Analysis of Efficiency of Least Trimmed Square and Least Median Square Methods in The Estimation of Robust Regression Parameters

<span lang="EN">Robust regression is a regression method used when the remainder's distribution is not reasonable, or there is an outreach to observational data that affects the model. One method for estimating regression parameters is the Least Squares Method (MKT). The method is easily affected by the presence of outliers. Therefore we need an alternative method that is robust to the presence of outliers, namely robust regression. Methods for estimating robust regression parameters include Least Trimmed Square (LTS) and Least Median Square (LMS). These methods are estimators with high breakdown points for outlier observational data and have more efficient algorithms than other estimation methods. This study aims to compare the regression models formed from the LTS and LMS methods, determine the efficiency of the model formed, and determine the factors that influence the production of community oil palm in Langkat District in 2018. The results showed that in testing, the estimated model of the regression parameters showed the same results. Compared to the efficiency estimator and the error square value, it was concluded that the LTS method was more efficient. Variable land area and productivity influence the production of palm oil smallholders in Langkat District in 2018. as well as the comparison of the efficiency estimator and the error square value, it was concluded that the LTS method was more efficient. Variable land area and productivity are factors that influence the production of palm oil smallholders in Langkat District in 2018. as well as the comparison of the efficiency estimator and the error square value, it was concluded that the LTS method was more efficient. Variable land area and productivity are factors that influence the production of palm oil smallholders in Langkat District in 2018</span>

Using of EOQ and EPQ Methods in Minimizing Inventory Cost of Crude Palm Oil

<span lang="EN-US">Excess or lack of inventory that is too large is a problem that can trigger increased costs so that companies do not get the benefits they should. The purpose of this study is to minimize the cost of inventories of crude palm oil using the EOQ (Economic Order Quantity) method and EPQ (Economic Production Quantity) methods at PT. Perkebunan Nusantara IV (Persero) Medan. From the results it is known that economic orders according to the EOQ method in 2017 amounted to 2.741,222 tons and in 2018 amounted to 2.825,927 tons. The difference in total inventory costs generated using the EOQ method and company conditions in 2017 amounted to Rp71.605.439.976,17 and in 2018 amounting to Rp60.884.174.907,3. The optimal amount of production (EPQ) in 2017 and 2018 was 146.226,147 tons. The difference in total inventory costs generated using the EPQ method and the condition of the company in 2017 and 2018 amounted to Rp102.771.704.121,63.</span>

Application of Whale Optimization Algorithm (WOA) on Quadratic Knapsack 0-1 Problem

<span lang="EN">Quadratic Knapsack Problem is a variation of the knapsack problem that aims to maximize an objective function. The objective function in this case is quadratic. While the constraints used are binary and linear capacity constraints. The Whale Optimization Algorithm is a metaheuristic algorithm that can solve this problem. Therefore, this paper aims to find out the best solution to solve the Knapsack 0-1 Quadratic Problem using the Whale Optimization Algorithm so that its effectiveness and efficiency are known. Based on the research has been done, the algorithm is said to be effective because, from each experiment, the algorithm is always converging or towards maximum profit. Also, with the right parameters, the algorithm can achieve optimal results. It is said to be efficient because getting optimal profit does not require more time and iteration. The combination of item parameters and maximum iteration dramatically Affect the total value of profit and its running time. However, the addition of item parameter combinations is faster to achieve optimal than the maximum iteration parameter.</span>

Variation Of Rotation In Chaos Game By Modifying The Rules

<span>The core concept of fractals is the process of rearranging identical components that have a large amount of self-similarity. One example of fractals is the Sierpinski trianglecan be generated using the chaos game method. This method is a form of play in drawing points on triangles that have certain rules and are repeated iteratively. This research will modify the rules of chaos game triangle with the addition of various rotationswith the center of rotation at one, two, three, four, and five reference points. The visual results obtained are in the form of fractals because they have self-similarity properties and a collection of new points formed experiences rotation with the center of rotation based on the selected reference point with the direction of rotation based on the rules. The visual results of the rotation </span><span>θ</span><span> angle are visually symmetrical about the axis-y with the visual results of the rotation 360</span><span>⁰</span><span>-</span><span>θ</span><span> angle at one, three, four, and five reference points as the center of rotation. At two reference points as the center of rotation it is obtained that there are two parts that are visually symmetrical about a certain line. Visual results of rotation 360</span><span>⁰</span><span> angles at one, two, three reference points as the center of rotation have a shape similar to the Sierpinski triangle. Whereas at four and five points of reference as the center of rotation has a shape similar to the Sierpinski triangle.</span>

Cluster Analysis Using the Hierarki Method For Grouping Sub-Districts in The District Steps Based on Health Indicators

