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Background: Structural Health Monitoring plays a critical role in ensuring the safety, reliability, and sustainability of high performance composite structures used in aerospace, civil infrastructure, and mechanical systems. Conventional externally mounted sensors often face challenges related to environmental interference, maintenance complexity, and long term stability. Objective: This study aims to develop and validate an integrated smart composite monitoring system with embedded sensing capabilities that enhances damage detection accuracy and operational durability under varying mechanical stress conditions. Method: Smart composite specimens were fabricated by embedding fiber optic and piezoelectric sensors within fiber reinforced polymer laminates, followed by tensile, fatigue, and vibration testing. Signal processing techniques including time frequency analysis were applied to extract damage sensitive features, which were then classified using machine learning algorithms to distinguish healthy and damaged structural states. Results: The experimental findings demonstrate high damage detection capability, stable sensor performance under cyclic loading, improved reliability compared to conventional monitoring approaches, and consistent monitoring accuracy throughout the fatigue life of the specimens. The integration of embedded sensing and data driven analytics significantly enhances structural response interpretation and supports predictive maintenance strategies.

The increasing incidence of bacterial resistance to antibiotics has become one of the major challenges in global health, necessitating the exploration of natural antibacterial sources as alternative treatments, such as bioactive compounds derived from sea urchins. This literature review aims to evaluate the antibacterial potential of sea urchin extracts based on existing research findings. The literature search was conducted using the PubMed and Google Scholar databases using the Boolean operators (AND, OR). Inclusion criteria include articles published between 2014 and 2024, available in full text, written in either Indonesian or English, and discussing the antibacterial activity of sea urchin extracts from the species Diadema setosum and/or Echinometra mathaei. Based on the selection process, eight articles met the inclusion criteria and were included in the review. The results of the literature review indicate that sea urchin extracts exhibit antibacterial activity against gram-negative bacteria, including Escherichia coli, Salmonella typhi, Salmonella typhimurium, Shigella flexneri, Pseudomonas aeruginosa, Aeromonas hydrophila, Acinetobacter sp., Citrobacter freundii, and Klebsiella pneumoniae, as well as gram-positive bacteria, including Propionibacterium acnes, Staphylococcus aureus, Bacillus cereus, Bacillus subtilis, Staphylococcus epidermidis, Streptococcus mutans, and Streptococcus sobrinus. These antibacterial effects are attributed to the presence of secondary metabolites such as alkaloids, steroids, flavonoids, saponins, and phenolics.

Mental health issues such as depression, anxiety, and stress continue to increase globally and are recognized as critical factors that influence social functioning, productivity, and overall quality of life. Conventional mental health services are often limited by barriers including high cost, geographical distance, and persistent stigma that discourage individuals from seeking timely help. The digital era provides an alternative through the integration of technology into mental health counseling, offering greater accessibility, flexibility, and anonymity. Nevertheless, a key limitation of many digital counseling platforms lies in their inability to fully capture and respond to the emotional nuances of users during interactions. This study aims to address that gap by developing a speech-based emotion detection framework designed to be integrated into digital counseling environments. The proposed methodology includes the collection and preprocessing of speech samples, feature extraction using acoustic parameters, and training machine learning models to classify emotions in real time. Experimental results demonstrate that this approach significantly improves the accuracy of emotion detection, enabling digital counseling systems to provide more adaptive and personalized support. Beyond counseling, the research highlights the broader applicability of speech emotion recognition in education, telemedicine, and interactive digital assistants, all of which benefit from improved sensitivity to human emotions. These findings underscore the potential of artificial intelligence to strengthen digital mental health interventions, ensuring services that are not only more efficient and inclusive but also capable of fostering long-term emotional well-being in diverse populations.

