eJournal PoliTekniK TEGAL (Politeknik Harapan Bersama Tegal)
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EFFECTIVENESS OF RED BETEL LEAF (PIPER CROCATUM) IN REDUCING SYMPTOMS OF FLUOR ALBUS IN WOMEN OF REPRODUCTIVE AGE
No full textFluor albus is the presence of Trichomonas vaginalis and Candida albicans bacterial infections. Fluor albus itself is an excessive discharge from the vagina that is not menstrual blood. Red betel leaf is one of the potential medicinal plants that is empirically known to have properties to cure various types of diseases, including fluor albus. This research method employs a quantitative design, specifically the randomized pretest post-test control group design. The subjects selected in this study were women of childbearing age in Islamic boarding schools. The number of samples was 40 people. The data analysis used was univariate and bivariate using the sample t-test. Based on the results of statistical analysis using the t-test, a p-value of 0.000 0.05 was obtained. The result shows that Ho is rejected and Ha is accepted. So it can be concluded that there is an effect of boiled red betel leaf water (piper crocatum) on reducing fluor albus symptoms in women of childbearing age
THE RELATIONSHIP BETWEEN KNOWLEDGE AND ATTITUDES OF ADOLESCENTS IN EFFORTS TO PREVENT ADOLESCENT PREGNANCY
No full textA critical issue during adolescence is reproductive health, particularly teenage pregnancy. One of the factors contributing to teenage pregnancy is the low level of knowledge among adolescents about sexuality and reproductive health, which can lead to negative behaviors. Adolescents' knowledge and attitudes are crucial in efforts to prevent teenage pregnancy. This study aims to determine the relationship between adolescents’ knowledge and attitudes in preventing teenage pregnancy. This research consists of three stages: preparation, implementation, and evaluation. The study was conducted at MA Al-Ihsan, Pondok Gede, over an effective period of three weeks in August 2024. The research method used was quantitative with a cross-sectional approach. The data used in this study were primary data, collected from 99 students (both male and female) at MA Al-Ihsan, using total sampling. The data analysis technique applied was the Chi-Square test. The results of the study indicate that knowledge plays a significant role in shaping adolescents' attitudes toward preventing pregnancy. These findings highlight the importance of early reproductive health education. In conclusion, there is a significant relationship between knowledge and adolescents’ attitudes in the effort to prevent teenage pregnancy
DESCRIPTION OF PHYSICAL ACTIVITY AMONG MIDWIFERY STUDENTS
No full textPhysical activity includes all movements, ranging from daily activities, moving from one place to another, work-related activities, and physical activities of low, moderate, and high intensity. Women in Indonesia tend to have a sedentary lifestyle or engage in physical activities at a low-intensity level. This study aims to describe the physical activity of midwifery students at Universitas ‘Aisyiyah Yogyakarta. This research employs a quantitative method with a cross-sectional approach. The sample consists of 52 midwifery students selected through purposive sampling. Data collection was conducted using a questionnaire, and data analysis utilized univariate analysis. The results indicate that most midwifery students at Universitas ‘Aisyiyah Yogyakarta engage in moderate physical activity, with 26 respondents (50%), while the least engage in high-intensity physical activity, with only 6 respondents (11.5%). It is recommended that students increase their physical activity, particularly through exercise
Developing a Web-based MSME Sales Revenue Data Management and Reporting Portal Using OAuth 2.0
No full textThe Cooperatives and SMEs Service (DinKopUKM) under the Ministry of Cooperatives and SMEs play a vital role in coordinating the implementation of tasks, coaching and providing administrative support for MSMEs. In this research, a portal for managing MSME data and Sales Revenue reporting was carried out to support transparent information management, monitoring MSME business implementation, and encouraging orderly administration in MSMEs so as to optimize efforts to empower MSMEs. The portal was developed using Laravel technology for the backend and NextJS for the frontend, with a responsive web design so that it can be accessed from various devices. Apart from that, to support data integration and data communication with resources that have been built in previous research, OAuth 2.0 was implemented. The development process is in accordance with the Prototyping process model. The portal developed was tested using the black box testing method. It was found that this portal was in accordance with the needs and design of the system. The portal developed helps DinKopUKM in carrying out its duties of data collection on MSMEs, monitoring MSMEs, and encouraging MSMEs to maintain orderly administratio
