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Ainiyah, Lailatul
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Penyuluhan Pemberian Puding Daun Kelur terhadap Balita Stunting Usia 2 tahun di Desa Nyalabu Daya Kabupaten Pamekasan Ainiyah, Lailatul; Rusady, Yulia Paramita
Jurnal Pengabdian Masyarakat Bangsa Vol. 3 No. 1 (2025): Maret
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v3i1.2187

Abstract

Stunting disebabkan oleh kekurangan gizi kronis sejak dalam kandungan hingga usia dua tahun. Daun kelor mengandung berbagai mikronutrien penting seperti vitamin A, C, dan zat besi yang berperan dalam pertumbuhan dan perkembangan anak. Penyuluhan ini bertujuan untuk mengevaluasi efektivitas puding daun kelor dalam meningkatkan status gizi balita. Metode yang digunakan adalah demonstrasi pembuatan pudding daun kelor. Hasil peyuluhan menunjukkan pemberian daun kelorsecara teratur dapat membantu mencegah terjadinya stunting pada anak balita Potensi daun kelorsebagai sumber nutrisi sangat besar. Selain untuk mencegah stunting, daun kelor juga dapat bermanfaat untuk meningkatkan daya tahan tubuh kandungan antioksidan yang tinggi dapat melindungi tubuh dari kerusakan sel dan memperkuat sistem kekebalan tubuh. Menjaga kesehatan pencernaan yaitu serat dalam daun kelor membantu menjaga kesehatan pencernaan. Hal ini menunjukkan bahwa konsumsi daun kelor dapat membantu menurunkan risiko penyakit kronis seperti diabetes dan penyakit jantung. Disimpulkan bahwa puding daun kelor dapat menjadi salah satu alternatif untuk mengatasi anemia dan kekurangan vitamin A pada balita, sehingga berkontribusi padapencegahan stunting
Implementing lee's model to apply fuzzy time series in forecasting bitcoin price Farida, Yuniar; Ainiyah, Lailatul
Computer Science and Information Technologies Vol 5, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v5i1.p72-83

Abstract

Over time, cryptocurrencies like Bitcoin have attracted investor's and speculators' interest. Bitcoin's dramatic rise in value in recent years has caught the attention of many who see it as a promising investment asset. After all, Bitcoin investment is inseparable from Bitcoin price volatility that investors must mitigate. This research aims to use Lee's Fuzzy Time Series approach to forecast the price of Bitcoin. A time series analysis method called Lee's Fuzzy Time Series to get around ambiguity and uncertainty in time series data. Ching-Cheng Lee first introduced this approach in his research on time series prediction. This method is a development of several previous fuzzy time series (FTS) models, namely Song and Chissom and Cheng and Chen. According to most previous studies, Lee's model was stated to be able to convey more precise forecasting results than the classic model from the FTS. This study used first and second orders, where researchers obtained error values from the first order of 5.419% and the second order of 4.042%, which means that the forecasting results are excellent. But of both orders, only the first order can be used to predict the next period's Bitcoin price. In the second order, the resulting relations in the next period do not have groups in their fuzzy logical relationship group (FLRG), so they can not predict the price in the next period. This study contributes to considering investors and the general public as a factor in keeping, selling, or purchasing cryptocurrencies.
Co-Authors Rusady, Yulia Paramita Yuniar Farida, Yuniar