Mild anemia in pregnant women remains a common health problem at the primary healthcare level and may negatively affect both maternal health and fetal development. One non-pharmacological approach to managing anemia is the utilization of local food sources rich in iron, such as spinach. This study aimed to determine the effectiveness of spinach extract in increasing hemoglobin levels among pregnant women with mild anemia at Poskesdes Wiritasi. This study employed a quasi-experimental design using a one-group pretest–posttest approach without a control group. The sample consisted of 30 pregnant women diagnosed with mild anemia who were selected through purposive sampling. The intervention involved the regular administration of spinach extract for 14 consecutive days. Hemoglobin levels were measured before and after the intervention using a standard hemoglobin testing device. Data were analyzed to assess differences in hemoglobin levels before and after the intervention. The results showed a significant increase in hemoglobin levels following the administration of spinach extract. These findings indicate that spinach extract has a positive effect on improving hemoglobin levels in pregnant women with mild anemia. Therefore, spinach extract may serve as an effective, safe, and easily applicable local food–based nutritional intervention for the prevention and management of mild anemia among pregnant women at the village healthcare level.

The threat of Distributed Denial of Service (DDoS) is increasing develop along with increasing use of the Internet of Things (IoT) and Software-Defined Networking (SDN) architecture . Although SDN provides convenience in management network , properties its centralized control make it prone to to flooding attacks that can paralyze controller performance . Detection method conventional , such as approach statistics and machine learning, still own limitations in matter accuracy , high false positive rate , and dependence on extracted features manually . To overcome problem said , research This propose a hybrid deep learning based DDoS detection and mitigation model that combines Convolutional Neural Network (CNN) to extraction feature spatial from RGB and Gated Recurrent Unit (GRU) images for understand temporal correlation between traffic data network . System tested through network test-bed Mininet based with Ryu/Floodlight controller, using simulation DDoS attacks (Hping3, LOIC) and normal traffic (video streaming, HTTP server). Traffic data cross recorded in PCAP format, processed become RGB image measuring 200×200 pixels, and labeled based on type traffic . Evaluation results with metric accuracy , precision, recall, F1-score, and MCC show that the CNN–GRU model has performance more superior compared to baseline approaches such as CNN-only, GRU-only, as well as classical ML methods such as SVM and Random Forest. In addition , the system capable apply mitigation adaptive through automatic flow rule creation on edge switches. Findings This confirm that effective deep learning- based spatial -temporal hybrid approach in increase detection early and response DDoS attacks on SDN networks adaptive and real-time.  

Sacha inchi (Plukenetia volubilis Linneo) is a plant from the Euphorbiaceae family known for its green star-shaped fruit and brown seeds. This plant has high nutritional value and significant antioxidant activity (Nuha and Sriwidodo 2022). This study aims to identify secondary metabolite compounds and determine the total phenolic content of the methanol extract of Plukenetia volubilis Linneo leaves. The samples were extracted using the maceration method, then phytochemical tests and total phenolic content analysis were carried out using the Folin-Ciocalteu method (Sari et al. 2021). The results of the phytochemical test showed that the methanol extract of sacha inchi leaves contained secondary metabolite compounds such as alkaloids, flavonoids, saponins, and tannins. The total phenolic content obtained from the extract was 19.94%, which indicates the potential for high antioxidant activity. The results of this study indicate that sacha inchi leaves have the potential to be developed as a source of natural bioactive compounds that are beneficial to health.

