Abstract. Expert system is dealt with system that used computer-based human intelligence to overcome particular problem which is commonly conducted by an expert. Frequent problem faced by the farmers of oil palm is the difficulty in defining the type of plant disease. As a result, the delay treatment of plant disease brings out the declining of farm products. An application system is needed to deal with the obstacles and diagnosing the type of oil palm plant disease. The researcher designed an intelligence-based application with input-output plan which is able to diagnose the type of oil palm plant disease by applying naive bayes method. Based on the research result by conducting bayes method with recognized symptom, diagnose of oil palm plant disease could be accomplished. The data of symptoms found are leaves turned yellow 0.4, dead leaves 0.4, black and brown color among the veins of leaves 0.5, young and old fruit with whole space 0.4, and decay of bunches is 0.3. The roots are tender in the amount of 0.5, and damage on sheath is 0.3. Through the chosen symptoms as mentioned above, the value of bayes is 80% with the type of disease is rotten bunch.

The use of technology is very important nowadays. Most of everyday activities are documented and stored in digital form. One of those activity is recording. Activity of an organization is very important, therefore recording of meeting material is one of those important activities. Usually the meeting material is documented by writing them into papers or typing them and stored them into computer. Sometimes, the meeting information is written or typed incorrectly so a speech-to-text application is required to solve this problem. In this study, the solution offered is to implement a web-based automation speed-to-text application which can record the voice of meeting participants then converted them into text automatically, so the results of the recording process of meeting materials are more effective and efficient By using voice recognition feature its called web kit Speech Recognition, this system can be implemented. After successfully implementing this application which is so called Speech Meeting Web kit system, the average value for duration system for Indonesia and English language is 96,63 % and 82,78 %.

Melihat perkembangan twitter tersebut maka twitter menjadi salah satu media yang dapat digunakan untuk melakukan analisis sentimen terhadap bebagai topik. Penelitian ini  melakukan suatu analisis sentimen terhadap bahasan yang saat ini sering menjadi trending topic di twitter yaitu “CoronaVirus Disease-2019 (covid19)”. Penyebaran virus ini juga langsung dibicarakan oleh banyak kalangan masyarakat twitter, saat ini virus corona tengah menjadi perhatian dunia internasional. Banyaknya jumlah angka korban dan cepatnya penularan virus membuat masyarakat khawatir dan muncul berbagai opini tentang virus corona, Opini inilah yang kemudian di analisa untuk diketahui polaritasnya dengan analisis sentimen. Metode yang digunakan adalah Logistic Regression dan Support Vector Machine (SVM) dimana SVM memiliki nilai akurasi 91,15% dalam data test sedangkan metode Logistic Regression mendapatkan nilai akurasi sebanyak 87,68% dalam data test.

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