Claim Missing Document
Check
Articles

Found 7 Documents
Search

Penanaman TOGA dan Produksi Jamu untuk Peningkatan Kesehatan dan Ekonomi Desa Buahan Amritha, Yadhurani Dewi; Candrawengi, Ni Luh Putu Ika
Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Vol 7, No 3 (2024): Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstormin
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/japhb.v7i3.6750

Abstract

Meningkatnya harga obat-obatan modern menurunkan tingkat kesehatan pada masyarakat dan berdampak negatif terhadap kesejahteraan dan ketahanan negara secara keseluruhan. Pemerintah dan masyarakat harus mencari alternatifadengan memanfaatkan kembali potensi tanaman obat. Untuk meningkatkan kesehatan, pertumbuhan ekonomi, dan konservasi keanekaragaman hayati tanaman obat, penciptaan TOGA (tanaman obat rumah tangga) di desa merupakan bagian penting dari program pengelolaan keanekaragaman hayati tanaman obat. Kegiatan pengabdian masyarakat di desa Buahan dilakukan sebagai upaya untuk memberikan edukasi tentang TOGA kepada masyarakat sehingga dapat meningkatkan kemampuan masyarakat dalam pemanfaatan TOGA dalam kehidupan sehari-hari. Maka dari itu diperlukan upaya-upaya yang dapat meningkatkan kemampuan masyarakat dalam memanfaatkan TOGA dan selanjutnya dapat juga meningkatkan nilai ekonomi TOGA. Dengan pendekatan yang sistematis dan berkelanjutan, kegiatan penanaman TOGA dapat memberikan dampak positif yang signifikan bagi masyarakat desa, baik dari segi kesehatan, ekonomi, maupun sosial. Produk olahan TOGA nantinya dapat membantu perekonomian masyarakat. Memperoleh pengetahuan dan keterampilan dalam proses budidaya tanaman obat rumahan dapat dilihat sebanyak 85% peserta pelatihan dapat mengidentifikasi 10 jenis tanaman obat dan manfaatnya, tingkat partisipasi sangat tinggi yaitu 90% warga desa terlibat aktif dalam kegiatan penanaman dan perawatan kebun TOGA, pengolahan pasca panen menjadi produk jamu, dan pemasaran yang tepat akan membantu meningkatkan kuantitas produk jamu serta keberlangsungan pemasaran.
Membangun Kesadaran Pertanian Modern: Pendekatan Edukatif melalui Hidroponik untuk Siswa/I Sdn 6 Sesetan: Penelitian Amritha, Yadhurani Dewi; Yadhurani Dewi Amritha
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 3 No. 4 (2025): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 3 Nomor 4 (April 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v3i4.1084