Background: Polycystic ovary syndrome (PCOS) is a complex endocrine-metabolic disorder common in women of reproductive age, characterized by insulin resistance (IR), anovulation, and hyperandrogenism, often leading to infertility. Metformin is the first-line therapy used. However, inositol, especially myo-inositol (MI) and D-chiro-inositol (DCI), have shown promising therapeutic potential. Direct comparison and optimal efficacy of both still require a comprehensive review. Objective: This systematic review aims to evaluate the efficacy of inositol (as monotherapy or in combination) compared with metformin, placebo, or no intervention, in improving reproductive, hormonal, and metabolic outcomes in women with PCOS. Methods: Conducted according to PRISMA guidelines, a systematic literature search was conducted in Pubmed and Ebsco databases for randomized controlled trials (RCTs) published in the last 10 years. Studies evaluating inositol and/or metformin in women with PCOS and reporting reproductive, hormonal, or metabolic outcomes were included. Study selection and data extraction were performed independently by five reviewers. Results: Six randomized controlled trials (RCTs) were included in this review. Metformin consistently showed improvements in insulin resistance and androgen levels. Myo-inositol also demonstrated efficacy in improving metabolic and hormonal parameters, as well as reproductive outcomes, often with a better tolerability profile, especially as monotherapy. The combination of metformin and myo-inositol has shown potential improvements in some reproductive functions (such as live birth rate) compared to metformin alone in some studies. However, other studies have shown comparable or superior efficacy of myo-inositol monotherapy with fewer side effects. Adjuvant therapies such as dexamethasone or calcium/vitamin D have shown benefits in certain subpopulations. Conclusions: Both inositol (especially myo-inositol) and metformin have significant therapeutic roles in the management of PCOS. Metformin remains an important intervention for metabolic dysregulation and hyperandrogenism. Inositol appears to be an effective and often better tolerated alternative, with significant reproductive benefits. The choice of therapy should be individualized based on patient phenotype and treatment goals.    

Centella asiatica (L) urban is a plant that has the potential to be a source of immunomodulatory agents because it contains several groups of active compounds, asiaticoside, madecassoside, madecassic acid and asiatic acid, which can act as anti-allergic, anti-inflammatory, and immunomodulators. This study aims to review relevant literature to summarize the immunomodulatory effects produced by Centella asiatica (L.) urban. This study used a literature review design involving 4 experimental study articles published in the last 10 years in the electronic databases  PubMed and ScienceDirect. The results of this study showed that C. asiatica has been shown to provide immunomodulatory effects through various mechanisms, including as an anti-inflammatory by decreasing nitrite production, PGE2 and TNF-α, reducing NF-κβ activation, and inhibiting pro-inflammatory mediators induced by IFN-γ and TNF-α, including IL-6 and COX-2. C. asiatica can also act as an antioxidant that inhibits ROS production, stimulates GSH, and binds free radicals. In addition, C. asiatica can also play a role in the adaptive immune response.

Image processing is a branch of computer science that is growing rapidly and is widely used in various fields, including in security systems. Face identification is one of the main applications of image processing that aims to recognize and distinguish individual faces in a system. The methods used in face identification involve various techniques, such as facial feature detection, characteristic extraction, and classification using machine learning algorithms. This article discusses the application of image processing in a security system based on face identification and the technology used to improve the accuracy and reliability of the system. The results of the study show that the combination of deep learning algorithms with image pre-processing techniques can increase the success rate of face identification in security systems.

Diabetes mellitus is gathering disease metabolic with hyperglycemia caused by abnormalities in insulin secretion , insulin action , or both of them . Loss central type 2 diabetes is caused by insulin resistance in muscles and liver as well failure pancreatic beta cells . Purpose This research is to find out How extract ethanol leaf stalk palm affect the lipid values of diabetic rats. Type This research is a experimental . This research is divided into 6 groups with different treatment​ namely normal, control negative CMC-Na (0.5%), control positive glibenclamide (0.45mL), 125mg/kgBW extract , 250mg/kgBW extract and 500mg/kgBW extract . The results of the lipid parameter data were analyzed with SPSS 22 with level 95% confidence level Results study show extract ethanol dose 250 mg/kgBW and 500 mg/kgBW or more Lots lower level total cholesterol , triglycerides , and LDL as well increase HDL levels

This study aims to analyze the perspectives of mathematics students on mixing aloe vera extract with weak acid solution for hair health and softness. The research method used is descriptive quantitative through the distribution of questionnaires to 43 mathematics students at Medan State University and other universities in North Sumatra. The questionnaire consists of 19 statements covering aspects of knowledge (12 items), environmental awareness (4 items), and psychomotor (4 items) with a Likert scale of 1-5. The results showed that the majority of respondents had good knowledge about the benefits of aloe vera for hair care (mean = 4.02), but the understanding of weak acid solution and its mechanism of action was still moderate (mean = 3.12). The environmental awareness aspect showed a high value (mean = 3.76) which reflects the tendency of students to choose natural products. Meanwhile, the psychomotor aspect showed a moderate value (mean = 3.44), which indicates the limitations of respondents' skills in applying hair care products optimally. This study found a positive correlation between knowledge about natural ingredients and the tendency to use natural-based products for hair care. The results of this study are expected to be the basis for developing hair care product formulations based on natural ingredients that suit the needs and preferences of students.

