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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Chemistry Indonesian Journal of Chemical Research Harmoni Sosial : Jurnal Pengabdian Dan Solidaritas Masyarakat
Amalia, Puspa
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Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Education Engineering Environmental Science Social Sciences Other

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Edukasi Peran Zat Besi pada Pencegahan Anemia di SMP Negeri 06 Ketapang Dwisari, Fath; Dermawan, Abdurraafi' Maududi; Amalia, Puspa; Azmi, Khulul; Ramadhani, Natasya Intan; Purwanti, Desi Asih
Harmoni Sosial : Jurnal Pengabdian dan Solidaritas Masyarakat Vol. 2 No. 3 (2025): Juli : Harmoni Sosial : Jurnal Pengabdian dan Solidaritas Masyarakat
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/harmoni.v2i3.1809

Abstract

Anemia is a common health problem among adolescents, often caused by iron deficiency. This educational activity aimed to improve students' knowledge about the role of iron in preventing anemia. The program was conducted at SMP Negeri 06 Ketapang and involved 35 students as respondents. The results showed that after the educational session, the majority of students were in the moderate knowledge category (19 students or 54.3%), followed by the high category (7 students or 20%) and the low category (9 students or 25.7%). It can be concluded that this educational activity was quite beneficial in increasing students’ knowledge about the importance of iron in anemia prevention.
Evaluation of the Antimicrobial Efficacy of Hibiscus sabdariffa L. Antiperspirant Preparations Against Staphylococcus epidermidis Dwisari, Fath; Dermawan, Abdurraafi Maududi; Amalia, Puspa; Tjoadri, Tessa Nathalia; Rahma, Nur Atika
Indonesian Journal of Chemical Research Vol 13 No 2 (2025): Edition for September 2025
Publisher : Jurusan Kimia, Fakultas Sains dan Teknologi, Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/ijcr.2025.13-fat

Abstract

Commercial antiperspirant products commonly incorporate synthetic compounds, several of which have raised concerns due to their potential carcinogenicity. Moreover, the inclusion of natural antibacterial agents in these formulations remains limited. Hibiscus sabdariffa L. (Rosella), a plant rich in bioactive secondary metabolites, offers a promising natural alternative. This study aimed to evaluate the antibacterial efficacy of rosella-based antiperspirant formulations, particularly against Staphylococcus epidermidis, a key contributor to body odor. Three formulations (F1, F2, and F3) were developed and assessed based on several parameters: pH, organoleptic properties, homogeneity, spreadability, adhesiveness, and antibacterial activity against Staphylococcus epidermidis. The results demonstrated that the antiperspirant preparations complied with standard evaluation criteria. Furthermore, the antibacterial assay outcomes yielded statistically significant differences (p < 0.05) in the mean diameter of the inhibition zones, indicating that H. sabdariffa L. exhibited measurable antibacterial activity against S. epidermidis. These findings support the potential application of Rosella extract in developing natural and efficacious anti-perspirant products.
Pengembangan Automated Image Analysis untuk Menentukan Jumlah Bakteri Tahan Asam (BTA) pada Kasus Tubercolosis Adam, Safri; Astuti, Puji; Amalia, Puspa; Sukandiarsyah, Fadli
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 4: Agustus 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2022945805

Abstract

Diagnosis TB (tuberculosis) oleh tenaga kesehatan menjadi kunci penting dalam menemukan pasien baru TB. Diagnosis umum yang digunakan di Fasilitas Kesehatan (Faskes) TK 1 seperti puskesmas dilakukan dengan cara mewarnai spesimen dahak penderita dengan metode Ziehl-Neelsen untuk mendeteksi keberadaan Bakteri Tahan Asam seperti Mycobaterium tuberculosis penyebab TB. Namun pada praktiknya, penghitungan manual dengan bidang pandang terbatas pada mikroskop membutuhkan waktu pengerjaan yang cukup panjang. Dimasa pandemi covid19, efisiensi pengerjaan diagnosis harian termasuk pemeriksaan BTA harus ditingkatkan karena keterbatasan tenaga ATLM dilapangan yang turut bekerja menghadapi Covid19. Maka, pada penelitian ini akan dikembangkan sebuah automated image analysis, atau analisis citra secara otomatis yang dapat menghitung jumlah bakteri yang tampak pada mikroskop. Proses pembuatan apusan BTA didapat 3 preparat yang menghasilkan data citra sebanyak total 171 citra. Noise pada citra dapat diatasi menggunakan metode CLAHE untuk memperbaiki kontras. Metode untuk pengolahan citra digital yang digunakan yaitu segmentasi HCA (Hiearcical Cluster Analysis) untuk memisahkah objek BTA dengan latar belakang. Hasil segmentasi dilakukan proses operasi morfologi untuk menghilangkan objek kecil selain objek BTA yang bekerja baik pada citra biner untuk mempermudah perhitungan jumlah bakteri. Metode HCA yang dikombinasikan dengan strategi seleksi objek dapat melakukan segmentasi objek BTA dengan baik. Hasil evaluasi menunjukkan RMSE (Root Mean Square Error) sebesar 2.484  yang didapat pada saat threshold 0.11. AbstractDiagnosis of TB (tuberculosis) by health workers is an important key in finding new TB patients. The general diagnosis used in TK 1 Health Facilities (Faskes) is carried out by revealing a patient's sputum specimen using the Ziehl-Neelsen method to detect the presence of acid-fast bacteria such as Mycobacterium tuberculosis, which causes TB. However, in practice, manual calculations with a limited field of view on a microscope require a fairly long processing time. During the covid19 pandemic, the efficiency of daily diagnostic work including BTA examinations must be increased due to the limited ATLM personnel in the field who are also working to deal with Covid19. So in this research, an automated image analysis application will be proposed that can count the number of bacteria that appear on a microscope. The process of making smears of AFB obtained 3 preparations which produced a total of 171 images of image data. Noise in the image can be overcome using the gaussian blur filter and the CLAHE method to improve contrast. The method for digital image processing is the HCA (Hiearcical Cluster Analysis) segmentation method to separate BTA objects from the background. Pre-processed segmentation results using morphological operations that work well on binary images to simplify the calculation of the number of bacteria. The HCA method combined with the object selection strategy can segment BTA objects well. The evaluation results show an RMSE (Root Mean Squere Error) of 2,484 obtained at the 0.11 . threshold
Co-Authors Azmi, Khulul Dermawan, Abdurraafi Maududi Puji Astuti Purwanti, Desi Asih Rahma, Nur Atika Ramadhani, Natasya Intan Safri Adam Sukandiarsyah, Fadli Tjoadri, Tessa Nathalia