Application of the Floyd Warshall Algorithm in Determining the Shortest Route for Distribution of UD Nadira Cinta Rasa Bread to Praya, Central Lombok

Optimizing the shortest route is needed by a company in the process of distributing goods to consumers. This optimization can help companies optimize the mileage and costs from source to destination. In this study, the shortest route method used is the Floyd-Warshall algorithm to determine the shortest route. Floyd-Warshall algorithm can compare all the possible paths in the graph for each side of all vertices it passes with the minimum number. Based on the calculation results of this study, the shortest route was obtained from Mataram as the source and Praya as the destination was 31 km.

Peramalan Penjualan Kendaraan Mobil Segmen B2B dengan Metode Regresi Linear Berganda, Jaringan Saraf Tiruan dan Jaringan Saraf Tiruan – Algoritma Genetika

This study aims to create an effective forecasting model in predicting sales of car products in the B2B segment (Business to Business) to obtain estimates of product sales in the future. This research uses multiple linear regression and artificial neural networks that are optimized by genetic algorithms. Forecasting factors for car sales are generally issued by total national car sales, the Consumer Price Index, the Consumer Confidence Index, the Inflation Rate, Gross Domestic Product (GDP), and Fuel Oil Price. The author has also gotten the factors that play a role in the sale of B2B segment by diverting the survey to 106 DMU (Decision Making Unit) who decide to purchase cars in their company. Then we evaluate the results of the questionnaire in training data and simulations on the Artificial Neural Network. Optimized Artificial Neural Networks with Genetic Algorithms can improve B2B segment car sales' accuracy when comparing error values in the ordinary Artificial Neural Network and Multiple Linear Regression.

Penerapan Metode Hungarian dalam Penugasan Dosen Pengampu Mata Kuliah Program Studi Matematika FMIPA Universitas Mataram

The tight schedule of lecture activities requires accuracy so that it always runs smoothly. Lecturer assignments play an important role to ensure the smooth lecture activities. Problems that often occur in the assignment of these lecturers need to be avoided. In an effort to reduce the risk of problems that occur in the assignment of lecturers, it is necessary to make a structured system with the right method. Hungarian method can be said very appropriate for this assignment problem because each course will only be charged to one lecturer. Another advantage of using the hungarian method in this lecturer assignment model is also because it uses the preferences of prospective lecturers as subjects of measurement. Each lecturer will take courses according to their best preferences with the expectation that the lecturer will have more mastery in the courses that he will teach.

Algoritma Needleman-Wunsch dalam Menentukan Tingkat Kemiripan Urutan DNA Rusa Timor (Cervus timorensis) dan Rusa Merah (Cervus elaphus)

Sequence alignment is a basic method in sequence analysis. This method is used to determine the similaritiy level of DNA sequences. The Needleman-Wunsch algorithm is an algorithm that can be used to solve the problem of sequence alignment. This research shows that the relation T (i, j) used in the Needleman-Wunsch algorithm is a function where T: (ℕ0 ℕ0) → ℤ. The function T (i, j) is a recursive function. Moreover, DNA sequence data used are DNA sequences from the Timor Deer, which are the identities of the provinces of West Nusa Tenggara and Red Deer, which are typical deer from the European continent as a comparison. The DNA sequence data was obtained from BLAST (Basic Local Alignment Search Tool). Based on the alignment, the most optimal alignment is obtained by forming 666 base pairs sequences with 322 matches, 230 missmatches and 114 gaps, meaning that the two DNA sequences have a 48% similarity (322/666).

Regresi Nonparametrik Kernel Gaussian pada Pemodelan Angka Kelahiran Kasar di Provinsi Nusa Tenggara Barat

This study aims to model Crude Birth Rates (CBR) in West Nusa Tenggara Province. The nonparametric regression method was used in this research by considering data distribution patterns that do not show a linear relationship between variables. In this case, the kernel nonparametric regression using the Gaussian function and the Nadaraya-Watson estimator. The results showed optimal bandwidths of 0.55542837, 1.29042927, 0.94706041, and 0.92278896 with a value of minimum Generalized Cross-Validation (GCV) of 0.000000000432613511, which was minimized by the simulated annealing algorithm. The resulting model's accuracy can be seen from the coefficient of determination (R2) of 99.23% and the Mean Absolute Percentage Error (MAPE) of 0.007049%.

Optimasi Penyaluran Bahan Bakar Minyak di Wilayah Maluku Indonesia

Fossil fuel (BBM) is a vital commodity and has a strategic value for people's lives. On the demand side, the need for BBM tends to increase along with the increasing energy demand for people's lives. Therefore, the distribution system for BBM has to be optimized in order to fulfill the people’s demand. The aim of this paper is to optimize vehicle route for BBM distribution in Maluku so that it has minimum cost, distance, and time. The optimization method in this paper is Mix Integer Linear Programming (MILP). Decision variables in this paper are chosen from the most significant variables for BBM distribution in Maluku.