Publication Search

This study aims to analyze the effect of cutting parameters on surface roughness in the turning process of AISI 1045 steel. The investigated parameters include cutting speed, feed rate, and depth of cut. A quantitative approach was employed using multiple linear regression analysis with SPSS software. The dataset consisted of 30 simulated experimental observations with varying cutting parameter conditions. Prior to regression analysis, classical assumption tests including normality, multicollinearity, and heteroscedasticity tests were conducted to ensure the validity of the model. The results indicated that all assumptions were satisfied. The findings reveal that simultaneously, all independent variables have a significant effect on surface roughness with a coefficient of determination of 82.1%. Partially, Feed rate and cutting speed significantly influence surface roughness, while depth of cut does not show a significant effect. Feed rate is identified as the most dominant variable affecting surface roughness, where an increase in Feed rate leads to higher roughness values. In contrast, increasing cutting speed tends to reduce surface roughness. This study highlights the importance of controlling cutting parameters, particularly Feed rate and cutting speed, to improve machining quality. The results provide practical implications for manufacturing industries in optimizing machining parameters to achieve better surface quality and process efficiency.

This research is motivated by the low critical thinking skills of third-grade students in learning Pancasila symbols and the limited use of interesting, interactive learning media in the classroom. The purpose of this study is to develop the Magic Letter Spinwheel learning media, determine its feasibility, and examine the improvement of students’ critical thinking skills after using the media. This study employed a Research and Development (R&D) method with the ADDIE development model, consisting of Analysis, Design, Development, Implementation, and Evaluation stages. The research subjects were third-grade students of SDN Sumber 02, Blitar Regency. Data were collected through observation, interviews, validation questionnaires from media and material experts, as well as pretests and posttests. The data were analyzed descriptively using qualitative and quantitative approaches, including feasibility percentages and the N-Gain test. The development results show that the Magic Letter Spinwheel is an interactive learning medium in the form of a spinning wheel containing Pancasila symbols, questions, and learning activities that encourage students to think critically. This medium is designed with an attractive display and is supported by light features and an automatic rotation button to increase students’ learning interest. Based on expert validation, the media is declared feasible for classroom use. The implementation of the Magic Letter Spinwheel can improve students’ critical thinking skills through active, enjoyable, and student-centered learning activities. Therefore, this media is suitable for use in Pancasila Education learning to support the development of critical thinking skills among third-grade elementary school students.

Balanced nutrition intake is an important factor in supporting the performance of young athletes, especially during the growth period that requires optimal nutrition for intense physical activity. However, the lack of nutritional knowledge among parents of young athletes often leads to nutritional imbalances that have a negative impact on athlete health and performance. This study aims to measure the effect of balanced nutrition education on improving the knowledge and attitudes of parents of athletes at the Kancil Mas Football School (SSB), Karawang. The method used was a quasi-experiment with a pre-test and post-test design involving 20 respondents who were parents of U-13 athletes. Education was provided in the form of direct counseling sessions and group discussions, which were supplemented with supporting materials such as leaflets. The Wilcoxon signed rank test was used to analyze changes in parental knowledge and attitude scores before and after the intervention. The results of the analysis showed a significant increase in parents' understanding and positive attitudes towards balanced nutrition after education (p < 0.05). The results showed a significant increase in the level of parents' understanding and positive attitudes towards nutrition after the education intervention. These findings highlight the importance of active parental involvement in ensuring that young athletes' nutritional needs are met, as well as providing a basis for developing nutrition education programs in other sports schools.

Cutaneous fungal infections caused by Malassezia furfur remain a significant health concern in tropical regions, highlighting the need for safe and effective alternative therapies. Moringa oleifera L. leaves are reported to contain various secondary metabolites, including flavonoids, tannins, and saponins, which exhibit potential antifungal activity. This study aimed to develop a topical suspension formulation of Moringa oleifera leaf extract and to evaluate the effect of varying extract concentrations on the physical characteristics of the preparation. An experimental method was employed using four formulations: F0 as the control, and F1, F2, and F3 containing 9%, 10%, and 11% extract, respectively. Evaluation parameters included organoleptic properties, homogeneity, pH, viscosity, and adhesiveness, as well as stability testing using a cycling test method for 12 days. The results demonstrated that all formulations exhibited good organoleptic characteristics, homogeneity, and viscosity. The pH values remained within the acceptable range for skin preparations, although slight fluctuations were observed during storage. Adhesiveness also showed variations across several testing cycles. Overall, the formulations met acceptable physical quality criteria and demonstrated potential for further development as topical suspensions; however, formulation optimization is still required to enhance stability during storage.

