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All Journal JOIV : International Journal on Informatics Visualization Indonesian Journal of Life Sciences
Angelyna, Angelyna
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Medicine & Pharmacology

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Analyzing the Effects of Kefir on the Gut Microbiota Strains in Alzheimer’s Patients Ellivia, Vanessa; Hariyanto, Belinda; Kwan, Erika Marceline; Angelyna, Angelyna; Tjahjadi, Celestine Jovanka; Wiguna, Andrea Benita; Wen, Chelsy Angelline; Astina, Junaida
Indonesian Journal of Life Sciences 2024: IJLS Vol 06 No.02
Publisher : Indonesia International Institute for Life Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54250/ijls.v6i2.182

Abstract

Alzheimer's disease (AD) is a neurodegenerative disorder that progresses over time and slowly deprives patients of their memory, cognitive abilities, and eventually, capability to carry out even the simplest activities, and even affects the gut microbiota. Studies suggest changes in gut microbial diversity and abnormalities in the gut-brain axis are associated with AD. Probiotics, known for their numerous health benefits, are well recognized as one of the most effective prophylactic strategies against cognitive deterioration in AD. In order to grow, the gut microbiota needs nutrients including Lactobacilli and Bifidobacteria which are frequently linked to the therapeutic potential of kefir. It is proven to modulate the immune system and maintain gut health by modifying the gut microbiota, lowering the prevalence of inflammation as well as oxidative stress, which slows down the progression of AD. Thus, this review summarizes the possible benefits of probiotics, specifically, kefir, on the gut microbiota strains in Alzheimer’s patients. A literature search was conducted on scientific platforms using Google Scholar and PubMed. Given the inclusion criteria and the limitation on the publication year, 53 scientific articles were selected for further analysis. Keyword searches were limited to the following. (1) Alzheimer’s disease and/or (2) gut microbiota and/or (3) probiotics and/or (4) kefir. The findings of this study clarify the association between probiotics and AD in altering the gut microbiota by improving the proliferation of Lactobacillus and Bifidobacterium and subsequently slowing the progression of AD. Keywords: Alzheimer’s disease (AD); gut microbiota; probiotics; nutrients; bioactive compounds; kefir
A Deep Learning Approach Using VGG16 to Classify Beef and Pork Images Zulfikar, Wildan Budiawan; Angelyna, Angelyna; Irfan, Mohamad; Atmadja, Aldy Rialdy; Jumadi, Jumadi
JOIV : International Journal on Informatics Visualization Vol 9, No 2 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.2.2848

Abstract

There are 87.2% of the Muslim population in Indonesia, which makes Indonesia one of the countries with the largest Muslim population in the world. As a Muslim, it is supposed to carry out and stay away from the commands that Allah SWT commands, one of which is in QS. Al-maidah:3, one of the commands in the verse is not to consume haram food such as pork. Even so, it turns out that many traders in Indonesia still cheat to get more significant profits, namely by counterfeiting beef and pork. The lack of public knowledge supports this situation to differentiate between the two types of meat. Therefore, the classification process is used to distinguish the two kinds of meat using the convolutional neural network approach with VGG16 with several preprocessing stages. Two primary stages are used during the preprocessing stage: scaling and contrast enhancement. The VGG16 algorithm gets very good results by getting an accuracy value of 99.6% of the test results using 4,500 images for training data and 500 images for testing data. To compare the effectiveness of these techniques, it is recommended to use alternative CNN architectures, such as mobilNet, ResNet, and GoogleNet. More investigation is also required to gather more varied datasets, enabling the ultimate goal to achieve the best possible categorization, even when using cell phone cameras or with dim or fuzzy photos.
Co-Authors Aldy Rialdy Atmadja Ellivia, Vanessa Hariyanto, Belinda Jumadi Jumadi Junaida Astina Kwan, Erika Marceline Mohamad Irfan, Mohamad Tjahjadi, Celestine Jovanka Wen, Chelsy Angelline Wiguna, Andrea Benita Wildan Budiawan Zulfikar