Abstract. Potato production is strongly influenced by the selection of suitable land for crops. Criteria for land suitability of planting potatoes is influenced by climatic factors and land characteristics. planted area clustered based on 11 criteria land suitability. The clustering results in the form of four clusters, namely: very suitable (S1), appropriate (S2), is quite suitable (S3) and are not suitable (N). Clustering of land aims to improve the quality and quantity of the potato crop. Clustering is done using a hybrid Particle Swarm Optimization with K-Means (KCPSO). The hybrid method is used to obtain an accurate result cluster. In this study used a new approach to doing improve KCPSO with random injection method. The calculation of the value of cost based on the silhouette coefficient. The results obtained KCPSO showed better results when compared to using the K-Means algorithm without hybrid. The calculation result KCPSO get the best centroid indicated by the value of the largest Silhouette coefficient.Keywords: Clustering, K-Means, Particle Swarm Optimization, random injection, silhouette Coefficient.

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Companies engaged in agro-industry, such as rice seed companies, depend on an efficient distribution process because of the characteristics of rice seed products that are easily damaged and do not last long. The distribution and delivery of goods from the production plant to reach consumers must go through several local distributors in several areas (multi-level) such as distributor centers, retailers, and agents spread across several cities in East Java Province. Determining the distribution network will be more complex when a company produces more than one type of product (multiproduct). Based on previous research, the genetic algorithm (GA) has been proven to provide the best solution for various optimization and combinatorial problems. However, the application of classical GA has the drawback that it has not yet reached the optimum global point, so it needs to be hybridized using a variable neighborhood search (VNS) algorithm. VNS was chosen because it can find solutions globally and find solutions locally to cover the shortcomings of GA. Using hybridization of GA-VNS, the cost obtained is 32392960, as evidenced by the cost savings of 323190 compared to the classic GA of 32716150. GA-VNS takes relatively the same time as classic GA.

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SuperH-antimagic total labeling (SHATL) can be utilized to generate encryption keys. The keys are then used to establish the improved block and stream ciphers. In these ciphers, different blocks were encrypted by the different keys, but all block keys were connected one another. These conditions make the developed cryptosystems more secure and require less keys storage capacity compared to the ordinary block and stream cipher. The randomness of the generated keys, however, still need to be tested. The test is necessary to ensure that there is no specific pattern that can be utilized by any intruder to guess the keys. This paper presents the randomness tests applied to all key sequences generated by both the improved block scheme and the stream based scheme.