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All Journal ADDIN Dinamika Kerajinan dan Batik: Majalah Ilmiah
Sahroni, Roni
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Religion Arts Engineering Environmental Science Industrial & Manufacturing Engineering Social Sciences

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Configuration of the Values of Al-Qur’an, Pancasila, and Mathematics: Critical Study of Integration-Based Analysis in Indonesia Wahidah, Evita Yuliatul; Abdillah, Syaik; Sahroni, Roni; Sirait, Sangkot; Kusumaputri, Erika Setyanti
ADDIN Vol 17, No 2 (2023): ADDIN
Publisher : LPPM IAIN Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21043/addin.v17i2.22487

Abstract

This paper presents about the values of Al-Qur’an, Pancasila, and Mathematics in the discourse on the theory of interconnection integration undergoing a demystification process. The configuration of the values of Al-Qur’an, Pancasila, and Mathematics through Islamic studies is carried out with a theo-anthropocentric process on the integralist values of Al-Qur’an to Mathematics, giving birth to six models, namely Mathematics for Al-Qur’an, Mathematics from Al-Qur’an, Mathematics to explore Al-Qur’an, Mathematics to deliver Al-Qur’an, Mathematics to explain Al-Qur’an, and Mathematics with Al-Qur’an. In integration, there is an effort to restructure Qur’anic and Mathematical sciences, while in interconnection there are meetings in the format of complementation, comparison, confirmation, and the contribution of the verses of Al-Qur’an to the five precepts of Pancasila.
Comparative RSM and ANN Modeling for Predicting Cotton Yarn Unevenness in Ring Spinning: Effect of Spacer Size and Cradle Pressure: Pemodelan RSM dan ANN Komparatif untuk Memprediksi Ketidakrataan Benang Katun pada Ring Spinning: Pengaruh Ukuran Spacer dan Tekanan Cradle Sahroni, Roni; Rival Firdaus, Muhammad; Putra, Valentinus Galih Vidia
Dinamika Kerajinan dan Batik: Majalah Ilmiah Vol. 43 No. 1 (2026): DINAMIKA KERAJINAN DAN BATIK : MAJALAH ILMIAH
Publisher : Balai Besar Standardisasi dan Pelayanan Jasa Industri Kerajinan dan Batik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22322/dkb.v43i1.8765

Abstract

This study developed and compared response surface methodology (RSM) and artificial neural network (ANN) models for predicting cotton yarn unevenness (U%) as a function of spacer size and cradle pressure in ring spinning. A 3×3 full-factorial experimental design was employed, yielding nine treatment combinations with 10 replicates each (90 samples total). Due to the limited dataset size (9 averaged data points), both models were fitted and assessed on the same data, with model performance interpreted accordingly. The RSM second-order polynomial model achieved R² = 0.98 (SSE = 0.0055), with sensitivity analysis identifying an optimal U% of 9.056% at a spacer size of 3.3 mm and cradle pressure of 1.53 N within the experimental domain [3.3–4.4 mm] × [1–2 N]. Notably, the unconstrained RSM optimum (x₁ = 2.638 mm) lies outside this domain, suggesting the experimental range may not fully bracket the true minimum. The ANN model, featuring a single hidden layer with four neurons trained via backpropagation over 10,000 epochs, achieved R² = 0.96 (MSE = 0.001942). Both models captured nonlinear input–output relationships, with RSM offering interpretable polynomial coefficients and ANN providing flexible data-driven mapping. A comparative analysis of predictive performance metrics (R², SSE, MSE) is provided, along with a discussion of model limitations related to dataset size and generalizability. These findings offer practical guidance for data-driven parameter optimization in ring spinning processes.
Co-Authors Abdillah, Syaik Erika Setyanti Kusumaputri, Erika Setyanti Evita Yuliatul Wahidah, Evita Yuliatul Putra, Valentinus Galih Vidia Rival Firdaus, Muhammad Sangkot Sirait, Sangkot