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Noviyanti, Inna
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Aerospace Engineering Computer Science & IT Health Professions Neuroscience Social Sciences

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Impact of Various Natural Feed Types on Water Quality on Silver Arowana (Osteo-glossum Bicirrhosum) Kusumanti, Ima; Hendriana, Andri; Sholihah, Walidatush; Noviyanti, Inna; Marcelita, Faldiena
Eduvest - Journal of Universal Studies Vol. 3 No. 12 (2023): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v3i12.966

Abstract

The research was conducted to determine the relationship between water quality and body length of arowana fish by measuring several water parameters including temperature, pH, dissolved oxygen and ammonia. In relation to length growth, calculations on SR, SGR are also carried out using ANNOVA. Direct laboratory scale observations were carried out by providing different feeds, including bloodworms, maggot, crickets and live fish with the water source for cultivation activities being well water. The results of observations in the field show that the growth rate of fish in length is influenced by the type of feed given. Giving bloodworms has the most effective value, next to live fish, maggots and crickets. This type of feed also affects the quality of the water used. To maintain success in ornamental fish cultivation, it is recommended to use water efficiently through integrated fish cultivation. Checking the water regularly as well as training of farmers on good management practices and integration is needed to ensure good water quality.
Prediction of Duration of Dry Bamboo Leaf Counting Using Fuzzy Logic Marcelita, Faldiena; Mindara, Gema Parasti; Noviyanti, Inna; Sholihah, Walidatush; Buono, Agus
Eduvest - Journal of Universal Studies Vol. 3 No. 12 (2023): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v3i12.967

Abstract

Dry bamboo leaves are selected as a planting medium for ornamental plants to enhance nutrient content and improve soil drainage. Before being processed into fertilizer, dry bamboo leaves need to be shredded first. The leaf counting process for planting ornamental plants in villages still relies on manual methods such as using knives and scissors, which can be time-consuming and less effective. In response to this issue, a device for shredding dry bamboo leaves has been developed to improve efficiency and facilitate the leaf counting process. The innovation created is a household-scale dry bamboo leaf shredder that is more affordable and easy to mobilize due to its compact dimensions and lighter weight. The device is also easy to operate, as the shredding occurs when it is closed, and the process stops when it is opened, ensuring safe use for various users. The manual control of bamboo leaf weight and counting duration results in inconsistent shredding outcomes. Therefore, development has been carried out on the dry bamboo leaf shredder with artificial intelligence capabilities, specifically using fuzzy logic to automate the counting duration based on the size and weight of the bamboo leaves being inputted.
Co-Authors Agus Buono Hendriana, Andri Ima Kusumanti Marcelita, Faldiena Mindara, Gema Parasti Sholihah, Walidatush