Susalam, Malikil Kudus
Universitas Negeri Padang

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Characterization of Lactic Acid Bacteria from Budu Fish as Probiotic Candidates from Padang Pariaman Regency Prima, Heppy Setya; Kudus Susalam, Malikil Alam; Maulana, Fajri Fajri; fajri, fadhli fadhli
JURNAL ILMIAH PETERNAKAN TERPADU Vol. 13 No. 2 (2025)
Publisher : DEPARTMENT OF ANIMAL HUSBANDRY, FACULTY OF AGRICULTURE, UNIVERSITY OF LAMPUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jipt.v13i2.p479-499

Abstract

West Sumatra is an area that has a large number of fermented food products, one of which is fermented fish called Budu. The purpose of this study was to isolate and identify Lactid Acid Bacteria isolates from Budu fish from Padang Pariaman Regency and evaluate their probiotic potential. The research method is as follows: isolation of Lactid Acid Bacteria from Budu fish, followed by assessment of resistance tests to gastric pH and bile salts and antimicrobial activity. Then, 16S rRNA was used to assess the species of lactic acid bacteria isolates. Of the 10 samples, one sample of Isolate MKS4, with potential antimicrobial activity was reported. The results showed that the morphological and biochemical characteristics of Lactid Acid Bacteria include Gram-positive bacteria, bacilli and catalase negative included in the homofermentative bacteria group. The greatest antimicrobial activity was shown by Escherichia coli MKS4 0157:H7 (14.79 mm), S. aureus ATCC 25923 (14.89 mm) and enteritidis ATCC 13076 (16.64 mm). The results of molecular identification using 16S rRNA showed that the isolated lactic acid bacteria had similarities with the Lactobacillus strain parabucneri strain HBUAS56106, namely antimicrobial potential against pathogenic bacteria. Lactobacillus. parabucneri strain HBUAS56106 can be used as an antidiarrheal agent and the best antimicrobial compound is classified as a probiotic bacteria
RANCANG BANGUN SISTEM KUALITAS TELUR AYAM RAS BERBASIS INTERNET OF THINGS UNTUK TRANSFORMASI DIGITAL PETERNAKAN Putri, Sylvia Delfi Mardiana; Yulkifli, Yulkifli; Sari, Mona Berlian; Susalam, Malikil Kudus
BIOCHEPHY: Journal of Science Education Vol. 5 No. 2 (2025)
Publisher : MO.RI Publishing

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Abstract

Kualitas telur ayam ras merupakan faktor penting yang menentukan nilai jual dan daya saing produk peternakan. Namun, metode pengujian yang umum digunakan masih bersifat manual dan destruktif, sehingga kurang efisien untuk skala besar. Penelitian ini bertujuan merancang sistem pendeteksi kualitas telur berbasis Internet of Things (IoT) dengan sensor non-destruktif yang terintegrasi model machine learning. Sistem prototype dibangun menggunakan sensor berat, cahaya, dan warna yang dikendalikan oleh mikrokontroler ESP32, dengan hasil pengukuran ditampilkan melalui LCD dan dikirimkan secara real-time ke platform IoT. Nilai Haugh Unit (HU) digunakan sebagai acuan untuk melatih model klasifikasi, di mana algoritma K-Nearest Neighbors (KNN) menunjukkan performa terbaik. Hasil penelitian memperlihatkan sistem mampu mencapai akurasi 89% dalam prediksi HU, sehingga berpotensi digunakan sebagai solusi non-destruktif dalam klasifikasi mutu telur pada skala industri peternakan.