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Low Birth Weight (LBW) refers to infants born with a birth weight of less than 2,500 grams and remains an important issue in neonatal health due to its association with increased neonatal morbidity and mortality. To analyze the determinants of LBW based on primary studies published from 2021 to 2026. A literature review was conducted using the PRISMA approach. Article searches were performed through PubMed, Google Scholar, Scopus, ScienceDirect, and ProQuest using the keywords low birth weight, determinant factors, risk factors, BBLR, and faktor risiko with Boolean operators AND/OR. The inclusion criteria were primary studies, full-text availability, publication in Indonesian or English, and publication years from 2021 to 2026. A total of 20 articles were included, consisting of 15 international articles and 5 national sources. The review showed that LBW is influenced by interrelated maternal, nutritional, obstetric, and sociodemographic factors during pregnancy. The most dominant factors included multiple pregnancy with an adjusted OR of 21.74, maternal food insecurity with an AOR of 6.85, maternal hemoglobin level <11 g/dL with an AOR of 5.21, lack of iron-folic acid supplementation with an AOR of 4.17, maternal age ≤20 years with an AOR of 3.42, pregnancy interval <1 year with an adjusted OR of 2.92, missed antenatal care visits with an AOR of 2.74, smoking during pregnancy with an OR of 2.18, and maternal hypertension with an AOR of 1.94. LBW is influenced by multiple interrelated factors; therefore, efforts to reduce its incidence should focus on evidence-based interventions, particularly through optimizing antenatal care services, improving maternal nutritional status, and early detection of pregnancy.

Breast tumors are classified into two types, namely benign and malignant tumors, the latter commonly referred to as breast cancer. Breast cancer is one of the major health problems affecting women worldwide, including in Indonesia. According to WHO data in 2022, there were 2.3 million breast cancer cases with 685,000 deaths globally, while in Indonesia, 396,914 cases and 234,511 deaths were reported. The high incidence rate is exacerbated by low public awareness in recognizing early symptoms and performing early detection, resulting in 60–70% of cases being diagnosed at an advanced stage, supported by findings that 65.6% of female students still have a low level of knowledge. Female students were selected as research subjects because they are in a vulnerable reproductive age group and have an important role in increasing awareness of early detection, yet they still have limited knowledge. Based on this, this study aims to design a web-based early detection system for breast tumor risk using the Forward Chaining method, which functions as a tool to identify early symptoms, assess risk levels, and provide information on prevention and initial management. This study employed the method with the Expert System Development Life Cycle (ESDLC) model, consisting of the stages of assessment, knowledge acquisition, design, testing, and documentation, along with the Forward Chaining inference method.

This study aims to examine the relationship between family support and depression levels among the elderly in Pejuang Village, Bekasi City, through a descriptive-narrative literature review. The review analyzed relevant scientific articles discussing family support, social support, and depression in older adults. Literature was selected based on the suitability of the elderly population, the presence of family or social support variables, and the measurement of depressive symptoms or depression levels. The analysis compared each article’s objectives, research design, respondent characteristics, instruments, findings, and conclusions. The results indicate that most studies found a relationship between family support or social support and depression among the elderly. Adequate family support, including emotional, instrumental, informational, and appraisal support, helps older adults feel cared for, valued, secure, and better able to adapt to the aging process. Preliminary findings at the Elderly Posyandu in Pejuang Village also show variations in family support and depression levels among elderly participants. Conversely, limited family support may increase loneliness, psychological distress, and depressive symptoms. Therefore, family support functions as a protective factor in reducing depression risk among older adults. Strengthening the involvement of families, health workers, and elderly posyandu cadres is necessary as a promotive and preventive strategy to maintain psychological well-being through education, early detection, and sustainable community-based assistance for vulnerable elderly groups living in community and family environments.

Hyperglycemia is a condition of elevated blood sugar levels that can potentially lead to various health complications if not controlled early. This condition is often influenced by unhealthy eating habits, lack of physical activity, and low awareness among adolescents regarding regular blood sugar checks. Adolescents are an age group that is vulnerable to lifestyle changes, putting them at risk of developing metabolic disorders later in life. This community service activity aims to increase adolescent knowledge and awareness regarding the dangers of hyperglycemia and the importance of preventive measures from school age. The activity was carried out at SMK Nurul Ulum Lebaksiu, involving 59 students as participants. The methods used included health education through audio-visual media, interactive lectures, discussions, and Random Blood Sugar (GDS) tests for early detection. The results of the activity showed an increase in student knowledge based on a comparison of pre-test and post-test scores, as well as the implementation of GDS tests on all participants. This activity is expected to foster healthy lifestyle behaviors and increase adolescent awareness of the prevention of non-communicable diseases.

