Jurnal Online Universitas Ibrahimy
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Effectiveness of Giving Carrot Juice (Daucus Carota l) in Overcoming Nipple Crack and Clogged Milk Duct in Breastfeeding Mother
Get PDFExclusive breastfeeding remains difficult to achieve, with prevalence still falling short of national and global targets. One contributing factor is the discomfort experienced during nursing, such as nipple cracks and blocked milk ducts, which can reduce milk output and discourage continued breastfeeding. Carrot juice, rich in beta-carotene, vitamin A, and antioxidants, offers anti-inflammatory benefits that may accelerate healing, relieve pain, and prevent complications like mastitis. Given these properties, carrot juice is a simple, natural addition to postpartum care. Carrot juice should be given urgently to breastfeeding mothers as it contains beta-carotene and antioxidants that help reduce inflammation, relieve nipple pain, and prevent blocked milk ducts. This study aimed to determine the effectiveness of carrot juice (Daucus carota L.) in improving breastfeeding outcomes by reducing the incidence of nipple cracks and blocked milk ducts. A quasi-experimental design was used involving 15 breastfeeding mothers. Participants consumed 250 cc of freshly prepared carrot juice daily for seven days. Data were collected before and after the intervention using observation sheets and analyzed with the Wilcoxon test. The results showed a Z value of -3.41 (p=0.001) for nipple cracks and -3.29 (p=0.001) for blocked ducts. Both p-values (< 0.05) indicate significant improvement post-intervention. These findings confirm that regular consumption of carrot juice can effectively reduce the severity of nipple injuries and milk duct blockages. Carrot juice is a low-cost, accessible, and safe nutritional therapy that supports lactation. Further research is recommended to explore its mechanism of action and potential dosage optimization for broader clinical application
SISTEM INFORMASI ARSIP BERKAS PERKARA PIDANA UMUM KEJAKSAAN NEGERI PALANGKA RAYA
Get PDFCase files are very important documents in the Palangka Raya District Attorney\u27s Office which currently still applies conventional systems such as writing a combination of letters and numbers on physical archive files using Microsoft Excel. The unorganized archive storage space and the large number of case files that have not been computerized cause employees to have difficulty finding the case files when needed by the Prosecutor. This study aims to design and build a general criminal case file archiving system at the Kejaksaan Negeri Palangka Raya. This information system is made web-based using PHP language and MySQL database to replace the existing manual archiving method. Based on the results of the questionnaire responses, 82.5% of this system provides convenience in archiving and retrieving general criminal case files needed by the Prosecutor.Berkas perkara menjadi dokumen yang sangat penting di Kejaksaan Negeri Palangka Raya yang saat ini masih menerapkan sistem konvensional seperti menuliskan kombinasi huruf dan angka pada berkas fisik arsip menggunakan Microsoft Excel. Ruang penyimpanan arsip yang tidak tertata dan banyaknya berkas perkara yang belum terkomputerisasi ini menyebabkan pegawai terkendala dalam menemukan berkas perkara tersebut apabila dibutuhkan oleh Jaksa. Penelitian ini bertujuan untuk merancang dan membangun sistem pengarsipan berka perkara pidana umum pada Kejaksaan Negeri Palngka Raya. Sistem informasi ini dibuat berbasis web menggunakan bahasa PHP dan basis data MySQL untuk menggantikan metode pengarsipan manual yang ada. Berdasarkan hasil respon kuesioner menunjukkan 82,5% sistem ini memberikan kemudahan dalam pengarsipan dan pencarian kembali berkas-berkas perkara pidana umum yang dibutuhkan oleh Jaksa
Klasifikasi Image Kulit Wajah Berjerawat, Berminyak dan Kulit Sehat Menggunakan Teachable Machine Learning
