, or operating the radio. Approximately 90% of accidents are caused by human error. Convolutional Neural Network (CNN) is a type of neural network commonly used on image data. CNN is often used for image classification due to its high performance and accuracy. Therefore, this study aims to analyze the performance of CNN for the classification of distracted driving activities. The results show that the CNN model is able to effectively classify images of distracted driving activities, with an accuracy of approximately 99% across all datasets and across all input image size variations. Furthermore, the results of this study also show that differences in right-hand and left-hand drive datasets do not significantly affect model accuracy. Variations in input image size also do not significantly affect model accuracy, but do affect the training duration.

The attendance recording system at PLN ULP Tanjungbalai still relies on manual, paper-based methods, resulting in delays in data recap, reduced efficiency, and a high potential for recording errors. This condition affects the accuracy of employee attendance information, which is essential for administrative activities and managerial decision-making. Based on these issues, this practical work aims to design and develop a web-based e-attendance application as a solution to enhance efficiency, processing speed, and the accuracy of attendance recapitulation. The system was developed using PHP as the programming language and MySQL as the database management system, following several stages including requirement analysis, system design using UML, and implementation of a web-based user interface. The application provides essential features such as user login, daily attendance recording, employee data management, attendance notes (permission, sickness, etc.), and automatic attendance report generation. The system is designed for two types of users—Admin and Employees—each with specific access rights. The implementation results indicate that the e-attendance application significantly improves the efficiency of attendance administration at PLN ULP Tanjungbalai. Data collection and recapitulation become faster, more structured, and less prone to errors, while also enabling administrators to monitor employee attendance in real time. Therefore, this web-based e-attendance application serves as an effective solution to support operational activities and enhance the quality of employee attendance management.

Measurement learning is a fundamental and applicable mathematical topic in everyday life, but it often causes learning difficulties for students, especially in understanding the meaning of units, relationships between quantities, and the conceptual measurement process. These difficulties are not only caused by students' limited cognitive abilities, but also by learning designs that do not fully facilitate social interaction and student learning development. This study aims to reconstruct the contextual didactic design in measurement learning by reviewing the role of social interaction and the Zone of Proximal Development (ZPD) in the student learning process. This study uses a qualitative approach with the type of Didactic Design Research (DDR). The research stages include analysis of the initial didactic situation to identify student learning barriers, implementation of contextual didactic design in measurement learning, and retrospective analysis of student responses as a basis for reconstructing the didactic design. Data were collected through learning observations, analysis of student work results, interviews, and learning documentation. Data analysis was carried out qualitatively by examining social interaction patterns, forms of scaffolding, and student movements in the Zone of Proximal Development. The results of this study indicate that understanding of measurement concepts develops through social interactions between students and between students and teachers within a meaningful learning context. Social interactions and scaffolding provided gradually can encourage students to move from actual abilities to potential abilities within the Zone of Proximal Development. Retrospective analysis indicates that reconstruction of the didactic design is necessary to refine the learning context, activity sequence, and scaffolding strategies to better align with students' learning characteristics. The reconstruction of the didactic design can reduce learning barriers and improve the quality of students' conceptual understanding in measurement learning. This research provides theoretical contributions to the study of social constructivism-based mathematics education and provides practical implications for teachers in designing measurement learning that is more responsive to social interactions and student learning development.

This article examines the typology and classification of regional government apparatus in Indonesia by analyzing their structure and functions within local governance. The study draws on recent theoretical literature (2020–2025) and legal frameworks to map how different types of regional apparatus such as executive agencies (“dinas”), supporting agencies (“badan daerah”), secretariat, inspectorate, and territorial units are organized and classified. Using a normative-juridical and conceptual approach, the paper reviews relevant laws, regulations, and academic studies to identify patterns of structural typology and functional differentiation within local governments. The findings reveal that many local governments still apply structural-heavy models rather than functionally tailored organizations, leading to excessive bureaucracy and inefficiency. The analysis suggests that a clearer classification aligned with functional roles can improve governance effectiveness and administrative efficiency. The article concludes by recommending that local governments re-evaluate their organizational structures to better reflect the functional needs of governance, rather than merely replicate structural models.                                                               

A wall follower robot is a type of autonomous robot that is designed to move by following a wall at a certain distance. This research aims to design and build a Wall follower robot equipped with a Fuzzy-PID control system to improve navigation performance. The robot uses five HC-SR04 ultrasonic sensors to detect the distance to the wall and the surrounding obstacles. The data from the sensor is then processed by a Fuzzy-PID algorithm that combines the advantages of conventional PID control with fuzzy logic, resulting in a more adaptive response to environmental conditions. The test results showed that the robot with Fuzzy-PID control was able to maintain the stability of the distance to the wall more consistently compared to the pure PID control. In addition, the system exhibits better adaptability to complex environmental conditions, such as sharp turns, uneven wall surfaces, and the presence of resistance variations. The application of Fuzzy-PID control has been shown to improve the stability, response speed, and accuracy of the robot's navigation. These findings are expected to contribute to the development of robotic navigation systems for a wide range of practical applications, including automated cleaning robots, environmental exploration, and industrial systems that require reliable autonomous mobility.