Dinamika Opini Publik Terkait Quarter Life Crisis Pada Media Sosisal X Menggunakan Support Vector Machine
No full textThis study aims to analyze the dynamics of public opinion related to quarter life crisis on platform X through a sentiment analysis approach based on machine learning Support Vector Machine (SVM) algorithm is used to classify positive and negative sentiments from text data. A total of 6.312 tweets were collected with the keyword “quarter life crisis” from January 2024 to January 2025. The data was then processed through the stages of text cleaning, tokenization, stopword removal, stemming, and lexicon-based sentiment labeling. The classification process is carried out using SVM with a data division of 80% training and 20% test. The results showed an accuracy of 81.57% with a sentiment distribution of 59.3% negative and 40.7% positive. Implementation was done on Google Colab platform with evaluation using confusion matrix and classification report. The fingdings prove the effectiveness of SVM in analyzing psychosocial phenomena on social media and provide an empirical basis for the development of digital data-based mental health interventions. The machine learning pipeline optimized in this study can be used as a reference for other studies in analyzing psychological phenomena on social medi
Implementasi Naïve Bayes untuk Rekomendasi Pembelian Produk pada Aplikasi E-commerce
No full textElectronic commerce (e-commerce) is a platform that influences buying and selling habits in Indonesia, with data from the Central Statistics Agency 2023 showing 31,753 e-commerce businesses using consumer review data as a determinant of product and service quality. This research aims to develop a sentiment-based product recommendation system using the Naïve Bayes algorithm. The research methodology includes collecting 1,287 data samples obtained from customer reviews using Web Scraper technology on the official MSI Official Store e-commerce platforms in the Tokopedia, Shopee, and Blibli applications. The results of data preprocessing yielded 921 clean data, and the Naïve Bayes Algorithm was applied as a classification model and system implementation in a website application. The data was then divided into 80% for training and 20% for testing. Model evaluation showed an accuracy of 82% for training data and 71% for testing data. These results indicate the effectiveness of the Naïve Bayes algorithm in forming a sentiment-based product recommendation system. This recommendation system helps users make more informed purchasing decisions based on consumer sentiment analysis. This research contributes to the development of intelligent recommendation systems that can improve user decision-making in the digital marke
Design and Implementation of IoT-Based Smart Election Using ESP32 and RFID
No full textThis research aims to design and implement a smart election system leveraging Internet of Things (IoT) technology through the integration of the RFID RC522 module, ESP32 microcontroller, and the MQTT communication protocol, with the goal of improving the efficiency, transparency, and security of the voting process. The research adopts a prototyping approach consisting of four main stages: requirement analysis, system design, performance evaluation, and refinement leading to final implementation. The system enables voter authentication through e-KTP verification using RFID sensors, which is cross-checked against a centralized database. Voting data are transmitted securely via the MQTT protocol and displayed in real-time through a Node-RED dashboard, allowing for continuous monitoring and rapid vote recapitulation. Experimental results indicate a 100% accuracy rate in UID verification, prevention of duplicate voting, and stable system responsiveness. The platform significantly reduces human intervention and the risk of vote manipulation, supporting the credibility and auditability of election results. In conclusion, the proposed IoT-based smart election prototype offers an efficient, scalable, and user-friendly technological solution suitable for local deployment. Future improvements may include the integration of cryptographic techniques, cloud-based data storage, and biometric authentication to enhance system robustness and security
Analisis Forensik Digital terhadap Kasus Penipuan pada E-Commerce Menggunakan Metode ACPO