Get PDFKulit wajah yang sehat merupakan kebutuhan penting bagi banyak individu, terutama dalam hal penampilan dan kesehatan. Namun berbagai masalah kulit seperti jerawat dan kulit berminyak tetap menjadi tantangan umum. Dengan kemajuan teknologi kecerdasan buatan, identifikasi kondisi kulit kini dapat dilakukan secara otomatis menggunakan pendekatan pembelajaran mesin. Penelitian ini bertujuan untuk mengembangkan model klasifikasi citra kulit wajah berdasarkan tiga kategori: kulit berjerawat, kulit berminyak, dan kulit sehat, menggunakan platform Teachable Machine oleh Google. Data citra dikumpulkan dari berbagai sumber keberanian, kemudian diberi label dan dibor secara manual menggunakan metode klasifikasi citra berbasis MobileNet V2. Dua percobaan dilakukan untuk membandingkan pengaruh ukuran dataset dan parameter pelatihan terhadap kinerja model. Percobaan pertama, menggunakan dataset terbatas, mencapai akurasi klasifikasi 94–96%, sedangkan percobaan kedua, menggunakan dataset yang lebih besar dan ukuran batch yang lebih tinggi, mencapai akurasi hingga 98–99%. Evaluasi menggunakan matriks gangguan menunjukkan bahwa model tersebut secara akurat mengklasifikasikan citra kulit wajah, terutama dalam kategori kulit berminyak. Studi ini menunjukkan bahwa Teachable Machine efektif sebagai solusi awal untuk diagnosis kondisi kulit wajah secara otomatis dan memiliki potensi untuk pengembangan lebih lanjut dalam aplikasi kecantikan dan dermatologi digital.Kondisi kulit wajah yang sehat menjadi kebutuhan penting bagi banyak individu, terutama dalam konteks penampilan dan kesehatan. Namun berbagai masalah kulit seperti jerawat dan kulit berminyak masih menjadi tantangan umum yang dihadapi. Seiring berkembangnya teknologi kecerdasan buatan, identifikasi kondisi kulit kini dapat dilakukan secara otomatis menggunakan pendekatan machine learning. Penelitian ini bertujuan untuk mengembangkan model klasifikasi citra kulit wajah berdasarkan tiga kategori: wajah berjerawat, wajah berminyak, dan kulit sehat, dengan memanfaatkan platform Teachable Machine dari Google. Data citra dikumpulkan dari berbagai sumber keberanian, kemudian dilakukan pelabelan manual dan pelatihan model menggunakan metode klasifikasi gambar berbasis MobileNet V2. Dua kali percobaan dilakukan untuk membandingkan pengaruh jumlah data dan parameter pelatihan terhadap kinerja model. Percobaan pertama menggunakan dataset terbatas menunjukkan akurasi klasifikasi sebesar 94–96%, sedangkan percobaan kedua dengan jumlah data yang lebih besar dan ukuran batch lebih tinggi menghasilkan akurasi hingga 98–99%. Hasil evaluasi menggunakan konfusi matriks menunjukkan bahwa model mampu mengklasifikasikan citra kulit wajah secara akurat, khususnya pada kategori kulit berminyak. Penelitian ini menunjukkan bahwa Teachable Machine efektif sebagai solusi awal dalam diagnosis kondisi kulit wajah secara otomatis, dan berpotensi dikembangkan lebih lanjut dalam bidang kecantikan serta aplikasi dermatologi digital
Deteksi Dini Terhadap Penyakit Tumor Otak Menggunakan Citra Magnetik Resonance Imaging (MRI) dengan Pendekatan Deep Convolutional Neural Network
Get PDFThis study aims to develop an early detection system for brain tumors using MRI images with a Deep Convolutional Neural Network (DCNN) based on the ResNet152V2 architecture. Rapid detection of brain tumors is crucial for improving recovery chances; however, manual processes often face challenges due to limitations in technology and medical expertise. Therefore, this research offers an automated solution for analyzing MRI images.The methods used include data collection from public datasets, image preprocessing, and training the DCNN model. The ResNet152V2 model was chosen for its ability to address the vanishing gradient problem and its effectiveness in feature extraction. The results show that the model achieved an accuracy of 92.38% in classifying four types of brain tumors: Meningioma, Glioma, Pituitary, and No Tumor. Evaluation using a confusion matrix and classification report indicates good performance. This research is expected to contribute to the early diagnosis of brain tumors and serve as a reference for future studies in the application of artificial intelligence in the medical field.Penelitian ini bertujuan mengembangkan sistem deteksi dini tumor otak menggunakan citra MRI dengan pendekatan Deep Convolutional Neural Network (DCNN) berbasis arsitektur ResNet152V2. Deteksi cepat tumor otak penting untuk meningkatkan peluang kesembuhan, namun proses manual sering terkendala oleh keterbatasan teknologi dan keahlian medis. Oleh karena itu, penelitian ini menawarkan solusi otomatis untuk analisis citra MRI. Metode yang digunakan mencakup pengumpulan data dari dataset publik, preprocessing citra, dan pelatihan model DCNN. Model ResNet152V2 dipilih karena kemampuannya mengatasi vanishing gradient dan efektivitas ekstraksi fitur. Hasil menunjukkan model mencapai akurasi 92,38% dalam mengklasifikasikan empat kelas tumor otak: Meningioma, Glioma, Pituitary, dan No Tumor. Evaluasi menggunakan confusion matrix dan classification report menunjukkan performa yang baik.Penelitian ini diharapkan dapat berkontribusi dalam diagnosis dini tumor otak dan menjadi referensi untuk penelitian selanjutnya dalam penerapan kecerdasan buatan di bidang medis