Maternal Mortality Rate (MMR) is a critical indicator for evaluating maternal health programs, and insufficient knowledge of pregnancy danger signs remains a significant factor in preventable maternal complications and mortality. This issue is particularly prevalent among third-trimester pregnant women. Health education has proven to be an effective strategy for enhancing maternal knowledge, promoting early detection of obstetric emergencies, and supporting timely decision-making. This study aimed to evaluate the impact of health education on improving knowledge of pregnancy danger signs among third-trimester pregnant women in Nunkurus Village. A pre-experimental study with a one-group pre-test–post-test design was conducted, involving 42 third-trimester pregnant women, with 40 selected through purposive sampling. Structured questionnaires were used to collect primary data, and the Wilcoxon signed-rank test was employed to analyze the knowledge differences before and after the intervention. Results showed a statistically significant increase in knowledge after the health education intervention (p-value = 0.000; p < 0.05). In conclusion, health education significantly enhances knowledge of pregnancy danger signs among third-trimester pregnant women. Strengthening community-level educational interventions can help in early detection of pregnancy complications and contribute to reducing maternal morbidity and mortality.

Malnutrition and stunting among children under five remain major public health challenges in developing countries, including Indonesia. These conditions are associated with increased morbidity, mortality, impaired cognitive development, and reduced productivity in adulthood. Stunting reflects chronic nutritional deficiencies, while severe malnutrition indicates acute or prolonged inadequate nutrient intake, often exacerbated by infections, poor caregiving practices, and unfavorable socioeconomic conditions. This case report aims to describe the clinical condition, contributing factors, management, and outcomes of a 14-month-old female toddler diagnosed with severe malnutrition and stunting without complications in Blang Dalam Geuteung Village, Nisam Subdistrict, North Aceh Regency. The assessment was conducted using a family medicine approach, incorporating detailed history taking, physical examination, anthropometric measurements, and nutritional status evaluation based on World Health Organization Z-score indicators. Interventions included nutritional rehabilitation through appropriate dietary intake, family education on balanced nutrition and proper feeding practices, routine growth monitoring, and optimization of primary healthcare services. The results showed gradual improvement in the child’s nutritional status, evidenced by weight gain, better appetite, and improved feeding patterns following the intervention. This case highlights the importance of early detection, comprehensive family-centered management, and continuous monitoring in addressing malnutrition and stunting at the primary care level. Strengthening community-based interventions, improving caregiver knowledge, and enhancing collaboration between healthcare providers and families are essential to reduce the burden of malnutrition and support optimal child growth and development.

Adolescent mental health is an important aspect in human resource development because it affects learning ability, social relationships, and readiness to face adult life. Adolescence, especially at the junior high school level, is a transitional period that is prone to mental and emotional disorders due to biological, psychological, and social changes that occur simultaneously. This study aims to describe the mental health condition of adolescents using the Self Reporting Questionnaire (SRQ-20) instrument in students of SMPN 3 Ubud, Gianyar Regency. The study used a descriptive design with a cross sectional approach. The sampling technique was carried out in total sampling with a total of 117 students. The research instrument is in the form of an SRQ-20 questionnaire that has been proven to be valid and reliable. Data analysis was carried out descriptively to describe the distribution of symptoms and mental health categories of respondents. The results showed that most students were in the category of good mental health, although there were still a number of students with poor conditions. The most common symptoms are easy to feel tired and difficulty in making decisions. Based on the characteristics of respondents, students aged 13–15 years are more likely to experience poor mental health conditions than 11-13 years old, and the proportion of female students is higher than men in experiencing symptoms of mental emotional disorders. These findings affirm the importance of early detection of adolescent mental health in schools as the basis for promotive and preventive interventions, through optimizing the role of counseling guidance and creating a supportive school environment.