Cutaneous fungal infections caused by Malassezia furfur remain a significant health concern in tropical regions, highlighting the need for safe and effective alternative therapies. Moringa oleifera L. leaves are reported to contain various secondary metabolites, including flavonoids, tannins, and saponins, which exhibit potential antifungal activity. This study aimed to develop a topical suspension formulation of Moringa oleifera leaf extract and to evaluate the effect of varying extract concentrations on the physical characteristics of the preparation. An experimental method was employed using four formulations: F0 as the control, and F1, F2, and F3 containing 9%, 10%, and 11% extract, respectively. Evaluation parameters included organoleptic properties, homogeneity, pH, viscosity, and adhesiveness, as well as stability testing using a cycling test method for 12 days. The results demonstrated that all formulations exhibited good organoleptic characteristics, homogeneity, and viscosity. The pH values remained within the acceptable range for skin preparations, although slight fluctuations were observed during storage. Adhesiveness also showed variations across several testing cycles. Overall, the formulations met acceptable physical quality criteria and demonstrated potential for further development as topical suspensions; however, formulation optimization is still required to enhance stability during storage.

Stress in older adults needs attention because it can negatively affect physical, emotional, and social well-being, as well as overall quality of life. Elderly individuals living in social welfare institutions are particularly vulnerable to stress due to environmental changes, limited family involvement, loneliness, daily routines, and reduced independence. This study aimed to determine the effect of art painting group activity therapy on stress levels among older adults at Budi Mulia 2 Cengkareng Social Welfare Home. A quantitative pre-experimental study with a one-group pretest-posttest design was conducted involving 33 participants selected through total sampling. Stress levels were measured using the DASS-21 stress subscale. The intervention consisted of four art painting sessions lasting 30–45 minutes each. Data were analyzed using the Wilcoxon test. The mean stress score decreased from 22.18 before the intervention to 15.94 after the intervention. The Wilcoxon test showed a significant difference (p = 0.000), indicating that art painting group activity therapy effectively reduced stress levels among older adults.

This study examines the influence of interest rates and the rupiah exchange rate on the money supply in Indonesia during the 2023–2025 period. A quantitative research approach was employed using monthly secondary data obtained from Statistics Indonesia (BPS) and Bank Indonesia (BI). The data were analyzed through multiple linear regression with the assistance of SPSS software. Several statistical procedures were applied, including classical assumption tests, partial significance tests (t-tests), simultaneous significance tests (F-tests), and coefficient of determination (R²) analysis. The findings reveal that interest rates have a significant negative effect on the money supply, while the rupiah exchange rate exerts a significant positive influence. Furthermore, the simultaneous test indicates that both variables collectively have a significant impact on the money supply. The coefficient of determination shows that 85.4% of the variation in the money supply can be explained by changes in interest rates and the rupiah exchange rate. These results highlight the importance of maintaining stable interest rates and exchange rates as essential components of monetary policy aimed at regulating the money supply and preserving monetary stability in Indonesia.

This study designs and implements an up-down counter system based on an AT89C2051 microcontroller programmed in assembly using the MC-51 application. The system modifies an existing digital clock board by mapping the display selector pins, seven-segment segment pins, pushbuttons, and buzzer to the microcontroller ports. The research method consists of literature review, hardware identification, algorithm design, assembly programming, program downloading, and functional testing using a 5 V DC supply. The implementation uses a four-digit common-cathode seven-segment display and a multiplexing routine to show the counter value in real time. The functional test shows that the system can display the initial value, increase the value through the up button, and decrease the value through the down button. The display is readable during operation, and the program can run on the target circuit after being downloaded to the AT89C2051. This study confirms that assembly programming on MC-51 can be applied to implement a simple counter system on a reused digital clock circuit. The main limitations are the absence of explicit button debouncing, overflow and underflow protection, quantitative response-time measurement, and non-volatile data retention.

