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All Journal Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control INTERNATIONAL JOURNAL OF CULTURAL AND SOCIAL SCIENCE
Said, Naufal
Unknown Affiliation
Humanities Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

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DEVELOPMENT OF STUDENTS' RELIGIOUS TOLERANCE THROUGH RELIGIOUS ACTIVITIES IN PUBLIC JUNIOR HIGH SCHOOL 17 MEDAN Ayu, Melisa Gusti; Said, Naufal; Al Karim Rambe, Rahmansyah Fadlul
International Journal of Cultural and Social Science Vol. 5 No. 1 (2024): January
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/ijcss.v5i1.871

Abstract

The job of training in developing a demeanor of resilience among individuals is to depict a disposition of resistance in strict life among understudies. Strict variety is frequently expected to set off struggle inside a greater part bunch against a minority. In any case, the strict variety that is found in most of schools doesn't cause struggle in view of contrasts in strict foundations. The point is to recognize types of strict resistance in schools and examine educator systems in encouraging understudies' strict resilience. The execution of strict exercises with regards to shaping the personality of resilience among strict individuals, the personality of resistance between strict individuals is applied in the acts of other strict exercises that are felt to be viable. Since as well as giving the premise of strict lessons, understudies/understudies are likewise straightforwardly acquainted with genuine practice in building connections. correspondence with one another with different religions.
DEVELOPMENT OF STUDENTS' RELIGIOUS TOLERANCE THROUGH RELIGIOUS ACTIVITIES IN PUBLIC JUNIOR HIGH SCHOOL 17 MEDAN Ayu, Melisa Gusti; Said, Naufal; Al Karim Rambe, Rahmansyah Fadlul
International Journal of Cultural and Social Science Vol. 5 No. 1 (2024): International Journal of Cultural and Social Science
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/ijcss.v5i1.871

Abstract

The job of training in developing a demeanor of resilience among individuals is to depict a disposition of resistance in strict life among understudies. Strict variety is frequently expected to set off struggle inside a greater part bunch against a minority. In any case, the strict variety that is found in most of schools doesn't cause struggle in view of contrasts in strict foundations. The point is to recognize types of strict resistance in schools and examine educator systems in encouraging understudies' strict resilience. The execution of strict exercises with regards to shaping the personality of resilience among strict individuals, the personality of resistance between strict individuals is applied in the acts of other strict exercises that are felt to be viable. Since as well as giving the premise of strict lessons, understudies/understudies are likewise straightforwardly acquainted with genuine practice in building connections. correspondence with one another with different religions.
Improving Postprandial Glucose Forecasting using Diagnosis-Aware Stacked Learning Indriani, Fatma; Faisal, Mohammad Reza; Said, Naufal
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 11, No. 2, May 2026 (Article in Progress)
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v11i2.2566

Abstract

Predicting glucose levels after a meal (postprandial glucose) can help anticipate abnormal responses and improve diabetes management. Yet such prediction remains difficult because post-meal glucose depends on multiple interacting factors, including prior glucose trends, meal composition, and recent activity. This study develops machine learning models to forecast short-term post-meal glucose levels using the CGMacros dataset, which combines continuous glucose monitoring (CGM) data from Dexcom and Libre sensors with meal macronutrient annotations and activity measurements. Several feature combinations and regression models were evaluated to identify an optimal representation. Results show that combining baseline glucose statistics with meal composition yields the lowest error across all regressors. Building on this feature configuration, a stacked learning framework was implemented in which a global model provides initial predictions refined by diagnosis-specific CatBoost regressors for Healthy, Pre-diabetes, and Type 2 Diabetes groups. Across 18 configurations spanning two sensors and three horizons (30, 60, 120 minutes), stacking reduced normalized RMSE by 3.5% ± 3.7 on average, with the strongest improvements at 120-minute horizons (mean 5.5%) and for linear global models (up to 13.6% reduction). Gains varied by diagnosis group and sensor type, highlighting the importance of device-aware validation. These results demonstrate that diagnosis-aware stacking enhances both accuracy and robustness, offering a practical foundation for personalized glucose forecasting in digital health systems.
Co-Authors Al Karim Rambe, Rahmansyah Fadlul Ayu, Melisa Gusti Fatma Indriani Muhammad Reza Faisal, Muhammad Reza