Postpartum depression (PPD) is a common and serious mental health disorder for mothers after givingbirth, which is a public mental health problem because it not only has a direct impact on the baby, but also on the family. The most common symptoms of PPD are overwhelming sadness, feelings of hopelessness and helplessness, moodiness, an inability to experience joy with the baby, serve anxienty, loss of appetite, poor concentration and memory, sleep disturbances, prolonged fatigue, and suicidal ideation (American Psychological Association, 2013). The design used in this study was quantitative by measuring the prevalence of postpartum depression in postpartum mothers using the EPDS form. The research was conducted at Gandapura Community Health Center, this location wa used as the research site because it had not been exposed at all regarding the use of the EPDS form as part of the initial assessment of midwifery services. A population is all elements that meet certain criteria for inclusion in a study. The population in this study was all postpartum mothers who gave birth in the obstetrics ward. The sample criteria in this study are divided into two, namely inclusion criteria and exclusion criteria. Conclusion: Postpartum guidance provided to mothers influences the risk of postpartum depression. Postpartum women who receive assistance are less likely to experience postpartum depression, and mothe who do not receive assistance are depression.

The Maternal Mortality Rate (MMR) is primarily caused by pregnancy complications that are actually preventable through early detection; however, maternal understanding of the Maternal and Child Health (MCH) Handbook remains very low. This community service aims to empower pregnant women at Sarfina Primary Clinic, Medan, by enhancing their MCH Handbook literacy. The implementation utilized a Community-Based Participatory Action (CBPA) approach conducted over four weeks, involving 30 pregnant women. The activity stages included a pre-test, interactive education, self-assessment simulations, and a post-test. Evaluation results indicated a significant surge in health literacy; pregnant women's knowledge in the "Good" category drastically increased from 13.3% to 86.7%, while the "Poor" knowledge category was successfully eliminated from 50% to 0%. In conclusion, this educational and simulation intervention proved highly effective in transforming pregnant women's behavior, making them proactive individuals in the early detection of pregnancy danger signs which is expected to reduce the risk of pregnancy complications and reduce maternal mortality rates.

Background: Comprehensive midwifery care is essential for early detection of complications and reducing maternal and infant mortality rates. In Sleman Regency, despite high access to health services, continuous monitoring remains crucial for ensuring maternal and fetal safety. Objective: To provide comprehensive midwifery care for Mrs. M at Klinik Pratama Shaqi, Sleman, from the third trimester of pregnancy through the postpartum and neonatal periods. Methods: This is a descriptive qualitative study using a case study approach based on Varney's seven-step midwifery management and SOAP documentation. Findings: During pregnancy (37 weeks 6 days), the mother experienced physiological complaints of back pain and shortness of breath, managed through posture education and pregnancy exercises. Labor proceeded normally and spontaneously on October 6, 2024, utilizing "gentle birth" practices such as endorphin massage to reduce pain. A second-degree perineal tear occurred and was treated according to procedure. The baby was born healthy, weighing 3100 grams, with successful Early Initiation of Breastfeeding (EIB). During the postpartum and neonatal periods, uterine involution was normal, breast milk production was adequate, and the infant's growth met standards with no danger signs. Implications: Continuous assistance improves the mother's physical and psychological readiness and ensures a healthy neonatal transition.

The growing use of smartphones among adolescents carries a high risk of addiction, which can negatively impact physical, mental, and social well-being. To address this issue, a community service program was implemented to conduct early detection of gadget addiction among high school students and provide educational health media to raise knowledge and awareness about excessive smartphone use. The program involved 240 students of SMA Negeri 1 Tuntang and was conducted in three stages: screening, development of educational materials, and health counseling. Screening used the short version of the Smartphone Addiction Scale and revealed that 90% of students were classified as addicted. Prior to counseling, 81.25% of students had low levels of knowledge regarding healthy gadget use, which significantly improved after the intervention, with 83.4% achieving high knowledge levels. Health counseling proved crucial in enhancing students’ understanding and promoting responsible smartphone habits. The program highlights the importance of collaborative efforts by schools, parents, and students to limit smartphone use, encourage physical activity, and foster face-to-face social interactions to support adolescent well-being.

Early detection of child growth and development is a crucial effort to prevent developmental delays and health problems in children. Family involvement plays a significant role because the family is the closest environment to the child and has continuous interaction in daily life. This study aims to analyze the effectiveness of a family education program in improving parents’ knowledge and skills in detecting child growth and development. The research employed a quantitative approach with a quasi-experimental design using a pretest–posttest method. The population consisted of families with children aged 0–6 years, with samples selected using purposive sampling techniques. Data were collected through questionnaires and observation sheets measuring parents’ knowledge, attitudes, and skills related to growth and developmental detection. Data analysis was conducted using paired sample t-tests. The results showed a significant increase in parents’ knowledge and skills after participating in the family education program. The findings indicate that structured and continuous family education can enhance parents’ ability to monitor child growth and development independently. This study implies that family-based education programs can be integrated into community health services as a preventive strategy to improve child health outcomes.