Python programming has become a fundamental competence in the digital era, yet students often struggle to transform algorithmic logic into functional code. This gap between conceptual understanding and practical implementation skills requires a thorough investigation into learning challenges within the Industrial Informatics Engineering Technology (TRIN) program at Politeknik Manufaktur Bandung. Grounded in Bloom's Revised Taxonomy and Cognitive Load Theory, this descriptive quantitative study utilized a Likert-scale questionnaire and an objective comprehension test administered to 87 third-year students. Data were analyzed using descriptive statistics to map performance across three aspects: conceptual understanding, syntactic comprehension, and implementation ability. Results indicate the conceptual aspect achieved the highest average of 4.15, followed by syntax at 3.56 and implementation at 3.54, with objective test accuracy rates of 76.09%, 65.52%, and 67.36%, respectively. Major obstacles identified include difficulties with looping, debugging, and comparison operators. Therefore, enhanced structured practice and Project-Based Learning approaches are recommended to strengthen students' implementation competencies.

The thesis supervision process in higher education institutions is still frequently conducted manually, which may lead to inefficiencies in recording supervision data. This study focuses on the development and implementation of a web-based thesis supervision attendance application designed to facilitate attendance documentation, supervision session administration, and systematic monitoring of thesis supervision history. The methodology applied in this study is the Waterfall model, which includes the phases of requirements analysis, system design, implementation, and testing. The application was developed using the Laravel framework and a MySQL database. The system design was modeled using Unified Modeling Language (UML), while the validation process was conducted through Black Box Testing techniques. The research findings indicate that the developed application is capable of performing real-time supervision attendance recording, managing supervision information, and generating attendance reports effectively and efficiently. It can be concluded that the web-based thesis supervision attendance application improves the efficiency and accuracy of supervision record management and supports a more effective thesis supervision monitoring process..

Malware represents an evolving cybersecurity threat that demands more effective detection methods. Conventional signature-based detection systems have limitations in identifying new variants, driving the development of deep learning-based approaches. This research implements and evaluates four variants of the YOLOv11 algorithm (n, s, m, l) for malware classification based on visual image representation. The dataset consists of 22,056 malware and benign images, divided into 70% training, 15% validation, and 15% testing across 8 classes (adware, backdoor, benign, downloader, spyware, trojan, virus, worm). Each model was trained for 100 epochs with batch size 32 using Google Colab with GPU support. Results demonstrate that all variants achieve high accuracy (97.8%-98.1%) with YOLOv11m as the best performer (98.1%). YOLOv11n offers optimal balance between accuracy (97.9%) and efficiency (1.5M parameters, 0.3 ms/img inference) ideal for real-time applications. This research surpasses previous methods such as K-NN (97.18%) and hybrid CNN (96.55%) with superior inference speed (0.3-0.9 ms/img vs tens to hundreds of ms/img), proving the effectiveness of YOLOv11 for fast, accurate, and scalable malware detection.

This study investigates the implementation of the Gradient Boosting Machine (GBM) algorithm for network intrusion detection using the CICIDS2017 dataset within the CRISP-DM framework. The process encompasses Business Understanding, Data Understanding, and Data Preparation including data cleaning, categorical feature encoding, normalization, and data split (80 % training, 20 % testing). In the Modeling phase, GBM Hyperparameters (learning_rate = 0.1; max_depth = 5; n_estimators = 150) were optimized via Grid Search with 2-fold Cross Validation, and F1-Score  was selected as the primary metric due to class imbalance. Evaluation on the test set yielded accuracy of 99.99 %, precision of 100 %, Recall of 99.98 %, and F1-Score  of 99.99 %, demonstrating exceptional detection capability with minimal false negatives and false positives. Compared to previous studies, this GBM model outperforms in accuracy and stability without overfitting. These findings confirm GBM’s effectiveness for modern Intrusion Detection Systems and its suitability for Deployment in resource-constrained operational environments.

