Indonesia has high biodiversity of algae that are under-utilised due to limitations in the processing techniques. Here, we observed the effect of two different extraction methods (cold maceration and ultrasonic-assisted extraction (UAE)) on multiple variables of Indonesian brown algae ethanol extracts (Sargassum polycystum, Sargassum cristaefolium, Sargassum aquifolium and Turbinaria ornata). The variables observed included metabolites screening by untargeted metabolomics liquid chromatography-high-resolution mass spectrometry (LC-HRMS), observation of total phenolic content (TPC), total flavonoid content (TFC), anti-oxidant and B16-F10 melanoma cells cytotoxicity. UAE extracts had higher extraction yield and TPC, but no TFC difference was observed. UAE extract had more lipophilic compounds, such as fatty acids (Palmitic acid, Oleamide, Palmitoleic acid, Eicosapentaenoic acid, α-Linolenic acid, Arachidonic acid), lipid-derived mediators (11,12-Epoxyeicosatrienoic acid ((±)11(12)-EET)), steroid derivatives (Ergosterol peroxide), lipophilic metabolite (Fucoxanthin), and lipid-soluble vitamins (all-trans-retinol). Principle component analysis (PCA) revealed that TPC, not TFC, in the UAE extracts was correlated with the anti-oxidant activities and cytotoxicity of the extracts towards B16-F10 melanoma cells. This means other non-flavonoid phenolic and lipophilic compounds may have contributed to its bioactivity. These results suggest that out of the two methods investigated, UAE could be a chosen method to extract natural anti-melanogenic agents from brown algae.

The frequent use of chemical fertilizers in agricultural practices has developed into a serious environmental concern which urgently needs a solution to restrain their use in agricultural systems. Hence, there is an urgent need to investigate potential organic fertilizers from various natural resources to decrease the use of chemical fertilizers. Seaweed is among the natural resources with potential sustainability value. Our previous work has shown the effectiveness of seaweed fertilizer for increasing plant growth and soil beneficial microbiota. This study aims to evaluate the functional genes present in the soil of rice plants treated with seaweed fertilization. It involves amendments with reduced concentrations of chemical fertilizer in three groups: CF (only chemical fertilizer), CFSF1 (50% dose of CF + seaweed fertilizer 1 ton/ha), and CFSF2 (50% dose of CF + seaweed fertilizer 2 ton/ha). The rice plants supplemented with CFSF1 and CFSF2 were taller and faster to mature compared to CF. In addition, the primary macronutrients nitrogen (N), phosphorus (P), and potassium (K) were also significantly higher in soil supplemented with SF. Our findings showed increased ammonia-oxidizing archaea Crenarchaeota abundance in increasing SF treatments. The PICRUSt analyses indicated enriched functional genes and proteins in relation to amino acid, nucleotide, protein, and carbohydrate metabolism based on the KEGG, BioCyc, and PFAM databases. The current outcomes enhanced our understanding regarding the importance of microbial community for soil quality. Furthermore, seaweed supplementation has shown improvement in soil fertility, which significantly increases rice plant growth and productivity.

COVID-19 patients with comorbid DM face more severe outcomes, indicating that hyperglycemic conditions exacerbate SARS-CoV-2 infection. Negative side effects from existing hyperglycemia treatments have urged the need for safer compounds. Therefore, sourcing potential compounds from marine resources becomes a new potential approach. Algal lipids are known to possess beneficial activities for human health. However, due to limitations in analyzing large amounts of potential anti-hyperglycemic and anti-COVID-19-related marine metabolites, there is an increasing need for new approaches to reduce risks and costs. Therefore, the main aim of this study was to identify potential compounds in macroalgae Sargassum cristaefolium, Tricleocarpa cylindrica, and Ulva lactuca lipophilic extracts for treating DM and COVID-19 by an integrated approach utilizing in vitro anti-oxidant, in vivo anti-hyperglycemic, and metabolomic-integrated in silico approaches. Among them, S. cristaefolium and T. cylindrica showed potential anti-hyperglycemic activity, with S. cristaefolium showing the highest anti-oxidant activity. A GC-MS-based untargeted metabolomic analysis was used to profile the lipophilic compounds in the extracts followed by an in silico molecular docking analysis to examine the binding affinity of the compounds to anti-DM and anti-COVID-19 targets, e.g., α-amylase, α-glucosidase, ACE2, and TMPRSS2. Notably, this study reveals for the first time that steroid-derived compounds in the macroalgae T. cylindrica had higher binding activity than known ligands for all the targets mentioned. Studies on drug likeliness indicate that these compounds possess favorable drug properties. These findings suggest the potential for these compounds to be further developed to treat COVID-19 patients with comorbid DM. The information in this study would be a basis for further in vitro and in vivo analysis. It would also be useful for the development of these candidate compounds into drug formulations.