Detection and identification of plant diseases is critical to the success and efficiency of agricultural production. Plant disease outbreaks are becoming more frequent throughout the world, and the presence of these diseases in cultivated plants has a significant impact on productivity. Therefore, researchers are focusing on developing effective and reliable plant disease detection methods. Thus, farmers can take advantage of early detection of this disease to minimize future losses. This article discusses machine learning approaches as well as decision trees, K-nearest neighbors, naive Bayes, support vector machines (SVM), and random forests for detecting coffee leaf diseases using leaf images. The above-mentioned classifications were researched and compared to determine the most suitable plant disease prediction model with the highest accuracy. Compared with other classification algorithms, the SVM algorithm achieves the highest accuracy of 99.75%. All the models trained above will be used by farmers to quickly identify and classify new diseases in images as a prevention strategy. As a preventive measure, farmers can detect and classify new diseases in images early.

Introduction: Triglycerides are a lipids fractions that play an important role in energy metabolism, but high levels in the blood are strongly associated with increased risk of cardiovascular disease, metabolic syndrome, and type 2 diabetes. The prevalence of hypertriglyceridemia tends to increase, including in urban area such us West Jakarta which have high risk consumption patterns. This community service activity aimed to raise public awareness about the importance  lipid profile management with screen triglyceride levels in community of Kelurahan Kota Bambu. Method: The activity was conducted in June 2025, involving 168 adult participants. The method was used was health education on the role of triglycerides and their risk,, followed by laboratory testing using the Nesco BL-101 5in1 Lipid Panel Monitoring System. Triglyceride level was classified into normal, borderline, high, and very high categories according to the NCEP ATP III guidelines. Results: The average triglyceride level of the participants was 181.21 mg/dL, with a range of 47–830 mg/dL. The triglyceride levels of the majority of participants were in the normal category, but the proportion with high and very high triglyceride levels was significant, indicating the existence of a risk group that needs attention. Conclusion: This activity confirms that simple triglyceride testing at the community level can be an effective step in early detection, education, and prevention

Knee osteoarthritis (OA) is one of the leading causes of disability among the elderly population. This degenerative joint disease is characterized by progressive damage to the articular cartilage and structural alterations of the knee joint, resulting in pain, reduced mobility, and diminished quality of life. This Community Service Program (PKM) aimed to promote early detection of knee OA through simple radiological screening as a preventive strategy to reduce the risk of musculoskeletal disability. The activity was conducted at Asisi Church, South Jakarta, involving 87 participants aged 54–87 years (mean 70.77 ± 7.32 years). Radiological examination was performed using standard anteroposterior knee X-rays, and results were classified according to the Kellgren–Lawrence grading system. Findings revealed that 98.9% of participants exhibited radiological signs of OA, predominantly grade II (60.9%), followed by grade III (21.8%), grade I (11.5%), and grade IV (4.6%), while only 1.1% showed normal results. Female participants (74.7%) predominated across all OA grades, indicating hormonal and biomechanical influences on disease progression. The mean age increased with OA severity, supporting the degenerative theory that aging leads to decreased chondrocyte function and cartilage elasticity. In addition to screening, participants received education on weight management, muscle strengthening exercises, and injury prevention. The results demonstrate that simple radiological screening is an effective, practical, and cost-efficient community-based approach for early detection of knee OA. Integrating such preventive strategies within primary care systems could significantly reduce the burden of disability among the elderly population.

Chronic kidney disease (CKD) is a growing global health concern that frequently remains undiagnosed until advanced stages. Early detection through simple laboratory screening is essential to prevent disease progression and associated cardiometabolic complications. This community service program aimed to assess kidney function using serum creatinine and estimated glomerular filtration rate (eGFR), while increasing public awareness regarding CKD prevention. A total of 59 participants were included, with a mean age of 39.15 ± 15.39 years (range 16–75 years), predominantly female (74.58%). The mean serum creatinine level was 1.0 ± 0.19 mg/dL, and the mean eGFR was 91.08 ± 20.53 mL/min/1.73 m². Most participants demonstrated normal kidney function (28.8%) or mild decline (21.6%). A progressive reduction in eGFR with increasing age was observed, reflecting the physiological decline in nephron mass and renal perfusion. The program also provided education on kidney-protective practices, including optimal blood pressure control, diabetes management, adequate hydration, and avoidance of nephrotoxic agents. This intervention improved participants’ understanding of CKD risk factors and the importance of regular screening. In conclusion, serum creatinine and eGFR evaluation offer simple, accurate, and practical tools for early CKD detection, supporting promotive–preventive strategies to slow disease progression and enhance quality of life in at-risk populations.