Online maps applications have become an essential tool for modern society in finding the fastest and most efficient routes. However, these applications often fail to detect current road conditions such as flooding, demonstrations, accidents, or public events, causing users to get stuck in problematic routes. This study aims to develop a prototype of a community-based road condition reporting system, visualized through a web-based digital map. The system allows users to directly report road conditions by providing photo evidence, descriptions, and event categories. It is also equipped with features for designing event routes such as carnivals and suggesting alternative paths based on community reports. The development process was carried out using a simulation-based approach with scenario testing that reflects real field conditions, without involving direct user data. The implementation results show that all core features work properly. The technologies used include Leaflet.js, OpenStreetMap, and the Nominatim geolocation API. This research produces an adaptive community-based GIS model that can be further developed as an intelligent navigation solution at the city scale

The Free Nutritional Meal Program (MBG) is a government policy that is widely discussed by the public through social media, especially TikTok. Various comments that have emerged indicate differences in public opinion towards the program, so an analysis is needed to determine the tendency of public sentiment. This study aims to analyze TikTok user sentiment towards the Free Nutritional Meal Program using the Naive Bayes method. The research method is carried out through several steps, namely collecting TikTok comment data, preprocessing text, labeling sentiment data into positive, negative, and neutral, feature transformation using TF-IDF, and classification using the Naive Bayes algorithm. Based on the analysis of 500 comment data, the results show that positive sentiment dominates public opinion by 42% (210 data), followed by negative sentiment by 36% (180 data), and neutral sentiment by 22% (110 data). Testing the classification model using Naive Bayes produces excellent performance with an accuracy rate of 86%, precision of 84%, recall of 85%, and F1-score of 84%. The conclusion of this study shows that the Naive Bayes method is effective as an approach in social media sentiment analysis to map public responses to government policies.

Digitalization in the fitness industry is increasingly essential to improve efficiency and service quality. However, many fitness centers still manage data manually, including KRESNA GYM, which faces challenges in member registration, workout scheduling, and facility information delivery. This study aims to design a web-based e-fitness application using the Laravel framework to support digital service management. The development follows the Waterfall model through stages of requirement analysis, design, implementation, testing, and evaluation. The application includes features such as a landing page, admin/member login and registration, management dashboards, workout schedules, equipment guides, and supplement listings. Black-box testing confirms that all features function as expected. This system simplifies administrative processes and enhances member experience, making it effective in supporting digital transformation at KRESNA GYM.

Background: Adenoid hypertrophy is a condition characterized by enlargement of the adenoid tissue which can cause nasopharyngeal obstruction and potentially affect the function of the Eustachian tube. Dysfunction of the Eustachian tube may disrupt middle ear ventilation and increase the risk of otitis media. The degree of adenoid hypertrophy can be objectively assessed using a lateral nasopharyngeal radiograph by calculating the adenoid–nasopharyngeal ratio (A/N ratio). Objective: This study aimed to determine the relationship between adenoid hypertrophy based on the adenoid–nasopharyngeal ratio and the incidence of otitis media. Methods: This study was a quantitative research with an analytic observational design using a cross-sectional approach. Data were obtained from the medical records of patients with adenoid hypertrophy who underwent lateral nasopharyngeal radiographic examination at RSI Purwokerto from 2022 to 2025. The sample consisted of 31 patients who met the inclusion and exclusion criteria. Data analysis was performed using the Spearman correlation test because the data were not normally distributed based on the Shapiro–Wilk test. Results: The results showed that most of the subjects were male (17 subjects, 54.8%) and female (14 subjects, 45.2%). The median age of the subjects was 7 years with an age range of 4–9 years. The median adenoid–nasopharyngeal ratio was 0.90 with a range of 0.68–0.99. Otitis media was found in 11 subjects (35,5%), while 20 subjects (64,5%) did not experience otitis media. The Spearman correlation test showed a correlation coefficient of r = 0.015 with a p-value of 0.936 (p > 0.05), indicating that there was no significant relationship between the adenoid–nasopharyngeal ratio and the incidence of otitis media. Conclusion: There was no statistically significant relationship between adenoid hypertrophy based on the adenoid–nasopharyngeal ratio and the incidence of otitis media.