This research analyzes user sentiment reviews of the KAI Access application from Google Play Store to improve customer service at PT Kereta Api Indonesia. The study uses a Natural Language Processing (NLP) approach with the Latent Dirichlet Allocation (LDA) algorithm to extract main topics from 10,000 reviews collected from April 2024 to April 2025. Analysis results show 40.7% positive sentiment reviews and 49.3% negative. After data preprocessing through case folding, normalization, tokenization, stopword removal, and stemming, seven optimum topics were found from negative sentiment with a coherence score of 0.508343 and two optimum topics from positive sentiment with a coherence score of 0.511673. Analysis based on five service quality dimensions (tangibles, reliability, responsiveness, assurance, and empathy) reveals that the reliability dimension becomes the main issue, including system instability, transaction failures, login difficulties, and data inaccuracy. The responsiveness dimension is the second priority, with users expecting fast and responsive service to complaints. The results of this study provide recommendations for PT KAI to prioritize improvements in system reliability and responsiveness aspects to enhance the overall user experience, which will ultimately impact customer satisfaction and loyalty.    

The development of information technology is also growing rapidly. One of the sectors that is also affected is transportation. This study aims to analyze the Influence of Trust, Online Customer Reviews, and Discounts on Purchasing Decisions Through Purchase Intention where the Intervening Variable is Gofood users on the Gojek application. The analysis method is quantitative primary data, with the test stages of convergent validity, Discriminant validity, average variance extracted (AVE), R-Square, predictive relevance (Q2), F-Square, path coefficient, specific indirect effect. Data were obtained through a questionnaire instrument, with a total of 175 respondents, which were then tested using SmartPLS 4.0. The research findings show that the Trust and Discount variables partially influence Purchasing Decisions through Purchase Intention of Gofood users on the Gojek application. Meanwhile, the Online Customer Review variable does not partially influence Purchasing Decisions through Purchase Intention of Gofood users on the Gojek application.

This study aimed to identify the secondary metabolite compounds present in the ethanol extract of Plukenetia volubilis L. (sacha inchi) shells through phytochemical screening and LC-MS analysis. The extraction was performed using the maceration method with 95% ethanol as solvent, resulting in a yield of 47.33%. Qualitative phytochemical tests revealed the presence of alkaloids, flavonoids, tannins, terpenoids, saponins, and glycosides in the extract. Further LC-MS analysis tentatively identified several phenolic and flavonoid compounds with known biological activities, including sinapinic acid, 1-o-sinapoylglucose, and azelaic acid from the dicarboxylic acid group. The presence of these compounds highlights the potential of sacha inchi shell extract as a natural antioxidant and antidiabetic agent. These findings support the valorization of sacha inchi agricultural waste as a promising raw material for pharmaceutical and nutraceutical applications.

