Kunyit putih (Curcuma zedoaria) adalah tanaman herbal yang banyak digunakan sebagai obat herbal di Asia, khasiatnya dipercaya dapat meningkatkan imun tubuh, sebagai anti nyeri dan anti inflamasi. Penggunaan obat herbal secara umum dipercayai oleh masyarakat memiliki efek samping cenderung rendah dibandingkan obat modern, akan tetapi belum ada banyak penelitian mengenai efek samping dari penggunaan kunyit putih. Kebaruan dalam penelitian ini karena meneliti uji akut ekstrak kunyit putih terhadap analisis gambaran histopatologi otot jantung. Penelitian ini bertujuan untuk menguji toksisitas akut dari ekstrak etanol rimpang kunyit putih terhadap gambaran histopatologi otot jantung. Penelitian menggunakan 30 ekor tikus putih (Rattus norvegicus) dengan berat antara 150-200 gr. Sampel dikelompokkan menjadi 2 kelompok kontrol dan 4 kelompok perlakuan. Perlakuan yang dilakukan yaitu pemberian aquades, NaCMC1%, dosis EKP 250 mg/KgBB, EKP 500 mg/KgBB, EKP 750mg/KgBB, dan EKP 2000 mg/KgBB. Parameter yang diamati adalah hiperemi, hemoragi dan degenerasi dari sel otot jantung. Hasil penelitian ini menunjukkan bahwa tidak terdapat tikus yang mati akibat pemberian EKP, akan tetapi terdapat kerusakan ringan pada dosis EKP 250 mg/KgBB, kerusakan sedang pada dosis EKP 500 mg/KgBB, kerusakan sedang-berat pada dosis EKP 750mg/KgBB dan kerusakan berat pada dosis EKP 2000 mg/KgBB. Berdasarkan hasil penelitian ini, maka dapat disimpulkan bahwa kerusakan sel otot jantung meningkat secara signifikan seiring dengan peningkatan dosis ekstrak etanol rimpang kunyit putih dimana kerusakan sel otot jantung terberat pada dosis EKP 2000mg/kgBB.Kata kunci : jantung; kunyit putih; tikus. AbstractWhite turmeric (Curcuma zedoaria) is a herbal plant that is widely used as herbal medicine in Asia because of its properties which are believed to increase the body’s immune system, anti-inflammatory, and an analgesic. The use of herbal medicine is generally believed by the public to have lower side effects than modern medicine, but in reality, there has not been much research on the side effects of white turmeric usage. The novelty in this study was due to the acute study of white turmeric extract on the histopathological analysis of heart muscle. Therefore, this study aims to determine the acute toxicity of white turmeric’s rhizome ethanol extract on histopathological features of the heart muscle. This experiment used 30 male white Wistar rats (Rattus norvegicus) with a weight between 150-200 grams. Rats were divided into 2 control groups and 4 groups of treatment. Treatment given to the rats are aquadest, NaCMC 1% WTE 250mg/KgBW, WTE 500mg/KgBW, WTE 750mg/KgBW, and WTE 2000mg/KgBW . The parameters observed are hyperemia, hemorrhage, and degeneration of heart muscle cells. The result showed in this study were that there were no mice that died due to EKP administration, but there was mild damage at WTE dose of 250 mg/KgBB, moderate damage at WTE dose of 500 mg/KgBB, moderate-severe damage at WTE dose of 750mg/KgBB and severe damage on WTE dose of 2000 mg/KgBW. Based on the results of this research, it can be concluded that there is significant damage found along with an increasing dose of white turmeric extract given, where the damage on heart muscle cells is most severe at WTE dose of 2000 mg/KgBW.

Heart attack disease is a condition where the arteries are blocked due to fatty deposits. This disease causes several symptoms such as shortness of breath, chest pain. In addition, this is also due to impaired blood flow to the heart that is blocked and can destroy the heart muscle. Until now, heart attack disease is still the leading cause of death in Indonesia. The problem faced today is that it is very difficult to predict heart disease and determine whether a person has heart disease. An appropriate method is needed to predict heart disease. The purpose of this study was to calculate the level of accuracy in predicting heart attack using the K-Nearest Neighbor and Logistic Regression methods. Based on the research and data processing that has been applied and the comparison of the K-Nearest Neighbor and Logistic Regression algorithms, the final results are the accuracy of the Logistic Regression Algorithm of 88% and the K-Nearest Neighbor algorithm of 83%. Thus it can be concluded that the Logistic Regression algorithm is the best in predicting heart attack disease than the K-Nearest Neighbor algorithm.

Objective – Cryptocurrency is growing overtime even being adopted as a legal money in a country out there. Besides can be used as a money, cryptocurrency also can be used as a digital goods to be trade and investment assets. To do some investing in cryptocurrency, there’s a need to evaluate the fundamental and sentiment of that cryptocurrency. This study aims to evaluate cryptocurrency based on responses of Twitter user.Methodology – The Algorithms used in this sentiment analysis study are Support Vector Machine and Naïve Bayes because it’s already proven that these 2 algorithm able to give a good accuracy and performance and using CRISP – DM framework for the study flow.Findings – This research predicts the sentiment for Bitcoin, Ethereum, Binance Coin, Dogecoin, and Ripple using the CRISP - DM method and using Support Vector Machine and Naïve Bayes algorithm.Novelty – This study calculate the sentiment on cryptocurrency using Rapidminer tools.Limitations - This study uses Bitcoin, Ethereum, Binance Coin, Dogecoin, and Ripple using tools such as rapidminerKeywords — Cryptocurrency, Naïve Bayes, Sentiment Analysis, Support Vector Machine

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