Garuda - Garba Rujukan Digital

Peningkatan Kemampuan Guru dalam Menggunakan Wolfram Cloud dalam Pembelajaran Matematika Dwi Nur Yunianti; Raden Sulaiman; Yuliani Puji Astuti; Budi Priyo Prawoto; Rudianto Artiono
Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Vol 5, No 2 (2022): 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.v5i2.3103

Penggunaan wolfram cloud diperlukan untuk mendukung keefektifan pembelajaran matematika selama masa pandemi Covid-19. Software ini dapat digunakan tidak hanya untuk menggambar grafik, visualisasi suara, menganalisa model bidang 3D tetapi juga dalam menyelesaikan permasalahan terkait kalkulus seperti persamaan kuadrat, turunan dan integral. Berdasarkan wawancara dengan beberapa guru matematika di MTsN 3 Jombang, 70% guru belum pernah menggunakan aplikasi wolfram cloud. Oleh karena itu mengingat pentingnya kompetensi guru dalam menguasai teknologi pada suatu pembelajaran maka kegiatan pelatihan wolfram cloud ini perlu diadakan. Berdasarkan hasil pre test dan posttest, terjadi peningkatan pemahaman tentang konsep persamaan kuadrat dan wolfram cloud yaitu dari rata-rata 41,4 menjadi 76,1. Selain itu, seluruh peserta pelatihan menyatakan kegiatan dapat menambah pemahaman terkait wolfram cloud dengan skor 4.46 (skala 5) dan dapat digunakan untuk pembelajaran matematika berbasis TPACK (Technological Pedagogical Content Knowledge) di sekolah dengan skor 4.23 (skala 5).

Pelatihan Penggunaan Software jBatik kepada Guru-guru MGMP Seni Budaya SMP Kabupaten Tulungagung Dimas Avian Maulana; Yusuf Fuad; Yuliani Puji Astuti
Abimanyu : Jornal of Community Engagement Vol 2 No 2 (2021): Agustus 2021
Publisher : Universitas Negeri Surabaya

Salah satu peninggalan budaya Indonesia yang menjadi primadona di seluruh dunia adalah batik. Batik adalah salah satu warisan budaya bangsa Indonesia yang mendapat pengakuan dari UNESCO sebagai Masterpieces of the Oral and Intangible Heritage of Humanity sejak tanggal 9 Oktober 2009. Seiring dengan perkembangan zaman, penciptaan batik tidak hanya melalui Teknik-teknik tradisional seperti teknik canting tulis, teknik tenun ikat, teknik cap, dan teknik colet saja. Dari survei awal kepada peserta, pengetahuan guru-guru Seni Budaya di Kabupaten Tulungagung mengenai penggunaan teknologi dalam membatik. Tujuan dari kegiatan pengabdian ini adalah meningkatkan pemahaman dan pengetahuan peserta mengenai batik fraktal secara khusus dan penggunaan software jBatik. Setelah dilakukan pelatihan, terdapat kenaikan yang signifikan dalam pengetahuan tentang batik fraktal dan penggunaan software jBatik yaitu 91% dan 82%.

Towards Sustainable and Trustworthy Digital Infrastructure: Benchmarking RSA and ECDSA Digital Signature Algorithms in Support of SDGs 9 and 16 Yuliani Puji Astuti; Ulfa Siti Nuraini
Journal of Current Studies in SDGs Vol. 2 No. 1 (2026): March
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jocsis.2.1.212

Objective: This study aims to evaluate and compare the performance of the Rivest–Shamir–Adleman (RSA) and Elliptic Curve Digital Signature Algorithm (ECDSA) digital signature schemes in terms of key generation, signing, verification, and storage efficiency. The research supports the advancement of secure digital communication systems aligned with Sustainable Development Goals (SDGs) 9 and 16, which emphasize innovation, resilient digital infrastructure, and trustworthy institutions. Method: A quantitative experimental approach was employed on a Windows AMD64 platform using Python. Five cryptographic configurations were evaluated: RSA-2048, RSA-4096, ECDSA P-256, ECDSA P-384, and ECDSA P-521. Performance tests were conducted on payload sizes of 1 KB, 10 KB, and 100 KB. Each cryptographic operation, including key generation, signing, and verification, was repeated 100 times to ensure measurement consistency and reliability. Results: The findings indicate that ECDSA significantly outperforms RSA in several performance aspects. ECDSA P-256 reduced signature storage requirements by 72.3%, generated keys nearly 13,000 times faster than RSA-2048, and signed 10 KB payloads approximately 48 times faster. ECDSA P-384 also demonstrated strong performance while providing a higher security level. Although RSA-2048 remains suitable for legacy systems, its efficiency is lower than ECDSA-based alternatives. Novelty: This study provides a comprehensive comparative evaluation of multiple RSA and ECDSA variants across different payload sizes and operational metrics, offering practical recommendations for selecting digital signature algorithms. The results highlight ECDSA P-256 as the optimal choice for 128-bit security requirements and ECDSA P-384 for applications requiring stronger 192-bit security.

