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All Journal Jurnal Simetris Scientific Journal of Informatics Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Teknologi dan Sistem Komputer SISFOTENIKA Jurnal Sisfokom (Sistem Informasi dan Komputer) Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal PkM (Pengabdian kepada Masyarakat) ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Brilliance: Research of Artificial Intelligence Jurnal Abdimastek (Pengabdian Masyarakat Berbasis Teknologi)
Harrizki Arie Pradana
ISB Atma Luhur
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Nursing Public Health Social Sciences Other

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PENGGUNAAN MICROSOFT OFFICE DI KECAMATAN GABEK Agus Dendi Rachmatsyah; Marna Marna; Harrizki Arie Pradana; Benny Wijaya
Jurnal Pengabdian Masyarakat Berbasis Teknologi Vol 1, No 1 (2020): APRIL 2020
Publisher : ISB Atma Luhur

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Abstract

Kewajiban setiap Perguruan Tinggi sebagaimana dijelaskan dalam Tridarma Perguruan Tinggi adalah melakukan Pendidikan, Penelitian, dan Pengabdian kepada Masyarakat. Sebagai pelaksanaan salah satu darma perguruan tinggi dosen-dosen kemudian melaksanakan kegiatan pengabdian kepada masyarakat. Saat ini pengabdian kepada masyarakat yang dilakukan berupa bimbingan teknis penggunaan Microsoft office bagi aparatur di kecamatan Gabek. Pelaksanaan pengabdian kepada masyarakat diawali dengan persiapan yang dilakukan oleh dosen terkait penentuan lokasi dan mekanisme pelaksanaan pengabdian kepada masyarakat. Dosen dengan dibantu beberapa orang mahasiswa kemudian memberikan bimbingan teknis terkait beberapa materi mengenai penggunaan Microsoft office untuk menunjang pelaskanaan tugas para aparatur pemerintahan di kecamatan Gabek. Dengan telah dilaksanakannya bimbingan teknis dapat memperkaya wawasan dan menambah kemampuan para aparatur pemerintahan di Kecamatan Gabek dalam penggunaan aplikasi pengolah kata dalam menunjang pelaksanaan tugas mereka
Ablation-Based Machine Learning Framework for Body Mass Index Classification Sechdyna Aura Tursyna; Harrizki Arie Pradana
Brilliance: Research of Artificial Intelligence Vol. 6 No. 3 (2026): Brilliance: Research of Artificial Intelligence, Article Research August 2026
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v6i3.8851

Abstract

Body Mass Index (BMI) status classification can support population screening, but the relative predictive value of survey-based behavioral data and laboratory biomarkers remains unclear. This study develops an ablation-based health analytics framework to quantify the contribution of these feature domains and a derived lifestyle profile. Nineteen NHANES 2021–2023 component datasets were integrated, producing an analytical sample of 3,631 adults aged 18–80 years. The four-class target comprised Underweight, Normal, Overweight, and Obese categories; predictors included 28 behavioral and 11 biomarker variables. A two-stage framework applied K-Means lifestyle profiling to training data and Gradient Boosting classification across five controlled ablation configurations. Missing data processing, scaling, and Gaussian noise-augmented oversampling were fitted or applied only to the training set to minimize leakage. The primary two-stage full model achieved an AUC of 0.700 (95% CI: 0.643–0.751), accuracy of 0.556, macro F1 of 0.407, and Cohen’s kappa of 0.329. The biomarker-only configuration obtained the highest AUC (0.713), while the behavioral-only model retained moderate discrimination (AUC=0.635). The lifestyle cluster added only 0.002 AUC. Permutation importance identified diastolic blood pressure, uric acid, HDL cholesterol, alanine aminotransferase, and albumin as leading predictors, and a three-class formulation increased macro F1 to 0.545. The results indicate that biomarkers should be prioritized when laboratory resources are available, whereas behavioral variables remain useful for preliminary screening in lower-resource settings.
Co-Authors Agus Dendi Rachmatsyah Benny Wijaya Dwi Yuny Sylfania Fitriyani Fitriyani Fransiskus Panca Juniawan Fransiskus Panca Juniawan Hamidah . Hariska Hariska Kirana, Chandra Laurentinus, Laurentinus Lukas Tommy Marisa Marisa Marna Marna Melati Suci Mayasari, Melati Suci Muslifah Muslifah Okkita Rizan Rahmat Sulaiman Rovik Rovik, Rovik Sechdyna Aura Tursyna Sujono Yuyi Andrika Yuyi Andrika, Yuyi