This work aims to develop an enhanced Perturbation based Variable Neighborhood Search with Adaptive Selection Mechanism (PVNS ASM) to solve the capacitated vehicle routing problem (CVRP). This approach combined Perturbation based Variable Neighborhood Search (PVNS) with Adaptive Selection Mechanism (ASM) to control perturbation scheme. Instead of stochastic approach, selection of perturbation scheme used in the algorithm employed an empirical selection based on success rate of each perturbation scheme along the search. The ASM helped algorithm to get more diversification degree and jumping from local optimum condition using most successful perturbation scheme empirically in the search process. A comparative analysis with existing heuristics in the literature has been performed on 21 CVRP benchmarks. The computational results proof that the developed method is competitive and very efficient in achieving high quality solution within reasonable computation time.

The purpose of this paper is to explain information and communication technology that can support the field of education in the disruption era, namely Augmented Reality (AR). The contribution of AR in education can provide a learning experience. Vocational education is an education that requires balance between acquiring knowledge and building experiences. In this way, AR can be one of the technologies that support vocational education. We will explain the potential case of AR game development in AR game development that is applied in education, especially in learning chemistry.

In the last few years, the decrease in the land use of soybean affected the reduced of soybean production. Land suitability assessment is an effort to increase the soybean production since the manual method was less accurate. This study aims to apply fuzzy sets and AHP to improve the accuracy of the assessment process of land suitability for soybean crops. The value of five sub-criteria converted into fuzzy sets for standardization process. The weighting by AHP performed to determine the importance level of sub-criteria. Suitability index and final land suitability classes were obtained from the calculation of the fuzzy membership function values and the weights of each sub-criteria before being overlaid with spatial data to produce land suitability map for soybeans. The results of this work showed that 81.42% of the total area was moderate suitability (S2), 11.25% was marginally suitable (S3) and of 7.33% was not suitable (N). From the results of land suitability assessment for soybean crops has been tested and has good correlation with the yield conditions. This study showed that the proposed tool based on Fuzzy sets and AHP were accurate to assess the land suitability of soybean and can be used as the basis for agricultural planning to optimize the land use and soybean production.

The spread of Covid-19 prevention has been carried out widely for example is the use of technology disinfectants. One of the development technologies at this time are drones. This study aims to design a UAV system as a disinfectant sprayer. Hexacopter is a type of drone that can fly more freely in the air that consists of 4 basic movements as throttle, roll motion, pitch motion, and yaw motion. The design method uses the ADDIE model (Analysis, Design, Development, Implementation, Evaluation). The analysis is needed including analysis of hardware and software requirements through a literature study. The design phase is designing concepts from the software. The development phase is to build-up the components into a drone. In the implementation phase by tool testing and an assessment of the implementation will be carried out. This research is an early part of the development of the UAV system. The results that design of UAV system consisting of components used Naza-M V2, a 23-inch propeller mounted on a 180KV Hobbywing X6 motor, ESC 80A, and a 12S 44.2V battery. Based on the results of hexacopter testing that can fly for 6 minutes, the weight is 10kg and works well in spraying disinfectants.

No abstract