Peningkatan Pemahaman Materi Struktur Daun Melalui Metode Quantum Pada Siswa Kelas IV SD N Kroyo 1 Kecamatan Karangmalang Kabupaten Sragen Tahun Pelajaran 2017/2018

The objectives of this classroom action research are: to optimize leaf structure using Quatum method to increase understanding in grade IV students of State Primary School of Kroyo 1 in Karangmalang Subdistrict, Sragen Regency, in the academic year of 2017/2018 and explain how to implement quantum learning model in improving science learning outcomes at leaf structure structure of grade IV students of State Primary School of Kroyo 1 in Karangmalang Sub-district, Sragen Regency in the academic year of 2017/2018. The objective of this research is to improve the cognitive ability in Natural Science through the Quantum learning method of the students in Grade IV of State Primary School of Kroyo 1 in Karangmalang Sub-district, Sragen Regency in the academic year of 2017/2018. This research is a classroom action one with two cycles. Each cycle consisted of four phases, namely: planning, implementation, observation, and reflection. The subject of the research was all of the students in grade IV of State Primary School of Kroyo 1 in Karangmalang Sub-district, Sragen Regency in the academic year of 2017/2018. Its data were gathered through observation, document analysis (content analysis), and in-depth interview. The data were then analyzed by using an interactive model of analysis comprising three components, namely: data reduction, data display, and conclusion drawing or verification. The result of the research shows that there is an improvement of cognitive ability in Natural Science of the students in grade IV of State Primary School of Kroyo 1 in Karangmalang Sub-district, Sragen Regency in the academic year of 2017/2018, who were taught with the Quantum learning method. This is indicated by their cognitive tests. Prior to the treatment, the average score of their cognitive test is 76,53, and the percentage of the students completing the learning is 71,8%. Following the treatment of cycle I, the average score improves to 81,41 and the percentage of students completing the learning is 79,49%. After the treatment of cycle II, the average score improves to 87,31, and the percentage of the students completing the learning is 100%

Optimization of Multiple Depot Vehicle Routing Problem (MDVRP) on Perishable Product Distribution by Using Genetic Algorithm and Fuzzy Logic Controller (FLC)

Distribution has a large portion of the total cost of sales of goods or product. It cause high cost transport and risk to the quality of the goods which are distributed, especially perishable product. Perishable product quality is greatly influenced by distribution, thus when the distribution not optimal, it will risk very big deal of broken product. In connection with this matter, the distribution process needed to optimize especially to perishable product. Optimal distribution problem can be solved using Multiple Depot Vehicle Distribution Routing Problem (MDVRP) model, which was development of Vehicle Routing Problem (VRP). To get the optimal solution of MDVRP, genetic Algorithm (GA) was used. Using GA, more than one alternative solution with good fitness value were gained. Then Fuzzy Logic Controller (FLC) was used to control these parameter values in order not to trap into local optimum. After new pm and pc value were obtained, the GA process was conducted to get the shortest route. The result of this research showed that the value of the probability of crossover and mutation affected the fitness values. The higher fitness value, the smaller the distance which reached. It will reduce the risk of rot caused by travel time. Testing results showed some alternative solutions which is not much different in fitness value. Level of optimality increased when FLC process were conducted. From 10 times evaluation reached 89, 9%