Abstract

Artikel ini membahas rekonstruksi pemikiran Islam melalui telaah terhadap gagasan pembaruan yang dikembangkan oleh sejumlah tokoh Muslim modern dan kontemporer, seperti Jamaluddin al-Afghani, Muhammad Abduh, Fazlur Rahman, dan Nurcholish Madjid. Fokus utama kajian ini adalah bagaimana pemikiran-pemikiran mereka merespons tantangan zaman, baik dalam bidang keagamaan, sosial, maupun pendidikan. Dengan menggunakan pendekatan kualitatif melalui studi kepustakaan, artikel ini mengkaji prinsip-prinsip dasar pembaruan yang mereka usung, seperti rasionalisasi ajaran Islam, ijtihad kontekstual, dan pembaruan institusi pendidikan Islam. Berdasarkan uraian dan analisis terhadap pemikiran tokoh-tokoh pembaharu Islam seperti Jamaluddin al-Afghani, Muhammad Abduh, Fazlur Rahman, dan Nurcholish Madjid, dapat disimpulkan bahwa rekonstruksi pemikiran Islam merupakan kebutuhan mendesak dalam menjawab tantangan zaman modern. Para tokoh ini, dengan latar sosial dan pendekatan yang beragam, memiliki benang merah dalam upaya membangkitkan kembali nalar kritis, membebaskan umat dari belenggu taklid, dan mereformasi sistem pendidikan agar selaras dengan nilai-nilai keislaman yang dinamis dan kontekstual. Rasionalisasi ajaran agama, pembukaan pintu ijtihad, penguatan pendidikan integratif, serta penolakan terhadap formalisme dan dogmatisme merupakan tawaran strategis yang mereka ajukan demi menjadikan Islam sebagai agama yang mampu memberi jawaban atas persoalan kontemporer tanpa kehilangan identitas spiritualnya. Pemikiran mereka juga mencerminkan semangat untuk menjembatani antara tradisi dan modernitas, antara wahyu dan akal, serta antara otoritas teks dan pengalaman hidup umat.
Landasan Filosofis Ritual Bhuta Yadnya: Tinjauan Literatur Komprehensif tentang Konsep Keseimbangan dalam Praktik Caru dan Sesajen di Bali Anjani, Ni Ketut; Amritha, Yadhurani Dewi
Journal of Innovative and Creativity Vol. 5 No. 3 (2025)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Ritual Bhuta Yadnya, yang terwujud dalam praktik caru dan sesajen, merupakan pilar penting dalam kehidupan spiritual masyarakat Hindu Bali. Namun, pemahaman terhadap landasan filosofisnya sering kali tersebar dalam berbagai kajian. Penelitian ini bertujuan untuk melakukan tinjauan literatur yang komprehensif guna mensintesis dan menganalisis konsep keseimbangan yang menjadi dasar filosofis dari praktik Bhuta Yadnya. Dengan menggunakan metode studi kepustakaan (library research), sebanyak 20 artikel ilmiah yang relevan dianalisis secara tematik. Hasil analisis menunjukkan bahwa landasan utama praktik caru dan sesajen adalah implementasi dari ajaran Tri Hita Karana, yang bertujuan menjaga keharmonisan antara manusia dengan Tuhan (Parhyangan), sesama manusia (Pawongan), dan alam lingkungan (Palemahan). Literatur yang ada juga mengidentifikasi bahwa ritual ini memiliki kekayaan simbolis dalam setiap elemennya dan menjalankan spektrum fungsi yang luas, meliputi aspek religius, sosial, ekologis, ekonomi, dan sebagai penanda identitas budaya. Tinjauan ini menyimpulkan bahwa Bhuta Yadnya bukanlah sekadar tradisi, melainkan sebuah sistem filosofis yang kompleks dan dinamis untuk menjaga keseimbangan kosmis.
PENGARUH KETERLIBATAN PELANGGAN DAN KUALITAS PELAYANAN TERHADAP PERTUMBUHAN PENJUALAN MELALUI KEPUASAN PELANGGAN SEBAGAI VARIABEL MEDIASI PADA DAPURMAMIASRI Aristia, Iswara; Amritha, Yadhurani Dewi
Journal of Innovative and Creativity Vol. 6 No. 1 (2026)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/joecy.v6i1.5848

Abstract

his study aims to analyze the influence of customer engagement and service quality on sales growth mediated by customer satisfaction at DapurMamiAsri, a culinary business located in Sanur, Bali. The intense competition within the culinary sector, particularly in the tourism area of Denpasar, highlights the need for businesses to strengthen customer relationships and service strategies to sustain growth. This quantitative research involved 150 customers selected using Slovin’s formula through simple random sampling. Data were collected using a five-point Likert-scale questionnaire and analyzed with Partial Least Squares–Structural Equation Modeling (PLS-SEM). The findings show that customer engagement and service quality significantly and positively influence customer satisfaction. Customer satisfaction further enhances sales growth and mediates the relationship between customer engagement and service quality with sales growth. This research supports Relationship Marketing Theory by emphasizing the strategic role of engagement and service quality in developing customer satisfaction and driving business performance. Practically, the findings offer insights for culinary businesses to improve customer experience and strengthen competitive advantage.
Pendekatan Transformer Deep Learning dalam Meramalkan Harga Minyak Sumatran Light Crude Candrawengi, Ni Luh Putu Ika; Amritha, Yadhurani Dewi; Dananjaya, Md. Wira Putra
Jurnal Kridatama Sains dan Teknologi Vol 7 No 02 (2025): Jurnal Kridatama Sains dan Teknologi
Publisher : Universitas Ma'arif Nahdlatul Ulama Kebumen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53863/kst.v7i02.1993