Social loans are an important tool for developing local economies, especially in remote areas such as rural areas. The Indonesian Village City Savings and Loan Cooperative (KSU) is one of the business entities that provides loan capital to its members. The purpose of this study is to determine the mechanism of social loan agreements in the Multipurpose Cooperative (KSU) of the Indonesian Village City and to determine the perspective of Islamic Economic Law on loan agreements in the Multipurpose Cooperative (KSU) of the Indonesian Village City. This research method uses a descriptive research type with a qualitative approach. Data collection was carried out through observation and interviews with the Management and members of the Savings and Loan Cooperative (KSU) of the Indonesian City Village. The results of the study show that first, the loan application procedure involves several steps such as becoming a member, filling out forms, completing documents and the approval stage. The maximum loan provision is 80% of the savings balance with a loan tenor of 12 months and 18 months. The payment system is made in installments through salary deductions and is subject to a 5% interest. For borrowing members who are late, there are no sanctions or fines but there is a time dispensation. Second, the loan application and management mechanism at the Multipurpose Cooperative has met sharia principles through transparent and structured governance, such as deductions from salary installments and a guarantee policy provided in the form of the amount of member savings balances. However, social loans at the Multipurpose Cooperative contain an element of benefit (profit) of 5%, which according to some scholars can be classified as usury because of the addition of value to the principal loan, even though the benefit is returned to members through the Business Result Remainder (SHU).

The purpose of this study is to analyze the settlement of criminal cases on the liability of parents for negligence that results in minors becoming perpetrators of traffic accidents. This type of research is normative legal research with a statutory approach, a case approach and a conceptual approach. The analysis used in this study is a descriptive analysis. has not explicitly regulated the criminal liability of parents for accidents committed by children, although Civil Code Article 1367 has provided a basis for civil liability, and the new Criminal Code through Article 37 opens up opportunities for the application of the principle of vicarious liability. This study recommends the need to reconstruct the Indonesian criminal law regulation which explicitly establishes a model of parental criminal responsibility based on the principle of vicarious liability and the principle of Radbruch legal certainty, without overriding the principle of child protection in the SPPA Law.

The rapid development of digital streaming platforms such as Netflix has generated a large volume of content data with diverse characteristics, thereby requiring effective analytical methods to understand emerging patterns and trends. This study aims to classify Netflix content into two main categories, namely movies and television shows, and to analyze genre trends and content characteristics using a data mining approach with the Naive Bayes algorithm. The dataset used in this study is the Netflix Shows dataset, consisting of 8,809 content entries, with the primary features analyzed including genre, rating, and country of production. The research process begins with data exploration and preprocessing stages, including data cleaning, handling missing values, and transforming categorical features to enable effective model construction. Subsequently, the dataset is divided into training and testing sets to objectively and systematically build and evaluate the Naive Bayes classification model. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics to assess the model’s ability to accurately distinguish between Netflix content types. The experimental results demonstrate that the Naive Bayes algorithm is able to classify Netflix content into Movie and TV Show categories with accuracy, precision, recall, and F1-score values of 100%, respectively. The confusion matrix indicates that no misclassification occurred, suggesting that genre, rating, and country of production features provide a very clear separation between content classes. These findings indicate that the Naive Bayes algorithm can achieve exceptionally high classification performance with optimal evaluation results. The results further reveal distinct differences in characteristics between movies and television shows based on genre and production attributes. Therefore, this study is expected to contribute to the development of content recommendation systems and strategic content management within the streaming industry.

Flower disease detection is a significant challenge in modern agriculture, particularly with factors such as changes in leaf color, petal shape and structure, and environmental conditions affecting the accuracy of conventional models. These factors make it difficult to achieve optimal results using traditional methods. Transfer learning is an effective solution to improve image detection performance, especially when data is limited. This study used several pre-trained models, namely VGG16, ResNet50, and EfficientNet-B0, to detect three types of flower diseases: black spot on roses, white powdery mildew, and leaf rust. The research process included data processing, increasing the data volume using augmentation techniques, model training, and evaluation of the results. Experimental results showed that the EfficientNet-B0 model produced the highest accuracy of 97.2%, significantly better than the CNN model built from scratch with an accuracy of 85.1%. This study demonstrates that transfer learning is highly effective in improving the accuracy of flower disease detection, making it a more reliable alternative to methods that do not utilize pre-trained models, especially for agricultural applications that require high levels of accuracy in disease detection.

ABSTRACT Background: Pregnancy complications are one of the causes of morbidity and mortality in women. Data from the 2017 Indonesian Demographic and Health Survey (SDKI) showed that 28% of pregnant women in Indonesia are at risk of experiencing complications during pregnancy. Preeclampsia is a condition characterized by the onset of hypertension followed by organ dysfunction either with or without proteinuria at a gestational age above 20 weeks. Objective: The purpose of this study was to determine the characteristics and outcomes of neonates born to mothers with preeclampsia. Method: This type of research is a quantitative descriptive study using secondary data and using a total sampling of 261 medical records. Results: The results of the study were as follows: preeclampsia occurs mostly in young adults 73.95%, Primigravida 60.15%, Islam 50.50%, working mothers 62.45%, secondary education 80.07%, and first marital status 76.62%. The description of neonatal outcomes in mothers giving birth with preeclampsia was obtained with neonatal outcomes in good condition, namely 47.14% born at term gestational age with 43.67% non-LBW conditions, experiencing asphyxia 37.94% and being treated without respiratory support 65.52%. Conclusion: the outcomes of neonates born to mothers with preeclampsia quite often experience asphyxia. Early detection, prevention and treatment of complications, especially in cases of preeclampsia, are necessary so that neonatal outcomes can be maintained without complications and produce a good level of health for both mothers giving birth and newborns.