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Agriculture is an activity of managing biological natural resources with the help of technology, capital, labor and management to produce agricultural commodities which include food crops, horticulture, plantations and or livestock in an agro-ecosystem. Most of the Indonesian people's livelihoods are as farmers, so the agricultural sector is very important to develop in this country. Poktan Beno Raharjo in Glonggong Village, Madiun Regency has a problem, namely the absence of an information system that is useful for managing agricultural production data, managing farmer data, managing village granary data, recording planting of food crops and horticultural crops, managing subsidized fertilizer assistance. The mobile-based Poktan information system was created using the dart programming language with the flutter framework using the waterfall method and testing using the black box testing method.

The government that is running at this time is also not spared from public comments on Twitter, especially regarding the increase in subsidized fuel. There are at least 4 impacts felt by the community when subsidized fuel prices increase, namely a decrease in people's purchasing power, an increase in basic prices, an increase in the unemployment rate and an increase in the poverty rate. This study aims to implement the Naïve Bayes Classifier and KNN algorithms in classifying a tweet of an increase in subsidized fuel so that it can be identified as belonging to a class with positive or negative sentiments. The data used in this research are 560 tweets. The data is divided into 2, namely 500 training data from tweet data and 60 test data from tweet data stored in xlsx format. The results of the accuracy with the Naïve Bayes Classifier algorithm is 85% while the KN algorithm is 86.8% so it can be concluded that the KNN method is better than the Naïve Bayes Classifier method in classifying tweets of increases in subsidized fuel. Keywords: Subsidized BBM, Naive Bayes, KNN

The government initiated farmer cards to improve the distribution of subsidized fertilizers that were still not on the target. However, in some areas the effectiveness of distributing subsidized fertilizers using farm cards is unknown. This study aimed to determine the effectiveness of subsidized fertilizers in Cibeuti Village, Kawalu District, Tasikmalaya City. The population in this study was farmers who received farmer cards with a total of 559 people who were then sampled using a random sampling technique of 85 people. This research was conducted using two methods, namely observation and interview. Observation is carried out by collecting data carried out through direct observation of farmers included in the farmer group in Cibeuti Village. The data analysis used is  multiple linear regression analysis using the SPSS application. From the results of this study, the level of effectiveness of farmer cards, the distribution of subsidized fertilizers in the Cibeuti area of Tasikmalaya City is very effective and the most effective, indicator of the distribution of subsidized fertilizers is on time, whose efficiency value is 0.005 which means less than 0.05.