Data-Driven Seismic Hazard Zonation of Indonesia to Support SDG 11 Using DBSCAN and K-Means Clustering Atik Wintarti; Fadhilah Qalbi Annisa; Harmon Prayogi; Yuliani Puji Astuti; Ibnu Febry Kurniawan
Journal of Current Studies in SDGs Vol. 2 No. 2 (2026): June
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jocsis.2.2.224

Objective: To examine ten years of earthquake data recorded across Indonesia drawing on 5,364 events with magnitudes above M 5.0 between 2016 and 2025. Method: DBSCAN algorithm was run after the optimal neighborhood radius was determined objectively from a k-distance plot. An elbow at about 65 km was identified and the value yielded 16 spatially distinct clusters alongside 460 noise events. K-means algorithm identified four seismic regimes. Results: Of the four regimes, one cluster (Cluster 1) concentrated every major earthquake in the catalog (64 events with M >= 7.0), even though it accounted for fewer than one event in ten. The three remaining clusters captured background seismicity at near-identical mean magnitudes of approximately from 5.33 to 5.35. At the conventional zonal level, Maluku-Sulawesi generated the most events about 40.8% from total events, while Sumatra registered the highest seismic energy output. A Gutenberg-Richter b-value of 0.98 was estimated for the full catalog. Novelty: Introducing earthquake zonation methods based on machine learning for earthquake catalog of Indonesia. These findings support multiple Sustainable Development Goals including the identification of underestimated high-energy rupture corridors informs evidence-based urban risk reduction (SDG 11), strengthens the scientific foundation for earthquake disaster preparedness (SDG 13), introduces an innovative and reproducible machine learning methodology applicable to infrastructure (SDG 9), and contributes a freely transferable workflow that adopt data-driven zonation methods (SDG 17)

Towards Sustainable and Trustworthy Digital Infrastructure: Benchmarking RSA and ECDSA Digital Signature Algorithms in Support of SDGs 9 and 16 Yuliani Puji Astuti; Ulfa Siti Nuraini
Journal of Current Studies in SDGs Vol. 2 No. 1 (2026): March
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jocsis.2.1.212

Objective: This study aims to evaluate and compare the performance of the Rivest–Shamir–Adleman (RSA) and Elliptic Curve Digital Signature Algorithm (ECDSA) digital signature schemes in terms of key generation, signing, verification, and storage efficiency. The research supports the advancement of secure digital communication systems aligned with Sustainable Development Goals (SDGs) 9 and 16, which emphasize innovation, resilient digital infrastructure, and trustworthy institutions. Method: A quantitative experimental approach was employed on a Windows AMD64 platform using Python. Five cryptographic configurations were evaluated: RSA-2048, RSA-4096, ECDSA P-256, ECDSA P-384, and ECDSA P-521. Performance tests were conducted on payload sizes of 1 KB, 10 KB, and 100 KB. Each cryptographic operation, including key generation, signing, and verification, was repeated 100 times to ensure measurement consistency and reliability. Results: The findings indicate that ECDSA significantly outperforms RSA in several performance aspects. ECDSA P-256 reduced signature storage requirements by 72.3%, generated keys nearly 13,000 times faster than RSA-2048, and signed 10 KB payloads approximately 48 times faster. ECDSA P-384 also demonstrated strong performance while providing a higher security level. Although RSA-2048 remains suitable for legacy systems, its efficiency is lower than ECDSA-based alternatives. Novelty: This study provides a comprehensive comparative evaluation of multiple RSA and ECDSA variants across different payload sizes and operational metrics, offering practical recommendations for selecting digital signature algorithms. The results highlight ECDSA P-256 as the optimal choice for 128-bit security requirements and ECDSA P-384 for applications requiring stronger 192-bit security.

Data-Driven Seismic Hazard Zonation of Indonesia to Support SDG 11 Using DBSCAN and K-Means Clustering Atik Wintarti; Fadhilah Qalbi Annisa; Harmon Prayogi; Yuliani Puji Astuti; Ibnu Febry Kurniawan
Journal of Current Studies in SDGs Vol. 2 No. 2 (2026): June
Publisher : Sekolah Tinggi Agama Islam Sabilul Muttaqin Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63230/jocsis.2.2.224

Objective: To examine ten years of earthquake data recorded across Indonesia drawing on 5,364 events with magnitudes above M 5.0 between 2016 and 2025. Method: DBSCAN algorithm was run after the optimal neighborhood radius was determined objectively from a k-distance plot. An elbow at about 65 km was identified and the value yielded 16 spatially distinct clusters alongside 460 noise events. K-means algorithm identified four seismic regimes. Results: Of the four regimes, one cluster (Cluster 1) concentrated every major earthquake in the catalog (64 events with M >= 7.0), even though it accounted for fewer than one event in ten. The three remaining clusters captured background seismicity at near-identical mean magnitudes of approximately from 5.33 to 5.35. At the conventional zonal level, Maluku-Sulawesi generated the most events about 40.8% from total events, while Sumatra registered the highest seismic energy output. A Gutenberg-Richter b-value of 0.98 was estimated for the full catalog. Novelty: Introducing earthquake zonation methods based on machine learning for earthquake catalog of Indonesia. These findings support multiple Sustainable Development Goals including the identification of underestimated high-energy rupture corridors informs evidence-based urban risk reduction (SDG 11), strengthens the scientific foundation for earthquake disaster preparedness (SDG 13), introduces an innovative and reproducible machine learning methodology applicable to infrastructure (SDG 9), and contributes a freely transferable workflow that adopt data-driven zonation methods (SDG 17)

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