Kombucha is one of the processed products of fermented sugar and tea with a starter mixture ofkombucha culture called SCOBY (Symbiotic Cultures of Bacteria and Yeast). Kombuchafermentation is carried out using yeast and bacteria microorganisms. Pomegranate or often calledpomegranate is a fruit that has quite high antioxidants. The purpose of this study was to determinethe characteristics of pomegranate juice kombucha with variations in concentration andfermentation time which have high antioxidant activity. This study used a factorial randomizeddesign with two factors and two repetitions. The factors used were variations in the percentage ofpomegranate juice (30%, 40%, and 50%) and fermentation time (7 days, 9 days, and 11 days). Thebest chemical and organoleptic analysis based on the highest antioxidant activity was 50%pomegranate juice treatment and 9 days of fermentation time with 71,10% antioxidant activity,total phenol 9,04 GAE/L, reducing sugar 2,45%, total acid 1,35%, pH 3,1 , anthocyanin 53.52%,lightness (L*) 44.72 , redness (a*) 5.15, yellowness (b*) 2.57, fruity aroma 2.27, sour taste 2,85, andfor overall preference 3,49 for the treatment of adding 50% pomegranate juice and 9 days offermentation time. Pomegranate extract able to improve activity of antioxidant for kombucha. 

In Indonesia, dry noodles are one of the most widely consumed foods because they are easy to cook. The use of banana flour as a substitute for making noodles is an effort to diversify food in reducing imports of wheat flour. This study dried noodles were made from katuk leaf extract and from the substitution of banana kepok flour with wheat flour. The chemical and organoleptic properties of noodles added with banana kepok flour and katuk leaf extract as natural dyes are the focus of this study. A two-factor factorial Complete Randomized Design (RAL) was used in this study, specifically the ratio of wheat flour to cocoon banana flour (5:95, 10:90, 15:85 g) and the concentration of katuk leaf extract (10/100, 20/100, 30/100 ml). The results showed that katuk leaf dried noodles the ratio of cocoon banana flour and wheat flour 5:95 with katuk leaf extract 30g/100ml contain an ash content of 3.43%; protein content of 14.72%; crude fiber of 11.11%; antioxidant activity of 17.32%; reduced sugar content of 0.24%. The organoleptic test results of dry noodles of katuk leaves compared to banana kepok flour and wheat flour 5:95 with katuk leaf extract 30g/100ml resulted in a stable green color with a score of 2.95 (quite like), aroma 2.52 (strong enough), taste 2.10 (quite like), and overall liking 2.99 (quite like). The highest antioxidant activity parameter was obtained with a ratio of banana kepok flour and wheat flour 15:85 with katuk leaf extract 30g/100ml with a yield of 23.07%. The noodles that the panelists liked the most were the ratio of banana kepok flour and wheat flour 5:95 with katuk leaf extract 30g / 100ml with a result of 2.99 (quite like). Dried noodles made from katuk leaves and banana kepok have high enough antioxidant activity so that they can become nutritious foods that also have beneficial values for body health.

Indonesia is rich in biodiversity, there are around 40,000 species of plants, and they have different uses,such as traditional medicine, can be made into handicrafts, used as decorations, used as natural dyes. Butterflypea flowers have the potential as a natural dye because the anthocyanins contained in their petals emit a bluecolor. The purpose of this study was to determine the anthocyanin content in butterfly pea flowers using themaceration extraction method which is commonly used to determine the best anthocyanin concentration. Thisstudy used a completely randomized factorial design (CRD), namely drying time, (fresh, 1, 2 days) andmaceration temperature (50, 60, 70oC), so that 9 combinations were obtained and each treatment was repeatedtwice. The results of this study indicate that the longer the drying time and the higher the macerationtemperature, the higher the levels of anthocyanin, total phenol, and the darker the color. The researchconducted showed that the best treatment combination was the drying time of 2 days with a macerationtemperature of 70°C to produce butterfly pea flower extract which had antioxidant activity of 54.66%, totalphenol 4.16 KTF (mgGAE/g), anthocyanin 123.48 mg/g, pH 6.03. Color sensory test analysis was 4.5 andwater content of butterfly pea flower was 10.79%. The optimal drying time and maceration temperature willproduce high total phenol and anthocyanin levels. Butterfly pea flowers have high levels of anthocyanins, sothey have the potential to be studied further. 

