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All Journal MEDISAINS Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi
Setiawan , Eko
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Medicine & Pharmacology Nursing Public Health

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Sistem Deteksi Durasi Waktu Penyimpanan Susu Sapi Segar Berdasarkan Tingkat Keasaman dan Perubahan Warna dengan Menggunakan Metode K-Nearest Neighbors (K-NN) Berbasis Arduino BHRAMANTYA , RIZKY; Syauqy , Dahnial; Setiawan , Eko
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 8 No 10 (2024): Oktober 2024
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Susu merupakan sumber pangan hewani yang penting, mengandung nutrisi seperti air, lemak, laktosa, protein, dan mineral. Susu sapi segar berasal dari kelenjar susu sapi perah Friesian Holstein (FH) betina dan biasanya mengalami proses pengolahan, termasuk pasteurisasi atau UHT, untuk menghilangkan bakteri patogen sambil mempertahankan kualitas nutrisinya. Kualitas susu sapi dapat dinilai berdasarkan pH, warna, dan rasa, dengan kisaran pH optimal antara 6,5 dan 6,7. Warna putih susu disebabkan oleh kasein, sedangkan warna kekuningan berasal dari karoten. Penentuan kualitas susu segar seringkali sulit dilakukan saat pembelian karena ketidakpastian lama penyimpanan. Beberapa penelitian telah mengeksplorasi metode untuk menilai kelayakan susu berdasarkan parameter seperti pH, warna, dan gas amonia. Penelitian ini bertujuan untuk mendeteksi durasi penyimpanan susu sapi segar menggunakan metode K-Nearest Neighbors (K-NN) dengan parameter tingkat keasaman dan perubahan warna. Sistem berbasis Arduino UNO akan menggunakan sensor pH (PH-4502C) dan sensor warna (TCS-3200) untuk menganalisis sampel susu sapi. Algoritma K-NN yang menggunakan supervised learning, akan mengklasifikasikan data susu berdasarkan data latih (training data) yang telah ada, dengan hasil ditampilkan pada layar LCD I2C Display. Metode ini dipilih karena efisiensi komputasinya pada jumlah data sedikit, dengan tingkat keakurasiannya bergantung pada pemilihan nilai K yang optimal.
Semi-Adaptive Control Systems on Self-Balancing Robot using Artificial Neural Networks Setiawan, Eko; Setiawan , Eko; Syauqy, Dahnial
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 5 No 2 (2021): August 2021
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (716.62 KB) | DOI: 10.29407/intensif.v5i2.15296

Abstract

A self-balancing type of robot works on the principle of maintaining the balance of the load's position to remains in the center. As a consequence of this principle, the driver can go forward reverse the vehicle by leaning in a particular direction. One of the factors affecting the control model is the weight of the driver. A control system that has been designed will not be able to balance the system if the driver using the vehicle exceeds or less than the predetermined weight value. The main objective of the study is to develop a semi-adaptive control system by implementing an Artificial Neural Network (ANN) algorithm that can estimate the driver's weight and use this information to reset the gain used in the control system. The experimental results show that the Artificial Neural Network can be used to estimate the weight of the driver's body by using 50-ms-duration of tilt sensor data to categorize into three defined classes that have been set. The ANN algorithm provides a high accuracy given by the results of the confusion matrix and the precision calculations, which show 99%.
In vivo study on the effect of noni leaf extract cream (Morinda Citrifolia L) on PDGF and TNF-α levels in cut wounds Sari, Shintia Devi Arum; Mulyani, Sri Priyantini; Putra, Agung; Setiawan , Eko
MEDISAINS: Jurnal Ilmiah Ilmu-Ilmu Kesehatan Vol. 23 No. 3 (2025)
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/medisains.v23i3.25252

Abstract

ABSTRACT Background: Skin wounds damage the structure and epithelial tissue, resulting in scar tissue formation. Prolonged wound healing or excessive body response will inhibit the normal process and produce unaesthetic scar tissue. Many plant extracts and their active components can accelerate the wound healing process, Noni leaf extract has antioxidant activity and accelerates wound healing. Objective: This study aims to determine the effect of noni leaf extract cream (Morinda Citrifolia L) on TNF-α and PDGF levels in Wistar rats with incised wounds. Method: A laboratory experimental study with a post-test only control group design. Consisting of five treatment groups, namely the healthy rat group (KS), Negative group (KN) rats with incised wounds without treatment, positive group (KP) rats with incised wounds that were smeared with povidone-iodine cream, treatment group 1 (P1) rats that were smeared with 20% noni leaf extract cream, and treatment group 2 (P2) rats that were smeared with 40% noni leaf extract cream, treatment for 3 days then examined the levels of TNF-α and PDGF skin tissue using the ELISA method. Results: The average TNF-α levels showed a significant difference between groups p of 0.000 (p <0.05) with the One way anova test, the highest average in group (KN) 220.68 pg / mL, there was a decrease in all treatment groups with the lowest TNF-α levels in group (KP) 76.59 pg / mL. The average results of TNF-α levels showed a significant difference of p 0.000 (<0.05) with the One-way ANOVA test, the group without intervention (KP) had the lowest PDGF levels while the group (P2) experienced the highest increase in PDGF levels. Conclusion: Administration of noni leaf extract cream with doses of 20% and 40% had an effect on reducing TNF-α levels and increasing PDGF levels in Wistar rats with incised wounds.
Co-Authors Agung Putra BHRAMANTYA , RIZKY Dahnial Syauqy Eko Setiawan Sari, Shintia Devi Arum Sri Priyantini Mulyani Syauqy , Dahnial