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All Journal Sciencestatistics: Journal of Statistics, Probability, and Its Application SWARNA: Jurnal Pengabdian Kepada Masyarakat
Indah Suciati
Program Studi Matematika, Universitas Lampung, Indonesia
Religion Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Languange, Linguistic, Communication & Media Mathematics

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Workshop Pembuatan Media Pembelajaran dan Pengolahan Nilai bagi Guru SMK Nurul Huda Pringsewu Widiarti Widiarti; Asmiati Asmiati; Dian Kurniasari; Notiragayu Notiragayu; Warsono Warsono; Wenty Okzarima; Indah Suciati
SWARNA: Jurnal Pengabdian Kepada Masyarakat Vol. 3 No. 6 (2024): SWARNA: Jurnal Pengabdian Kepada Masyarakat, Juni 2024
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi 45 Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/swarna.v3i6.1315

Abstract

Sekolah Menengah Kejuruan (SMK) Swasta Nurul Huda Pringsewu memiliki empat jurusan, yaitu Asisten Perawat, Farmasi, Multimedia, dan Teknik Kendaraan Ringan dengan jumlah peserta didik sebanyak 205 Siswa dan guru sebanyak 30 orang. Berdasarkan data yang diperoleh hanya sekitar  28% lulusan SMKS Nurul Huda Pringsewu yang melanjutkan pendidikannya ke PT. Dengan demikian diperlukan adanya pembinaan terintegrasi untuk meningkatkan keinginan para siswa melanjutkan pendidikan ke PT.  Pengabdian ini menitik beratkan pada pembinaan komprehensif guru. Pembinaan guru meliputi pelatihan pembuatan media pembelajaran menggunakan Canva dan pengolahan nilai menggunakan Microsoft Excel. Kegiatan pengabdian ini mendapat sambutan  dan hasil yang baik dari para guru di SMK Swasta Nurul Huda Pringsewu. Berdasarkan hasil analisis statistik dengan menggunakan Uji T (T Test) menggunakan R Studio diperoleh bahwa nilai pre-test sebelum dilakukan workshop berbeda sangat signifikan dengan nilai post-test setelah dilakukan workshop.
Optimizing Breast Cancer Prediction by Applying Machine Learning Vina Nurmadani; Indah Suciati; Yoga Aji Sukma; Linda Rassiyanti
Sciencestatistics: Journal of Statistics, Probability, and Its Application Vol. 3 No. 2 (2025): JULY
Publisher : Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/sciencestatistics.v3i2.9667

Abstract

In 2015, breast cancer ranked among the most prevalent and fatal cancers affecting women globally. Artificial intelligence is urgently needed to help medical professionals make more accurate decisions, reduce overdiagnosis, and streamline the diagnostic process. This study will implement and perform a comparative study of selected machine learning techniques algorithms, with a focus on SVM, XGBoost, and ANN, with various parameter combinations on the breast cancer dataset. Performance metrics such as accuracy, precision, recall, and F1-score were employed to evaluate and compare the algorithms. The results of this study show that the best model for predicting chronic breast cancer disease, which can help medical professionals predict chronic disease so that it can be treated quickly and accurately, is the SVM method using 8 parameters without the mitosis parameter: Clump thickness, Cell Size Uniformity, Cell Shape Uniformity, Marginal Adhesion, Single Epithelial Cell Size, Bare Nuclei, Bland Chromatin, and Normal Nuclei, with an accuracy value of 0.96 and a sensitivity value of 0.98.
Co-Authors Asmiati Asmiati Dian Kurniasari Linda Rassiyanti Notiragayu Notiragayu Vina Nurmadani Warsono Warsono Wenty Okzarima Widiarti Widiarti Yoga Aji Sukma