Purpose: VPN networks in multi-region scope have various challenges, such as in terms of Quality of Service (QoS) and security, especially when using the Layer 2 Tunneling Protocol (L2TP) protocol. This research aims to analyze the quality of QoS based on Telecommunications and Internet Protocol Harmonization Over Network (TIPHON) standardization in multi-region networks using the L2TP protocol without IPsec. Design/methodology/approach: Tests were conducted using experimental methods through the GNS3 simulator to simulate network topology and Wireshark to check QoS results, such as throughput, delay, and packet loss. Findings/result: Based on the test results, the throughput and packet loss values are obtained in a very good category, but for the delay value is in a very low category based on TIPHON standardization.
Purpose: This study aims to analyze public sentiment toward illegal parking on platform X and provide insights to policymakers regarding public perceptions.Design/methodology/approach: The study employs the IndoBERTweet model, spesifically design for sentimen analysis in Indonesian. The process includes data collection from X, pre-processing to remove noise, labelling sentiments as positive, negatice, or neutral, and evaluating the model based on its accuracy and ability to handle informal language on social mediaFindings/result: The results show that the IndoBERTweet model archieved an accuracy of 90.46%, with most sentiments being negative, reflecting public dissatisfaction with illegal parking attendants. The model has proven effective in understanding the complexity of informal language on social media.Originality/value/state of the art: As an extension of IndoBERT, IndoBERTweet demonstrates superior performance in handling informal language compared to other methods. This study also provides recommendations for addressing the limitations of a small dataset by applying methods such as SMOTE or ensemble learning to improve accuracy for minority sentiments.
Purpose: For most paper printing shops, especially those that are still small and not too sophisticated, the existence of quite a lot of paper cutting scraps is a problem. If there is a request for paper cutting for various sizes, they still use manual methods to draw the cutting pattern, this causes a lack of time efficiency and optimization of the remaining paper cutting. This research discusses the optimization of paper cutting patterns in a two-dimensional Cutting Stock Problem in one of the paper printing shops in Bandung, where cutting only takes into account the length and width of the raw material (stock). Design/methodology/approach: The method used is the Greedy Randomized Adaptive Search Procedure algorithm whose initial solution is combined with the Linear Congruential Generator algorithm and the optimal solution is refined with the Integer Linear Programming model. Findings/result: The results showed that there were 3 optimal cutting patterns, namely the 3rd pattern cut 10 sheets, the 10th pattern cut 162 sheets and the 23rd pattern cut 57 sheets. The remaining paper cutting is 413455 cm2 . Originality/value/state of the art: The existence of this research makes it easier for printers to make patterns and minimize the remaining paper cuts without the need to calculate manually.
Rain classification consists of several categories of rain, such as light rain, moderate rain, and heavy rain. Classification is also useful in managing water resources and disaster mitigation, both floods and landslides. One of the methods used to classify rainfall is K-Nearest Neighbor (KNN). However, KKN has a weakness, namely in determining the value of the parameter k which is not maximized. Therefore, to cover the weaknesses of the KNN method, an optimization is needed for the K value using the Particle Swarm Optimization method so that the accuracy results obtained are optimal..PSO will optimize the selection of K values by initializing the respective K value particles used for KNN classification, then updating the position and velocity based on PBest and GBest. The process will be repeated in certain iterations until the criteria are met and will produce an optimal K value. The optimized K value will then be used for the KNN classification process.Based on the model that has been made with a total of 525578 training data and 41268 test data has the most optimal K value, namely K = 7. From the K value by testing using the confusion matrix obtained an accuracy of 99.88%. From optimizing using PSO on KNN, getting a better time in selecting K values is 3 minutes 52 seconds, whereas without optimizing using PSO on KNN, you get approximately 5 minutes. This proves that PSO optimization on KNN can provide good time efficiency in selecting the most optimal K value
Purpose: Inheritance in Islamic law involves various complex elements such as the rights of heirs and the provisions set forth in the Qur'an and Hadith. This study develops a rule-based expert system to facilitate the calculation and distribution of inheritance according to Islamic Sharia. Design/methodology/approach: The research methodology includes literature review, observation, needs analysis, system design, system implementation, and system testing. With rule-based reasoning technology, this system is expected to expedite the inheritance process and help the community understand their rights and obligations. Findings/result: White box testing demonstrates the system's reliability in handling various input scenarios, from handling empty inputs to validating the number of heirs. Black box testing confirms that all key features of the application, including login, registration, consultation, and inheritance calculation, function properly and meet expectations. Expert validation also shows that the calculations performed by the system align with manual calculations by experts. The results of this study indicate that the developed rule-based expert system can effectively manage the inheritance process in Islamic law, reduce potential conflicts, and enhance the understanding of heirs regarding the Sharia rules that must be followed.
