Suchergebnisse

Indonesian government agencies under the Ministry of Energy and Mineral Resources have problems in classifying data dictionary of coal. This research conduct grouping coal dictionary using KMeans and MeanShift algorithm. K-means algorithm is used to get cluster value on character and word criteria. The last iteration of Euclidian distance calculation data on k-means combine with Meanshift algorithm. The meanshift calculates centroid by selecting different bandwidths. The result of grouping using k-means and meanshift algorithm shows different centroid to find optimum bandwidth value. The data dictionary of this research has sorted in alphabetically.

Abstract— In this pandemic era, the government is forced to implement policies that can reduce the daily positive rate of COVID-19. One of these policies is known as PPKM. It is unclear when the pandemic will end, causing data phenomena to be scattered on social media, one of which is Twitter. Therefore, in this study, we conducted an analysis of sentiment originating from tweets from Twitter social media users in the Jakarta area regarding the government's policy, namely PPKM in the face of the COVID-19 pandemic. In this research, we use a Machine Learning approach, namely LSTM. This modeling produces a classification of positive and negative sentiments. The dataset used is 3000 tweets with a time period of September - November 2021. At the preprocessing stage, the data that are ready to be used for modeling are 2176. The results of this study get an accuracy of 0.943. So the model that we propose, namely LSTM, has succeeded in classifying a satisfactory sentiment with a positive number of 92% and a negative 8% of 2176 sentiments, so it can be concluded that the PPKM policy implemented by the Indonesian government in the DKI Jakarta area is said to be effective or positive.

The Government of the Republic of Indonesia is currently focusing on building logistics infrastructure to facilitate the distribution of logistics to all regions in Indonesia. The Distribution of logistics to each area requires an electronically connected warehouse so that information about goods in the warehouse can be monitored continuously. There are some problems with one of the logistics companies because the existing warehouse management technology is not sufficient enough, so the complex warehouse functions do not become dynamic. One of the solutions to solve the problem need to use RFID technology, conveyor belt, and robotic arm by using an Arduino microcontroller. This research uses Design Science Research Methodology which focuses on developing and improving the model performance of a system and using the prototyping model for system development. The test results state that the built system works well because it could lift, identify and sort goods by type. So, this research could answer the problem that happened at the warehouse.

Indonesian government agencies under the Ministry of Energy and Mineral Resources still use manual methods in determining and selecting proposals for operational activities to be carried out. This study uses the Decision Support System (DSS) method, namely Fuzzy Multiple Attribute Decision Decision (Fmadm) and K-Means Clustering method in managing Operational Plan activities. Fmadm to select the best alternative from a number of alternatives, alternatives from this study proposed activity proposals, then ranking to determine the optimal alternative. The K-Means Clustering Method to obtain cluster values for alternatives on the criteria for activity dates, types of activities, and activity ceilings. The last iteration of the Euclidian distance calculation data on k-means shows that alternatives that have the smallest centroid value are important proposal criteria and the largest centroid value is an insignificant proposal criteria. The results of the collaboration of the Fmadm and K-Means Clustering methods show the optimal ranking of activities (proposal activities) and the centroid value of each alternative.

Indonesian government agencies under the Ministry of Energy and Mineral Resources have problems in classifying data dictionary of coal. This research conduct grouping coal dictionary using K-Means and MeanShift algorithm. K-means algorithm is used to get cluster value on character and word criteria. The last iteration of Euclidian distance calculation data on k-means combine with Meanshift algorithm. The meanshift calculates centroid by selecting different bandwidths. The result of grouping using k-means and meanshift algorithm shows different centroid to find optimum bandwidth value. The data dictionary of this research has sorted in alphabetically.

The Government of the Republic of Indonesia is currently focusing on building logistics infrastructure to facilitate the distribution of logistics to all regions in Indonesia. The Distribution of logistics to each area requires an electronically connected warehouse so that information about goods in the warehouse can be monitored continuously. There are some problems with one of the logistics companies because the existing warehouse management technology is not sufficient enough, so the complex warehouse functions do not become dynamic. One of the solutions to solve the problem need to use RFID technology, conveyor belt, and robotic arm by using an Arduino microcontroller. This research uses Design Science Research Methodology which focuses on developing and improving the model performance of a system and using the prototyping model for system development. The test results state that the built system works well because it could lift, identify and sort goods by type. So, this research could answer the problem that happened at the warehouse.