PERAN ULAMA DALAM KOMUNIKASI POLITIK LOKAL: STUDI STRATEGI DAN PENGARUH PADA PEMILIHAN KEPALA DAERAH
Get PDFMoral support and political communication in the local area have a huge influence on the victory of Regional Head candidates in Tapal Kuda. This research aims to analyze the role of ulama in local political communication, the strategies used, and their impact on the results of regional head elections. This research uses a qualitative approach with a case study method in two areas that have a strong religious culture, namely Probolinggo, Bondowoso, Jember and Situbondo Regencies. The results found were Moral Endorsement, namely ulama providing explicit support for certain candidates, often by linking the candidate\u27s character to religious values. Dissemination of Political Messages through religious lectures, mass mobilization, ulama mobilize their support base to attend campaigns and use religious networks to strengthen political support
MODERNIZING MOUNTAIN EDUCATION: ESTABLISHING A TECHNOLOGY-BASED ISLAMIC BOARDING SCHOOL TO ENHANCE LEARNING QUALITY
Get PDFEducation is the cornerstone of national development; however, access to education in remote areas of Indonesia remains limited. Pondok Pesantren (Islamic Boarding Schools), as long-established Islamic educational institutions, hold significant potential in addressing this disparity, particularly in hard-to-reach mountainous regions. This article examines the role of Pondok Pesantren Al Fatih As Syafii in empowering education in remote areas through the integration of technology. By utilizing technology, Islamic boarding schools can enhance the quality of education, reduce disparities, and expand access to information for students. Beyond education, these institutions also function as centers for social and economic development, nurturing the character and skills of students. The appropriate application of technology can strengthen Pondok Pesantren\u27s role in preparing a more competitive generation for the digital age. This research contributes to understanding how Pondok Pesantren can serve as key drivers in bridging the educational gap in remote areas and promoting a more inclusive, technology-enhanced learning environment
BUSINESS COMMUNITY EMPOWERMENT: BRANDING OPTIMIZATION, PRODUCT DIVERSIFICATION AND DIGITAL MARKETING
Get PDFThe Village SDGs are an effort to create a village without poverty and hunger, a village with an even economic growth, a women-friendly village, a networked village, and a culturally responsive village to accelerate the achievement of the Sustainable Development Goals. Dusun Krajan is one of the villages part located at the western tip of Jember Regency. This village is a village that has a variety of potential, both in terms of natural resource potential and the potential for an abundant population. However, this potential cannot yet be utilized optimally. Many residents of Tanggul Wetan Village are still below the poverty line. There are several business communities located in Tanggul Wetan village, especially in Karajan hamlet . Various potential factors and the conditions of the community in this village indicate a deep need to carry out empowerment programs. To achive the Tanggul Wetan Village SDGs, the service team carried out an analysis of the potential and problems that exist in Dusun Krajan. The problem is the knowledge of society especially in Dusun Krajan about how to build a good business is relatively low and there are no socialization or training about how to skill up their potential resources. Based on the results of the problem analysis, the service team from Jember University designed a community service activity, which was packaged in the form of training, guidance and mentoring. or the community to create a village without poverty and hunger. After this community service conducted, the knowledge of the society especially in Dusun Krajan about the branding optimization, product diversification and digital marketing increased
Integration of ethnomathematics in culturally responsive STEM education to foster computational thinking
