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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi Journal of Applied Data Sciences Shof Journal of Social Impact
Awawin Mustana Rohmah
Universitas Islam Darul 'Ulum
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Mathematics

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Empowering Karangtaruna Of Ngasemlemahbang Village Through Gamelan Training To Preserve Local Culture Rifky Ardhana Kisno Saputra; Awawin Mustana Rohmah; Zuhro Nurmala M.R; M Najib Alif R.; Miftakhul Jannah
Shof Journal of Social Impact Vol. 1 No. 2 (2024): August
Publisher : Shof Literacy Community

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Abstract

Music is believed to have the power to represent the culture of a person or group at a certain time. He is considered to have a basic understanding of ideas, determining methods and actions in every note produced. The color of sound, range of notes and musical production in each region have many differences. Because in essence, music is a work of art which contains aesthetic symbols from every culture in different societies. Gamelan is a musical instrument that represents or depicts the culture of Javanese society. Some Javanese gamelan in the Surakarta, Yogjakarta and Cirebon palaces include Kyai Guntur Madu, Kyai Guntur Sari, Kyai Naga Wilaga and Gong Sekati. This orchestra has a pentatonic scale in the slendro scale system and pelog scale system. Each gamelan has an honorary name befitting a sacred heirloom. slendro on the gamelan used as the research sample. Meanwhile, the independent variables are the frequency and color of the sound for each area.
Assistance in Learning to Count for SDN Ngimbang Students through Singing Siti Alfiatur Rohamaniah; Novita Eka Chandra; Awawin Mustana Rohmah; Sinta Nurjanah Ely; Ani Habibatun Nisa; Alda Dwi Valentino
Shof Journal of Social Impact Vol. 1 No. 2 (2024): August
Publisher : Shof Literacy Community

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Abstract

This activity aims to assist students learning to count who are still experiencing difficulties at Ngimbang State Elementary School. Mastery of mathematical calculations at a basic level is very important as an effort to build a strong foundation in understanding basic mathematics. This community service uses the singing method. The results of this service were attended by 30 grade 1 students, with 20 students able to count well and 10 students who were still lacking. This mentoring activity was carried out well. Students were very enthusiastic about following it. This service is a community service that aims to improve the numeracy skills of grade 1 students through the use of singing as a fun and interactive learning approach. It can be seen that grade 1 students who previously had absolutely no understanding of counting, have now made significant progress. The use of singing media is a very effective and exciting learning method for improving numeracy skills for elementary school students.
Minor-Eigenvalue Spectral Analysis in Intuitionistic Fuzzy Soft Sets for Multicriteria Decision Making Silfiatis Sabila Azra Shofa; Siti Amiroch; Awawin Mustana Rohmah
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.41247

Abstract

Multi-criteria decision making (MCDM) under uncertain data requires a framework capable of capturing ambiguity and non-linear interactions among criteria. This study develops an Intuitionistic Fuzzy Soft Set (IFSS)-based MCDM model using spectral analysis of aggregation matrices constructed with the Einstein operator. Unlike approaches that rely mainly on global eigenvalues, the proposed method utilizes dominant eigenvalues of principal minors to capture local structural variations among alternatives. The method is validated using subdistrict-level economic facility data from Lamongan Regency. The results produce spectral scores ranging from 0.0683 to 2.0000, with Bluluk obtaining the lowest score and Lamongan obtaining the highest score. Several alternatives with comparable global structural characteristics also exhibit distinct minor-eigenvalue responses, indicating that the proposed approach can reveal local structural variations that may not be reflected in global spectral analysis. These findings suggest that minor-eigenvalue-based spectral analysis provides an alternative local perspective for distinguishing alternatives within the IFSS framework. The proposed framework contributes theoretically to IFSS-based spectral modeling and practically supports decision-makers in prioritizing subdistrict development based on local structural characteristics.
Newton Divided Difference Optimization for Fingerprint-Based Neural Virtual Screening against Avian Influenza A/H9N2 Siti Amiroch; Mohammad Jamhuri; Awawin Mustana Rohmah; Mohammad Hamim Zajuli Al Faroby; Chairul Anwar Nidom; Reviany Vibrianita Nidom
Journal of Applied Data Sciences Vol 7, No 3: September 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i3.1416

Abstract

Avian influenza A/H9N2 poses persistent zoonotic and veterinary threats, yet efficient computational tools for antiviral compound prioritization remain underdeveloped, particularly with respect to optimizer behavior in high-dimensional neural screening. This study proposes Newton Divided Difference (NDD) optimization, a lightweight positive diagonal curvature-aware training strategy, as a novel optimizer for fingerprint-based neural virtual screening against avian influenza A/H9N2, with the objective of evaluating its performance across aligned molecular fingerprint representations and chemically structured validation protocols. An aligned benchmark of 1,459 molecules consisting of 615 candidate active compounds and 844 decoys was represented by EState (79 features), PubChem (881 features), and Klekota–Roth (4,860 features) fingerprints, sharing identical molecule identities, labels, and split assignments. A fixed multilayer perceptron (MLP) classifier was trained with NDD and seven baseline optimizers under stratified, scaffold-key, and similarity-cluster split protocols across five repeated seeds. NDD achieved the highest descriptive ROC-AUC (Receiver Operating Characteriztic – Area Under the Curve) and PR-AUC (Precision-Recall Area Under the Curve) on Klekota–Roth fingerprints under scaffold-key and similarity-cluster protocols, and remained competitive under the stratified split with ROC-AUC of 0.9872. Architecture-sensitivity tests confirmed stable NDD performance across multiple network configurations, with ROC-AUC values ranging from 0.9876 to 0.9890. Compared with Hessian-free optimization, NDD reduced per-run runtime from approximately 50–54 seconds to approximately 8 seconds on Klekota–Roth under the same CPU-only configuration while achieving comparable ranking performance. The novelty of this work lies in the first systematic assessment of NDD for H9N2 neural virtual screening, demonstrating that positive diagonal curvature-aware scaling provides a practical, stable, and computationally efficient optimization alternative in sparse high-dimensional ligand-based screening settings, although external validation and prospective experimental confirmation remain necessary before practical antiviral prioritization.
Co-Authors Alda Dwi Valentino Ani Habibatun Nisa Chairul Anwar Nidom M Najib Alif R. Miftakhul Jannah Mohammad Hamim Zajuli Al Faroby Mohammad Jamhuri Novita Eka Chandra Reviany Vibrianita Nidom Rifky Ardhana Kisno Saputra Silfiatis Sabila Azra Shofa Sinta Nurjanah Ely Siti Alfiatur Rohamaniah Siti Amiroch Zuhro Nurmala M.R