Abstract

Time series forecasting plays an important role in understanding the dynamics of volatile data that depends on long-term historical patterns, such as crude oil prices. Parametric statistical approaches often face limitations due to strict assumptions, making nonparametric deep learning methods a more flexible alternative. This study proposes the application of a Transformer-based deep learning model to predict the price of Sumatran Light Crude Oil (SLC), utilizing a self-attention mechanism to capture long-term dependencies in time series data. Experiments were conducted by evaluating various configurations of multi-head attention and number of layers, while keeping the model dimensions and input-output windows consistent. The results show that the Transformer configuration with 16 heads and 4 layers provides the best performance with a Root Mean Square Error (RMSE) value of 8.19818. These findings indicate that Transformer is capable of effectively modeling long-term trends in SLC prices, although its sensitivity to short-term fluctuations is still limited. The main contribution of this research lies in the use of Transformer as an alternative approach to forecasting crude oil prices in Indonesia, which was previously dominated by statistical methods and recurrent models. In practical terms, the results of this study provide a basis for the development of a more adaptive oil price forecasting system to support energy analysis and data-driven decision making
Model Machine Learning yang Dioptimalkan untuk Prediksi Penyakit Jantung Menggunakan R Shiny Amritha, Yadhurani Dewi; Candrawengi, Ni Luh Putu Ika; Dananjaya, Md Wira Putra; Dayanti, Made Ari Riska
Jurnal Kridatama Sains dan Teknologi Vol 8 No 01 (2026): Jurnal Kridatama Sains dan Teknologi (In Progress)
Publisher : Universitas Ma'arif Nahdlatul Ulama Kebumen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53863/kst.v8i01.1994

Abstract

Heart disease continues to be a major contributor to global mortality, highlighting the critical importance of early detection in enhancing patient outcomes. The increasing availability of structured clinical datasets has enabled the application of intelligent systems for risk prediction and diagnostic support. In this paper, the effectiveness of three supervised learning algo- rithms—Random Forest (RF), Support Vector Machine (SVM), and Decision Tree (DT)—is evaluated for the task of heart disease prediction. This investigation is based on the Heart Failure Prediction dataset sourced from the Kaggle platform. The training process for each model involved a 10-fold cross- validation, with its hyperparameters later being tuned using grid search optimization. Model efficacy was measured against standard classification benchmarks, including accuracy, sensitivity, specificity, and the area under the ROC curve (AUC). The Random Forest model emerged as the most effective, demon- strating superior performance with an AUC of 0.9517, sensitivity of 81.18%, and specificity of 90.44%. To facilitate clinical use, this model was subsequently integrated into a user-friendly web tool built with the R Shiny framework. The interface allows users to input patient-level clinical data and obtain real-time predictions, along with visualizations of feature importance and risk probability. This implementation bridges the gap between algorithm development and practical application, offering a user- friendly decision support tool for early heart disease screening. The findings affirm that machine learning models, when properly tuned and validated, can serve as effective and interpretable tools in clinical decision-making. This work contributes to the advancement of e-health and the integration of AI-driven models into medical workflows
Human Intruder Detection System (IDS) for Restricted Security Area: A Systematic Literature Review Amritha, Yadhurani Dewi; Dipta, I Made Yogaswara
Jurnal Internasional Teknik, Teknologi dan Ilmu Pengetahuan Alam Vol 7 No 2 (2025): International Journal of Engineering, Technology and Natural Sciences
Publisher : Universitas Teknologi Yogyakarta, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46923/ijets.v7i2.457

Abstract

Ensuring security in sensitive areas such as airports, military bases, and nuclear facilities is critical to prevent unauthorized access. Traditional reliance on security personnel is often inefficient and insufficient for continuous monitoring. Intruder Detection Systems (IDS), which utilize devices or sensors to detect unauthorized entry, have emerged as essential tools for safeguarding high-security environments. However, there is a lack of comprehensive understanding that systematically synthesizes existing research on human intruder detection. This study aims to conduct a systematic literature review (SLR) on human IDS to provide a structured overview of current methodologies, technologies, and challenges in the field. Using established SLR protocols, relevant studies were collected, analyzed, and categorized to identify prevailing trends and gaps. The results highlight various object detection techniques and their effectiveness in real-world security applications. Despite the advances, challenges such as limited environmental adaptability and real-time accuracy remain. The findings of this review offer valuable insights for professionals and future researchers, guiding the development of more robust and efficient human intruder detection solutions.