Tuberculosis (TBC) in children remains a serious public health problem in Indonesia, with the 0–14 age group accounting for 16.2% of total notified cases in 2024. The uneven distribution of cases across provinces is thought to be influenced by various social determinants, yet spatial studies specifically on childhood TBC at the national level remain scarce. This study aimed to analyze the spatial pattern of childhood tuberculosis cases and social determinants in Indonesia in 2024 using a spatial ecological design across 38 provinces. Analysis included descriptive statistics, thematic mapping using QGIS, Moran's I test, and Local Indicator of Spatial Association (LISA) with queen contiguity weighting matrix. Results showed a strong positive spatial autocorrelation with a Moran's I value of 0.612. High-high clusters were identified in DKI Jakarta, Central Java, Banten, and West Java, which simultaneously recorded high population density and low primary healthcare ratios. Territory-based interventions should be prioritized in these hotspot provinces.

Tuberculosis (TBC) in children remains a serious public health problem in Indonesia, with the 0–14 age group accounting for 16.2% of total notified cases in 2024. The uneven distribution of cases across provinces is thought to be influenced by various social determinants, yet spatial studies specifically on childhood TBC at the national level remain scarce. This study aimed to analyze the spatial pattern of childhood tuberculosis cases and social determinants in Indonesia in 2024 using a spatial ecological design across 38 provinces. Analysis included descriptive statistics, thematic mapping using QGIS, Moran's I test, and Local Indicator of Spatial Association (LISA) with queen contiguity weighting matrix. Results showed a strong positive spatial autocorrelation with a Moran's I value of 0.612. High-high clusters were identified in DKI Jakarta, Central Java, Banten, and West Java, which simultaneously recorded high population density and low primary healthcare ratios. Territory-based interventions should be prioritized in these hotspot provinces.

Diabetes Mellitus is a non-communicable disease with an increasing prevalence and has become a major public health concern globally and nationally. The incidence of diabetes mellitus is influenced by various individual and environmental factors. This study aimed to analyze the relationship between age, gender, and residential proximity to landfill areas and the incidence of diabetes mellitus in Bendosari District. A quantitative analytic observational design with a cross-sectional approach was employed. The study population consisted of 1,890 patient visit records recorded in the Management Information System of Bendosari Public Health Center in 2025. A total of 363 respondents were selected using proportionate stratified random sampling. Data were analyzed through univariate analysis, bivariate analysis using the Chi-Square test, and multivariate analysis using multiple logistic regression. The findings showed that age was significantly associated with diabetes mellitus incidence (p=0.000; OR=79.790; 95% CI=53.511–118.974). Gender was also significantly related to diabetes mellitus incidence (p=0.000; OR=0.298; 95% CI=0.203–0.435), indicating that females had a higher risk than males. In contrast, residential proximity to landfill areas was not significantly associated with diabetes mellitus incidence (p=0.308; OR=1.247; 95% CI=0.439–3.540). Multivariate analysis revealed that age and gender were the dominant factors influencing diabetes mellitus incidence, with the model explaining 56.1% of the variation. The study concludes that age and gender are significant determinants of diabetes mellitus incidence, whereas residential proximity to landfill areas has not been proven to significantly affect its occurrence.

Adolescents are a nutritionally vulnerable group at risk of double burden of malnutrition. Riskesdas 2023 data showed that the prevalence of undernutrition in adolescents aged 13–15 years in North Sumatra reached 16.8%, while overweight and obesity reached 18.3%. The habit of consuming unhealthy snacks at school is one of the main preventable risk factors through structured nutrition education. Objective: This community service program aimed to increase knowledge of balanced nutrition and healthy snack selection behavior among Grade VIII students of SMP Negeri 19 Medan. Methods: Activities were carried out through interactive lectures, demonstrations, educational games, and workshops with 64 students. Evaluation used pre-test and post-test analysis with Wilcoxon Signed Rank Test. Results: There was a significant increase in nutritional knowledge in both classes (p=0.001) and healthy snack selection behavior (p=0.000). Conclusion: The Healthy Teen School program effectively improved adolescent nutrition knowledge and behavior.