Hypertension is a highly prevalent non-communicable disease often referred to as "The Silent Killer" because it rarely shows symptoms until it causes serious complications such as stroke, kidney failure, and heart disease. This community service activity aims to optimize the Mobile Blood Pressure Monitoring Program as a hypertension screening method in Sanahu Village. The methods used include participant data collection, blood pressure checks with a manual sphygmomanometer, and health education on hypertension prevention. A total of 96 participants participated in this activity, and the results showed that 58 participants (60.4%) were hypertensive. This program has proven effective in reaching communities with limited access to health services and raising public awareness about the importance of early detection of non-communicable diseases. In addition, this activity succeeded in providing knowledge to the community about how to prevent hypertension and the importance of maintaining a healthy lifestyle, which is expected to reduce the incidence of hypertension in the future.

Diabetes Mellitus is a chronic disease that requires early detection to prevent serious complications. This study aims to implement the Artificial Neural Network (ANN) algorithm with the Backpropagation method to predict the risk of diabetes. The dataset used is the Pima Indians Diabetes Dataset, consisting of 768 medical records with 8 feature attributes. This study employs the Multi-Layer Perceptron method with an architecture of 8 input neurons, two hidden layers, and 1 output neuron. Model evaluation is conducted using a Confusion Matrix to measure accuracy levels. The test results show that the model is capable of predicting diabetes diagnosis with an accuracy rate of 76.62%. Based on these results, it can be concluded that the Backpropagation algorithm is effective as an alternative method for early detection of diabetes, although further development is needed to improve the model's sensitivity to positive cases.  

Cervical cancer remains a major public health problem and is one of the leading causes of cancer-related mortality among women in Indonesia. Early detection through Visual Inspection with Acetic Acid (VIA) is an effective and feasible screening method at the primary health care level. However, the coverage of VIA screening among women of reproductive age (WRA) remains low. Knowledge is considered an important predisposing factor that may influence women’s motivation to undergo VIA screening. This study aimed to analyze the association between cervical cancer knowledge and motivation to undergo VIA screening among women of reproductive age. This study employed a quantitative analytic design with a cross-sectional approach. A total of 105 women of reproductive age were recruited using consecutive sampling at the Payangan Community Health Center, Gianyar Regency, Indonesia. Data were collected using validated and reliable structured questionnaires measuring cervical cancer knowledge and motivation to undergo VIA screening. Univariate analysis was performed to describe respondent characteristics, while bivariate analysis using the chi-square test was applied to examine the association between knowledge and motivation at a significance level of 5%. The results showed that 61.9% of respondents had good knowledge of cervical cancer, while 52.4% demonstrated low motivation to undergo VIA screening. A statistically significant association was found between cervical cancer knowledge and motivation to undergo VIA screening (p = 0.043). Women with higher levels of knowledge tended to have greater motivation to participate in VIA screening. In conclusion, cervical cancer knowledge is significantly associated with motivation to undergo VIA screening among women of reproductive age. These findings suggest that strengthening health education interventions at primary health care facilities is essential to enhance motivation and increase participation in early cervical cancer detection programs.

Chronic kidney disease is an increasingly prevalent health issue that requires more precise clinical data-based early detection methods to enable timely and appropriate treatment. This study focuses on developing a predictive model for chronic kidney disease using the Light Gradient Boosting Machine (LightGBM) algorithm and enhancing its performance through hyperparameter optimization with the Grey Wolf Optimizer (GWO). The dataset used originates from public sources and undergoes several preprocessing steps, including missing value imputation, categorical feature encoding, outlier handling, initial feature selection, and stratified data splitting to maintain model quality. Three modeling approaches were evaluated: LightGBM with default parameters, LightGBM enhanced using Random Search, and LightGBM optimized with GWO. The experimental results indicate that the baseline model already performs well, Random Search improves accuracy and F1-score, and GWO achieves the highest AUC-ROC value despite requiring longer computation time. Significance testing through cross-validation shows that the performance differences among the three models are not statistically significant, suggesting that the observed improvements are not strong enough to determine a definitively superior optimization method. The feature importance analysis highlights that clinical indicators such as creatinine levels, glomerular filtration rate, blood pressure, and urine protein contribute most prominently to the prediction. Overall, the study demonstrates that LightGBM is a reliable model for early detection of chronic kidney disease, and hyperparameter optimization still offers added value that can support the development of AI-based clinical decision-support systems