The National Health Insurance (JKN) program, administered by BPJS Kesehatan, has significantly expanded public access to healthcare services, particularly inpatient care. This study aims to analyze inpatient JKN reimbursement patterns at Surakarta General Government Hospital during the period of 2020 to 2024. The analysis focuses on five main variables: INA-CBGs grouping codes, class of care, severity level, INA-CBGs tariff, and actual hospital costs. A descriptive-analytic method with a quantitative approach was employed, utilizing secondary data extracted from the INA-CBGs system. The results indicate that inpatient reimbursements were predominantly concentrated in Class 3 services (64%–70%) and severity level 1 (45%–59%). From 2020 to 2022, respiratory-related cases dominated, likely due to the COVID-19 pandemic, while in 2023–2024 a shift occurred toward non-communicable diseases such as cardiovascular and metabolic conditions. A consistent negative tariff gap was identified, particularly in Class 3 and severity level 1, where INA-CBGs reimbursements were insufficient to cover actual service costs. These findings underscore the importance of periodic review of INA-CBGs tariff structures, reinforcement of Quality and Cost Control (KMKB), and optimization of reimbursement management information systems to enhance service efficiency and ensure the financial sustainability of JKN, especially in Type C hospitals that serve as the primary level of healthcare delivery.

The large number of cattle breeders in Indonesia has positive and negative values. Cattle farmers generally produce livestock waste such as cow rumen. Cow rumen can be used as a starter for alternative biogas energy production, and cabbage vegetable waste has the potential to be used as raw material for making biogas, because it contains nutrients such as crude protein (PK) 22.47%, crude fat (LK) 3.05%, crude fiber (SK) 12.09%, dry matter 10.22% and extract material without nitrogen 34.96%. Apart from that, in this research cow rumen and EM4 were also used as starters for the anaerobic fermentation process. The cow's rumen contains methane bacteria, namely Methanosarcina sp, and the cow's rumen also contains quite high levels of organic compounds with a COD value of 17,183 mg/l. Effective Microorganisms (EM4) are bacteria whose function is to accelerate the degradation process of organic materials. The aim of this research is to design a biodigester, and carry out biodigester design trials. The research methods carried out are COD analysis, CH4 analysis and pH analysis. The results showed that the percentage of CH4 increased in a mixture of 100% cow rumen, because the total COD value in the substrate was directly proportional to the addition of the cow rumen composition. This can be seen from the total COD in 100% beef rumen starter of 1175 ppm.  

The urgency of consumer protection in Sharia-compliant transactions has become increasingly prominent alongside the growth of the halal industry and rising public awareness of transactional justice based on Islamic principles. This study aims to formulate the theoretical and normative construction of consumer protection within the framework of Islamic law and to assess its compatibility with Indonesia’s positive legal system. Employing a normative juridical approach combined with a descriptive-analytical method, this research explores primary legal sources including Qur’anic verses, the hadiths of Prophet Muhammad (PBUH), and scholarly opinions found in classical and contemporary fiqh al-mu‘āmalāt literature, as well as secondary legal sources such as Law Number 8 of 1999 on Consumer Protection, fatwas of the National Sharia Council (DSN-MUI), and relevant academic literature. The analysis is conducted through content analysis to extract the values of justice, transparency, and balance of rights and obligations within contractual mechanisms. This study finds that core principles such as truthfulness (ṣidq), disclosure (bayān), and justice (‘adālah) constitute the essential foundation of consumer protection in the Islamic legal perspective. The prohibition of gharar (uncertainty), riba (usury), and tadlīs (fraudulent misrepresentation) is not merely a moral injunction but an integral safeguard mechanism for consumer rights. Furthermore, the institutional presence of supervisory bodies such as DSN-MUI and Sharia certification mechanisms has proven to be strategic, though they continue to face challenges in implementation, socialization, and consumer literacy. The findings also indicate a substantial opportunity for harmonizing Islamic legal principles with the national legal system within the framework of maqāṣid al-sharī‘ah. Therefore, this study recommends strengthening sectoral regulations based on Sharia principles, integrating fatwas into positive legal norms, and enhancing educational capacity for both business actors and consumers in order to realize ethical, equitable, and sustainable transactions.