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Jurnal Kridatama Sains dan Teknologi
Published by Universitas Ma'arif Nahdlatul Ulama
ISSN : 26566966     EISSN : 26856921     DOI : -
Core Subject : Science, Education, Agriculture, Social, Engineering,
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Social Sciences
Jurnal KRIDATAMA SAINS DAN TEKNOLOGI diterbitkan oleh Universitas Ma’arif Nahdlatul Ulama (UMNU) Kebumen Pendidikan (Education). Teknologi (technology), Penelitian (research). Bahasa Inggris (Language English), Bahasa Indonesia (Language Indonesian), Olahraga (Sport), Anak Usia Dini (early childhood education), Teknik Informatika (Technical Information), Teknik Sipil (civil Engineering). Pertanian (agriculture), Peternakan (animal husbandry).
Arjuna Subject : Umum - Umum
Articles 274 Documents
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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
Analisis Kapasitas Hidraulik Saluran Drainase Menggunakan Pemodelan Storm Water Management Model (SWMM): Studi Kasus di Kecamatan Banguntapan Arifin, Muhamad; Permatasari, Cahyaning Kilang
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.v8i01.2091

Abstract

Inundation is a major problem that frequently occurs in both residential areas and other urban zones, particularly in large cities. Flooding in residential areas is often caused by the failure of drainage channels to convey excess water. This condition commonly occurs when high rainfall intensity is not supported by adequate drainage capacity or when drainage channels are obstructed by solid waste. This study employs a mixed-methods approach, combining quantitative and qualitative methods. Identification was conducted through coordination with relevant stakeholders and direct observation of existing conditions at the study location. The analysis was carried out using hydraulic modeling of drainage channels with the SWMM 5.2 software. The results of the hydraulic modeling indicate that, in several locations, the drainage channel capacity is no longer sufficient and therefore requires capacity enlargement. Meanwhile, in locations where the channel capacity remains adequate, significant amounts of waste and sedimentation were found, causing blockages and reducing the effective capacity of the existing drainage system. To ensure the sustainability of the drainage system in Kapanewon Banguntapan, routine and periodic operation and maintenance activities are required, including rehabilitation of drainage channels that are already in deteriorated condition.
Studi Perbandingan Perilaku Balok Beton Tulangan Baja Konvensional dan Balok Beton Tulangan Glass Fiber Reinforced Polymer Ramadhani, Kharisma Dwi; Sabrina, Annisa Rahma; Bachtiar, M. Vicky Restu; Setiawan, Aviv; Pangestuti, Endah Kanti; Anggraini, Nurti Kusuma
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.v8i01.2107

Abstract

Reinforced concrete commonly uses conventional steel reinforcement due to its good tensile strength and ductility. However, steel reinforcement is susceptible to corrosion and has a relatively high self-weight. Glass Fiber Reinforced Polymer (GFRP) has emerged as an alternative reinforcement material with high tensile strength, low weight, and excellent corrosion resistance. This study aims to compare the flexural behavior of reinforced concrete beams using GFRP reinforcement and conventional steel reinforcement in terms of maximum flexural capacity, load–deflection behavior, and crack patterns. The research was conducted experimentally through laboratory testing using the two-point loading method. The test specimens were concrete beams measuring 150 × 150 × 600 mm, reinforced with either steel or GFRP bars with diameters of 6 mm and 8 mm. The results indicate that GFRP-reinforced beams exhibit higher maximum flexural capacity than steel-reinforced beams, with increases of 44.53% for 6 mm diameter bars and 15.65% for 8 mm diameter bars. In addition, GFRP-reinforced beams show greater deflection, indicating higher flexibility compared to steel-reinforced beams. Crack pattern observations reveal that GFRP-reinforced beams develop more numerous and widely distributed cracks and tend to experience shear failure, whereas steel-reinforced beams display more controlled flexural cracking. These findings suggest that GFRP reinforcement has significant potential as an alternative to conventional steel reinforcement, particularly for structures requiring high corrosion resistance and a high strength-to-weight ratio, while careful consideration of shear failure is necessary in design
Interaksi Air Tanah dan Air Permukaan Sungai Asem Ruas Antara Bendung Boreng sampai Area Industri Kabupaten Lumajang Widiyanti, Anisa Tri; Siswoyo, Hari; Prasetyorini, Linda
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.v8i01.2111

Abstract

The interaction between groundwater and river water is an important hydrological process that affects the quantity and quality of water resources. The purpose of this study was to identify and analyze the interaction between groundwater and surface water in the Asem River in the section between Boreng weir and the Industrial Area of Lumajang Regency. The study was conducted during the dry season, namely from May to October 2025. Sampling was carried out at 5 river cross-sections, each consisting of groundwater on the left side of the river flow, surface water (river), and groundwater on the right side of the river. The physical-chemical parameters observed included pH, temperature, TDS, and EC. The measurement data were analyzed using a statistical approach that included time series analysis, correlation analysis, principal component analysis, and cluster analysis. Based on the results of the time series analysis, it can be stated that there are similarities in the fluctuation patterns of physical-chemical parameters, especially temperature and pH, between groundwater and river water. Based on the results of the correlation analysis, it can be stated that the level of relationship is moderate to strong between groundwater and river water. Based on the results of the principal component analysis, it can be stated that the TDS and EC parameters play a dominant role in differentiating water characteristics. Based on the results of the cluster analysis, it can be stated that the interaction between groundwater and river water is not uniform along the river flow, with strong interactions identified in Cross Section-4 and Cross Section-5. In general, it can be concluded that at the research location there is an interaction between groundwater and river water which is influenced by local hydrological conditions

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