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All Journal Jambi Medical Journal : Jurnal Kedokteran dan Kesehatan Amal Ilmiah: Jurnal Pengabdian Kepada Masyarakat
Mafazy, Muhammad Meftah
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Education Medicine & Pharmacology

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Optimalisasi Pelaporan Keuangan Sesuai SAK EMKM Bagi Pelaku Usaha Mikro Marliadi, Reny; Jamaludin, Wahyudin Bin; Nirwana, Ros; Jakiroh, Jakiroh; Hilmi, Rahmat; Mafazy, Muhammad Meftah
Amal Ilmiah: Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 1 (2026): Edisi Maret 2026
Publisher : FKIP Universitas Halu Oleo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36709/amalilmiah.v7i1.765

Abstract

Usaha Mikro, Kecil, dan Menengah (UMKM) berperan strategis dalam perekonomian Indonesia, namun masih menghadapi kendala dalam pengelolaan dan pelaporan keuangan yang berdampak pada keterbatasan akses pembiayaan. Tujuan kegiatan pengabdian kepada masyarakat ini ialah meningkatkan kemampuan pelaku usaha mikro dalam menyusun laporan keuangan yang akuntabel sesuai Standar Akuntansi Keuangan Entitas Mikro, Kecil, dan Menengah (SAK EMKM). Metode kegiatan dilaksanakan pada tujuh pelaku usaha mikro sektor kuliner di Kota Banjarbaru melalui tahapan sosialisasi SAK EMKM, pelatihan pencatatan keuangan menggunakan Microsoft Excel/Google Spreadsheet, serta pendampingan intensif selama tiga bulan disertai evaluasi berkala. Hasil kegiatan menunjukkan adanya peningkatan signifikan pada kualitas pencatatan dan pelaporan keuangan mitra. Seluruh mitra mampu menyusun laporan posisi keuangan dan laporan laba rugi sesuai SAK EMKM, meskipun penyusunan jurnal penutup dan Catatan atas Laporan Keuangan (CALK) belum sepenuhnya optimal. Dari kegiatan ini disimpulkan bahwa pendampingan berbasis teknologi sederhana efektif meningkatkan literasi dan keterampilan pelaporan keuangan pelaku usaha mikro serta berpotensi mendukung akses pembiayaan dan keberlanjutan usaha.
The Effect of CLAHE Enhancement for Breast Cancer RSNA Detection Putra, Gregorius Guntur Sunardi; Mafazy, Muhammad Meftah
Jambi Medical Journal : Jurnal Kedokteran dan Kesehatan Vol. 14 No. 1 (2026): JAMBI MEDICAL JOURNAL: Jurnal Kedokteran dan Kesehatan
Publisher : FAKULTAS KEDOKTERAN DAN ILMU KESEHATAN UNIVERSITAS JAMBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jmj.v14i1.52596

Abstract

Background: In recent years, image detection has gained substantial importance within the medical field, particularly in diagnosing and interpreting diseases such as breast cancer. Breast cancer stands as a formidable threat, constituting approximately 30% of newly diagnosed cancer cases in the United States and contributing to 12.5% of all new cancer cases. Early detection is crucial for preventing the progression of this severe ailment. Method: This research endeavours to leverage deep learning methodologies to ascertain the presence or absence of breast cancer in patients, utilizing the mammograph breast cancer RSNA dataset. The Contrast Limited Adaptive Histogram Equalization (CLAHE) technique enhances the dataset's images for more precise results. The focus of this study is specifically on the biopsy status related to breast cancer. The deep learning algorithms implemented encompass ResNet50, VGG16, and EfficientNetB0. Notably, the dataset is confined to biopsy status, streamlining the investigation to this critical aspect. Result: The experimental results reveal that the ResNet50 model achieved the highest accuracy at 61%, coupled with an F1-Score of 0.47%. These findings underscore the potential of deep learning techniques, particularly ResNet50, in aiding the early detection of breast cancer. Conclusion: Incorporating image enhancement techniques like CLAHE adds an extra layer of refinement to the dataset, contributing to the overall accuracy and reliability of the diagnostic process. As medical image analysis continues to evolve, such studies pave the way for advancements in early disease detection and intervention strategies.
Co-Authors Hilmi, Rahmat Jakiroh Jamaludin, Wahyudin Bin Nirwana, Ros Putra, Gregorius Guntur Sunardi Reny Marliadi