<span lang="EN">Cluster analysis is a method used to group objects based on similarity of characteristics they have. Cluster analysis using the hierarchy method is a method with a grouping process that is used in stages. Health is a condition where a person is not sick, has no complaints, and can carry out daily activities. To find out information about the level of health in Langkat Regency, it is necessary to use the grouping method. The grouping was carried out in 23 districts in Langkat Regency. The purpose of this study is to classify sub-districts in Langkat Regency which have similar characteristics based on health indicators through the square euclidian distance is used to measure the similarity between object pairs and the ward method. From the results of cluster analysis using the ward method.</span>

NAIVE BAYES ALGORITHM IN PREDICT GRADUATION OF STUDENTS

<p><strong><em>Abstract.</em></strong><em> </em><em>The University of XYZ is a well established university which has five faculties with one of them is post graduate. Charging with a very low cost of tuition fee has attracted so many high school graduation and make it becoming the university with the bulk number of students. It has caused one subject is taught by more than one lecturer. This research is using quantitative analysis method with Naive Bayes Algorithm methodology in passing decision on PTI (Pengantar Teknologi Informasi) subject. The result gives pattern of training data in mean and standard deviation towards three attributes, i.e. tasks, mid-semester and final exam score, which can classify or predict graduation for new data test. The pattern of this equation can also be used for other class classification, on the same or different subjects. </em></p>

DECISION SUPPORT SYSTEM DETERMINING THE LEVEL OF PUBLIC SATISFACTION OF THE CITY WITHOUT SLUMS PROGRAM (KOTAKU) IN PNPM MANDIRI IN DELI SERDANG DISTRICT USING THE MULTI-ATTRIBUTE UTILITY THEORY METHOD

<p><strong><em>Abstract </em></strong><em>To evaluate the success of the Kotaku program (City Without Slums) in PNPM Mandiri in Deli Serdang Regency, a study is needed to determine the level of community satisfaction with the results of the Kotaku program. Then in this study, a decision support system will be built to assist in determining the level of community satisfaction with the Kotaku program. The method chosen to support the above problem solving is Multi-Attribute Utility Theory (MAUT). The system design is done by using Unified Modeling Language (UML) modelling and accompanied by a system interface design. The advantage of this system is that it can perform calculations very quickly and effectively. This decision support system shows that with the advancement of science and technology it can help in determining the right level of community satisfaction by following the correct considerations and calculations. But there are still some weaknesses of the system including this system has a simple interface and does not have the feature to backup the database. </em></p>

Application of K-Means Clustering Method for City Grouping on Food Plant Productivity in North Sumatera

The development of population increases every year, causing food needs to expand to meet food needs by increasing food crop productivity so that food availability can be sufficient. Food crops consist of rice, corn, green beans, peanuts, cassava, and sweet potatoes. Productivity in each region has different characteristics, and therefore it is necessary to group the areas so that solution can be implemented by each of the components of the region. The purpose of this study is to group districts/cities in North Sumatera Province based on food crop productivity using the k-means clustering method. Clustering k-means is a method of grouping non-hierarchical data that attempts to partition existing data into one or more clusters or groups so that data that has the same characteristics are grouped into one same characteristic are grouped into other groups. The result of this study is the formation of 3 city district clusters, namely, cluster 1 amounting to 1 regency/city, cluster 2 totaling seven districts/cities, and cluster 3 totaling 25 districts/cities.

Implementation of Electre Method in Determining Tourism Places in North Sumatera

A tourist in determining the purpose of his tour, must be based on several criteria that are used as a determining factor in choosing. These criteria are taken into consideration by tourists in determining which tourist attractions will be chosen. Thus this study aims to assist tourists in choosing tourist attractions in North Sumatra based on the desired criteria and / or provide information to tourists about the best tourist attractions in North Sumatra in accordance with the desired criteria. The Elimination Et Choix Traduisant La Realita (ELECTRE) method which is a system that uses a multicriter decision making method based on the outranking concept by using a pairwise comparison of alternatives based on each appropriate criterion. This research resulted in a recommendation for natural tourist attractions in North Sumatra, namely Teluk Dalam tourism in the Nias Islands.

Data Analysis Time Series For Forecasting The Greenhouse Effect

<span lang="EN-US">The greenhouse effect is a term used to describe the earth having a greenhouse effect where the sun's heat is trapped by the earth's atmosphere. This study aims to model the greenhouse effect and then predict the greenhouse effect in the coming period using the Autoregressive Integrated Moving Average (ARIMA) method. In this case, time series analysis and reference data for 31 months are used, from the period January 2017 - July 2019, the results of the ARIMA model that are suitable for forecasting the greenhouse effect are ARIMA (4.2.0) with Mean Square Error (MSE) of 161885</span>