No full textAbstrak – Perkembangan e-commerce berbasis media sosial telah meningkatkan risiko kejahatan siber, terutama kasus penipuan yang dilakukan di luar sistem resmi platform. TikTok Shop menjadi salah satu platform yang paling banyak digunakan, tetapi maraknya transaksi di luar sistem menimbulkan tantangan dalam investigasi kejahatan digital. Penelitian ini bertujuan untuk menganalisis efektivitas metode ACPO (Association of Chief Police Officers) dalam proses investigasi forensik digital guna mengidentifikasi dan mengamankan bukti elektronik terkait kasus penipuan pada e-commerce berbasis media sosial. Penelitian dilakukan dengan pendekatan eksperimental menggunakan Belkasoft dan MOBILedit Forensic Express untuk mengekstraksi bukti digital dari perangkat seluler. Dataset awal terdiri dari 2 akun, 2 gambar, 1 video, dan 8 percakapan pesan, sehingga total terdapat 13 bukti digital. Hasil pengujian menunjukkan bahwa Belkasoft berhasil mengekstraksi gambar dan video (100%) tetapi gagal memperoleh akun serta percakapan pesan, sedangkan MOBILedit Forensic Express berhasil mengekstraksi seluruh bukti (100%) kecuali video. Dengan menerapkan prinsip ACPO, memastikan penyelidikan bahwa seluruh bukti digital dikumpulkan secara sistematis dengan tetap menjaga integritasnya agar dapat digunakan dalam proses hukum. Hasil penelitian ini menunjukkan bahwa metode ACPO dapat diimplementasikan secara efektif dalam analisis forensik digital guna mendukung investigasi kejahatan siber di platform e-commerce berbasis media sosial. Penerapan metode ini berkontribusi dalam meningkatkan efektivitas investigasi dan validitas bukti digital dalam sistem peradilan.
FACTORS INFLUENCING COLOSTRUM PROVISION AMONG POST-CESAREAN MOTHERS
No full textColostrum provision is a vital effort in reducing infant mortality, as it contains essential nutrients and antibodies for newborns. However, post-cesarean mothers are at greater risk of delayed or absent breastfeeding initiation due to postoperative discomfort. This study aimed to identify the factors influencing colostrum provision among post-cesarean mothers at RSI Al-Ikhlas Pemalang, focusing on age, education, knowledge, parity, and family support. A quantitative analytical method with a cross-sectional design was employed. Data were collected through structured questionnaires from 66 post-cesarean mothers. Bivariate analysis using the chi-square test revealed that education, knowledge, and family support significantly influenced colostrum provision (p 0.05), whereas age and parity did not show a significant relationship (p 0.05). Furthermore, multivariate analysis using logistic regression identified family support as the most dominant factor affecting colostrum provision. The findings highlight the importance of strengthening educational interventions and fostering family involvement to support early breastfeeding practices in post-cesarean mothers. In conclusion, education, knowledge, and particularly family support plays crucial roles in ensuring the successful provision of colostrum, with family support emerging as the most influential factor. Health professionals are encouraged to engage families as active participants in promoting optimal breastfeeding practices
Segmentasi Citra Daun Tomat untuk Klasifikasi Penyakit Tanaman Menggunakan Support Vector Machine (SVM)
No full textTomatoes are one of the most widely grown crops worldwide. In Indonesia, particularly in West Sumatra, tomato production has declined. This is due to extreme weather conditions and plant disease outbreaks. One solution to help with early identification of tomato plant diseases is through digital image-based classification. This process involves several important stages, starting from image acquisition, preprocessing, segmentation, feature extraction, and classification. However, the quality of classification is highly dependent on the effectiveness of segmentation in separating leaf objects from the background. This study proposes a method for segmenting tomato leaf images based on a combination of color thresholding techniques, morphological operations, contour filtering, and bitwise masking to ensure that only the leaf parts are processed further. After undergoing the segmentation process, images are extracted based on color characteristics in HSV space and GLCM texture, then further processed using an SVM algorithm with an RBF kernel. The dataset used consists of 4000 tomato leaf images with an 80% training and 20% testing data division scheme, accompanied by 5-fold cross validation. The model achieved an accuracy of 96.97% on the training data and 93.75% on the testing data. The results show that segmentation methods using color thresholding, morphology, contours, and bitwise masking can help improve the consistency of extracted features, thereby potentially supporting more stable classification performance