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Isolation of Probiotic Lactic Acid Bacteria (LAB) From Commercialized Yogurt Based on 16s rRNA Gene Apriansyah Wibowo; Kaisar Akhmad Khan; Dewi Mustikaningtyas; Rizky Ajie Aprilianto
Sainteknol : Jurnal Sains dan Teknologi Vol. 23 No. 1 (2025): June 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sainteknol.v23i1.19825

Abstract

Yogurt, a globally cherished dairy product, is celebrated not only for its creamy texture and tangy flavour but also for its numerous health benefits, primarily attributed to lactic acid bacteria (LAB). Key LAB species such as Lactobacillus bulgaricus and Streptococcus thermophilus drive the fermentation process, transforming milk into yogurt through lactic acid production. This study aims to isolate and identify LAB species from various yogurt brands using the 16S rRNA gene, employing advanced microbial analysis techniques such as PCR. Yogurt samples from five different brands were collected from a local convenience store in Gunungpati, Central Java, Indonesia. The bacterial inoculation was carried out using MRS agar, and isolated colonies were subjected to direct colony PCR with primers 27f and 1492r. The PCR products were analyzed using agarose gel electrophoresis. The results demonstrated that direct colony PCR is an effective technique for rapidly and accurately detecting bacterial species without the need for DNA extraction. All five yogurt samples contained Lactobacillus sp., as evidenced by the amplification of DNA fragments approximately 1500 base pairs in size. This study confirms the specificity and effectiveness of the 27f/1492r primers in identifying Lactobacillus sp., providing more information for further research on the probiotic roles of LAB in yogurt quality and health impacts.
IMPLEMENTASI DRIP IRRIGATION BERBASIS IOT DAN ENERGI SURYA PADA KELOMPOK TANI KUBIS Rizky Ajie Aprilianto; Subiyanto Subiyanto; Nur Anita; Fauzul Adzim; Faiq Mananul Faqih; Aisya Fathimah; Wildatul Afiah; Apriansyah Wibowo; I Gede Bagus Jayendra; Listiana Sukaesi; Bayu Adi Pambudi; Yohanes Lenaldo Sinaga; Febrian Adi; Muhammad Hilmi Farras
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 7 No. 2 (2026): Inpress Vol. 7 No. 2 (2026)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v7i2.56109

Abstract

Irigasi yang efektif sangat penting untuk memenuhi kebutuhan air tanaman sekaligus mencegah penguapan berlebih dan kekurangan air. Praktik konvensional seringkali menyebabkan pemborosan air dan pupuk sehingga menurunkan efisiensi produksi pertanian, Kegiatan ini bertujuan untuk menerapkan sistem drip irrigation berbasis Internet of Things (IoT) dan energi terbarukan meningkatkan efisiensi penggunaan air dan nutrisi pada budidaya kubis di Kelompok Tani Bangkit Merbabu. Sistem ini mengintegrasikan sensor kelembapan tanah, suhu, dan kelembapan udara yang terhubung ke mikrokontroler untuk melakukan monitoring dan kontrol otomatis. Irigasi dan fertigasi dijadwalkan sesuai kebutuhan tanaman dengan mode otomatis. Hasil penerapan menunjukkan bahwa sistem fertigasi tetes berbasis IoT mampu meningkatkan efisiensi waktu kerja sebesar 80%, dibandingkan metode konvensional, dengan penghematan air mencapai 40%. Penerapan sistem ini menunjukkan potensi signifikan dalam mengoptimalkan sumber daya pertanian, meningkatkan produktivitas, serta mendukung penerapan pertanian presisi dan berkelanjutan berbasis energi terbarukan.
Ray Tracing-Based Modeling of Bifacial Photovoltaic Systems in Greenhouse Agrivoltaics Endang Widiyawati; Subiyanto Subiyanto; Siti Ridloah; Budi Sunarko; Bagaskoro Saputro; Rizky Ajie Aprilianto; Mario Norman Syah; Abdurrakhaman Hamid Al-Azhari; Deyndrawan Sutrisno; Aisya Fathimah; Apriansyah Wibowo; I Gede Bagus Jayendra
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 15 No. 2 (2026): April 2026
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtepl.v15i2.510-524

Abstract

This work presents an enhanced ray tracing-based modeling framework to optimize bifacial photovoltaic energy generation and crop productivity within greenhouse environments. The proposed framework integrates a ray tracing-based optical and electrical model to simulate light dynamics and energy generation within greenhouse structures. The optical model incorporates Uniform Distribution of rear-irradiance (UF) and Non-Uniform Distribution of rear-irradiance (NUF) principles to simulate irradiance distribution, shading, and reflection, using Light Saturation Point (LSP) and Photosynthetically Active Radiation (PAR) measurements. The electrical model estimates energy yield using the LambertW function based on incident and transmitted light through photovoltaic arrays. Five types of greenhouse structures using plastic and SG80 materials are analyzed to assess their impact on system performance under various conditions. The evaluation showed that integrating bPV increased rear-side energy captured by 25-30%. The optimal configuration was achieved by combining a plastic cover with a checkerboard pattern, resulting in up to 5% higher performance than the 35° tilt setup and offering enhanced light distribution uniformity. Although the average soil irradiance of 170.801 W/m² slightly exceeded the light saturation threshold of 164.7 W/m², it remained within a safe range that supports efficient photosynthesis without causing photoinhibition.