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Indonesia is the world’s largest palm oil producer and exporter, can produce 230 kg of OPEFB. The utilization of OPEFB is still at 10%, even though OPEFB is composed of 37.26% cellulose. This research aims to find out how to synthesize and characterize cellulose acetate from OPEFB cellulose into membrane material. The synthesis of cellulose acetate using the acetylation method is carried out in several processes. The activation process expands the surface of the cellulose fibers. The acetylation process is intended to substitute cellulose hydroxyl groups with acetyl groups. The hydrolysis removes some acetyl groups from trimester cellulose and reduces the combination of sulfate esters. In the results of FTIR analysis, carbonyl groups (C=O) and acetyl groups (C-O) have high peak depths in OPEFB cellulose acetate. Based on the calculation of acetyl content, OPEFB cellulose acetate has an acetyl content of 39.82% with a degree of substitution of 2.44. The results of XRD analysis show that OPEFB cellulose acetate has a crystallinity index of 34.5%. In TGA analysis, the thermal stability of cellulose acetate is up to a temperature of 210°C. Based on the research results, OPEFB cellulose can be synthesized into cellulose acetate using the acetylation method.

Information and communication technology is growing rapidly, making it the target of various attacks. The attacks can be in the form of data theft, phishing, and Denial of Service (DoS). There are many ways to handle attacks on communication networks, including developing an Intrusion Detection System (IDS) model. Research on IDS has developed a lot and focuses on certain things such as feature selection, dealing with data imbalance problems. Feature selection is essential to the IDS model because of the dataset's characteristics, which have many features. Besides, the number of features included in the classification can affect the detection performance of the IDS model. This research proposes an IDS combining mutual information with thresholding feature selection and XGBoost classification algorithm. Mutual information is used to measure the dependency between every input feature and the target features. After the amount of information is obtained with mutual information, thresholding is used to decide the best number of features in the classification process. Then, the data are classified using XGBoost selected features. The proposed method was tested using four metrics: accuracy, precision, recall, and f1-score. This study used UNSW-NB15 as the primary dataset to analyze the best combinations of feature selection method and thresholding value. In addition, the proposed method has also been tested using NSL-KDD and CIC-IDS2017 datasets to evaluate the performance compared with previous research. The proposed method performs best using the CIC-IDS2017 dataset with 99.89 % accuracy and 99.68 % F1 score. Furthermore, it can reduce computational training time compared with other IDS methods that only use feature selection or tree-model-based algorithms without thresholds. [ABSTRACT FROM AUTHOR]

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One of the important problems that often occur in rural communities is attention to waste. Data on waste in Indonesia from 2019 to 2020 is observed to continue to increase in number. Waste data for that year was 66-67 tons in 2019 and increased to 67.8 tons in 2020. Therefore, it is necessary to have BUMDes that are willing to manage waste and benefit from these activities. This study will focus on discussing the problem of the role of BUMDes in improving the residents' economy by empowering and managing waste by Kreto Makmur BUMDes. The type of research used in this research is qualitative research. This research uses a case study approach. The instruments of this research are interview guidelines and document collection related to waste management by BUMDes. The data analysis process is carried out continuously (cyclically) since the researcher enters the field until the research activity ends. The analysis techniques of research results are: (1) data collection; (2) data reduction; (3) data presentation; (4) conclusion/verification. The results of this study are BUMDes have a significant role in empowering the Miagan Village community, one of which is waste management. From this management, the village government and BUMDes are able to contribute PAD of 6,000,000 rupiah per month. [ABSTRACT FROM AUTHOR]