Get PDFThis study aims to describe the implementation of culturally responsive STEM learning integrated with an ethnomathematics approach to enhance students’ computational thinking skills. The research employed a descriptive qualitative method and was conducted at SMA Zainul Hasan Genggong, involving 30 tenth-grade students (class X-A) and one mathematics teacher. Data were collected through observation, interviews, documentation, and bibliometric analysis using VOSviewer. The findings indicate that incorporating local cultural elements such as Madurese batik motifs, bamboo weaving, and traditional culinary units created meaningful and contextual learning experiences. Students showed clear progress in key components of computational thinking, including breaking down cultural tasks into smaller mathematical components, identifying geometric and symmetrical patterns in cultural artefacts, and developing structured steps to address practical problems. Both teachers and students responded positively, highlighting increased engagement, motivation, and collaboration during group projects. The teacher reported that students became more active, creative, and critical, while students expressed that learning felt more relevant and enjoyable. Word Cloud visualisation revealed dominant keywords such as culture, mathematics, patterns, symmetry, problem-solving, and collaboration, reflecting the strong connection between cultural contexts and STEM education. Bibliometric analysis further confirmed the interrelation between STEM, computational thinking, and contextual learning. These findings suggest that culturally rooted STEM learning not only enhances conceptual mastery but also fosters systematic, reflective, and creative thinking, positioning it as an effective strategy for addressing the challenges of 21st-century education
ANALISIS BUKU AL-MUMTAZ FI KHIWARATI AL YAUMIYAH DENGAN PRINSIP KEBAHASAAN AL-GHALI DAN ABDULLAH
Get PDFTextbooks are commonly used in formal and non-formal education. The preparation of textbooks needs to pay attention to the principles of textbook development so that the material presented is in accordance with the needs of students at each level to achieve educational goals. Al Mumtaz\u27s book is an Arabic language book published by a private institution which is not yet widely used in formal institutions such as state schools. The Al Mumtaz book is used in Arabic language learning which focuses on maharah kalam, this book is available in two formats, namely print and non-print which is used in online and face-to-face learning. The aim of this research is to reveal the suitability of the book Al-Mumtaz fi hiwaroti al yaumiyah lighoiri natiqina bil Arabiyah with the principles of developing linguistic aspect textbooks. This research uses library research with Harold and S. Laasswell\u27s analysis technique, namely content data analysis. The findings of this research indicate that the book Al-Mumtaz uses modern fushah Arabic as the language taught. There is no sound element that explains the differences in Arabic letters. The sentence structure of the book Al-Mumtaz is dominated by fi\u27liyah and ismiyah sentences with a language structure that is in accordance with nahwu rules. The compilation and writing of the book Al-Mumtaz was not accompanied by accompanying books, footnotes and endnotes, so it was not accompanied by accompanying books, footnotes and endnotes. not in accordance with the linguistic aspects of Al-Ghali and Abdullah
THE EFFECT OF SYAHRUL LUGHAH PROGRAM PLANNING ON IMPROVING ARABIC LANGUAGE COMPETENCE OF UINSI SAMARINDA STUDENTS: (George R. Terry\u27s Management Theory Perspective)
Get PDFThis study aims to describe the planning of the Syahrul Lughah Program at UINSI Samarinda and its influence on improving students’ Arabic language competence. The research focuses specifically on the planning aspect, as part of George R. Terry\u27s management theory, which includes objectives, strategy, scheduling, and preliminary evaluation. This study uses a quantitative approach with descriptive and inferential statistical analysis. Data were collected through questionnaires distributed to 120 students who participated in the program. The findings show that the planning of the Syahrul Lughah Program was well-structured, with clear goals and relevant learning strategies. Statistical analysis indicates a significant influence between planning quality and the improvement of students’ Arabic proficiency, with a coefficient of determination (R²) of 37.4%. Among the planning components, objectives and strategy had the strongest contribution to the program’s success, while preliminary evaluation scored the lowest, indicating a lack of standardized assessment of participants\u27 initial abilities. The study concludes that effective planning is a crucial determinant in the success of Arabic language programs. Strengthening the evaluation phase and refining the implementation schedule are recommended to maximize learning outcomes in similar intensive programs