Malnutrition and stunting are serious issues in Indonesia, particularly in Sekotong Subdistrict, West Lombok Regency, West Nusa Tenggara. The prevalence of stunting in this subdistrict reached 94 cases in 2020. This research aims to develop an Android application called Yess Nutrition as a medium for educating pregnant women about nutrition and stunting prevention in Sekotong Subdistrict. The Design Thinking and Personal Extreme Programming methods are employed in the development of this application. The test results show that the application received a mean opinion score of 4.173, indicating good quality and user interface. It is expected that the Yess Nutrition app will enhance the knowledge of pregnant women regarding nutrition and stunting prevention. By leveraging the vast potential of the Android platform, this application has the potential to become an effective educational tool for raising awareness about nutrition and preventing stunting.

Banyak permasalahan dijumpai dalam hal pengajuan Praktek Kerja Lapangan (PKL) di Program Studi Teknik Informatika (PSTI) Fakultas Teknik Universitas Mataram, seperti proses pengajuan dokumen persyaratan PKL masih dilakukan secara manual yaitu menggunakan blanko yang harus dicetak sehingga rentan akan kerusakan dan kehilangan. Pencatatan data mahasiswa yang mengajukan masih dilakukan secara manual. Dari sisi pengelola prodi, teknik manual masih merepotkan karena semua berkas-berkas masih disimpan dalam map dan belum terdapat penyimpanan khusus, sehingga rawan hilang dan tercampur dengan berkas lainnya. Disamping itu, ketika mencari suatu berkas tertentu, harus mencari satu persatu di dalam tumpukan berkas lainnya. Mahasiswa juga harus antri di loket prodi ketika terdapat banyak mahasiswa yang melakukan pengajuan PKL di waktu yang sama sehingga dari sisi staf prodi dan mahasiswa akan membutuhkan waktu yang lama. Pihak program studi juga masih kesulitan dalam hal pelaporan statistik beban bimbingan dosen dari mahasiswa PKL sehingga terkadang terdapat dosen yang beban bimbingan sangat banyak dan ada juga yang beban bimbingannya sedikit, membuat distribusi beban dosen tidak merata. Tujuan dari pengabdian kepada masyarakat ini adalah untuk membantu memberikan solusi terhadap permasalahan program studi dalam hal manajemen administratif pengurusan PKL yaitu dengan membuat sebuah sistem informasi berbasis web yang terdapat fitur-fitur sesuai Standar Operasional Prosedur (SOP) PKL. Mahasiswa dapat melakukan pengajuan PKL secara online seperti meminta persetujuan dosen PA, mencetak surat pengantar secara mandiri, hingga seminar PKL. Pihak Prodi juga dapat terbantu karena semua berkas tersimpan di dalam basis data sistem dan mempermudah dalam hal pembuatan laporan statistik PKL. Keywords: sistem informasi, website, praktek kerja lapangan, teknologi, pendidikan.

West Nusa Tenggara (NTB) is one of the regions in Indonesia with significant potential in the field of livestock farming. In the context of the agricultural industry, livestock is considered a valuable asset, and monitoring their health is crucial for improving livestock productivity. This research aims to determine the relationship between the body temperature of cattle (Y) and environmental factors, namely air humidity (), environmental temperature (), and barometric pressure (), using smart livestock data provided by PT Telkom. The study was conducted in Pengengat Village, NTB, involving correlation and regression analysis. The analysis results indicate a significant positive correlation between the body temperature of cattle and environmental temperature () and a negative correlation with humidity (). Additionally, there is a strong positive correlation between the body temperature of cattle and barometric pressure (). The multiple linear regression equation obtained is as follows: = –26.816842418191094 + -0,0014707 + 0.39772325 + 0.04927779. Model testing shows excellent prediction quality with low Mean Squared Error (MSE) values (0.3849 for training and 0.4623 for testing). Furthermore, the high R-squared (R^2) values (0.7283 for training and 0.7110 for testing) indicate that the linear regression model can predict the body temperature of cattle based on the analyzed environmental factors. Keywords: Cattle Body Temperature, Smart Livestock Data, Prediction, Machine Learning, Linear Regression