Analysis and Design of Inventory Control Information Systems With Forecasting Methods: Moving Average and Exponential Smoothing

Inventory inventory on CV. Mitra Marga Sejahtera often experiences stockpiling of goods so that it wastes more costs and the manual process of recording goods using excel, so that they often experience data corruption and loss of sales data. Forecasting methods are usually used by the sales department in planning (sales planning) based on the results of sales forecasts, so that forecasting information can be useful for Production which uses Moving Average and Exponential Smoothing. the program that has been made using the forecasting method can help manage the stock of goods that will be needed in the coming months, so that store managers can save costs in stock items that are not excessive

The Analysis and Design Marketplace Information Systems Web-Based of Electronic Repair Service Providers with Haversine Method

This system is designed to help customers find electronic service centers were spread in Tangerang. The distribution of electronic service center makes it difficult for users to determine the right electronic service center. Sometimes customers don’t know the results of repairs from the electronic service center. Search for electronic service center on the system is using the Haversine method. Haversine is used to calculate the distance between the position of the customer and the position of the electronic service centers. In addition to Haversine, the search for electronic service center will be adjusted to the type of goods you want to repair and rating from the results of the performance electronic service center. In this system, the customer can choose the damage diagnosis available and the customer can also make a special order by describing the customer's damage. This system was tested using Black Box Testing with Boundary Value Analysis technique, based on the results of testing the system can use data with a success percentage of 96.66%. The system is tested with User Acceptance Testing to find out how much the level of user acceptance of the system designed, and the result is 75% of users agree with the system.

Extraction Opinion of Social Media in Higher Education Using Sentiment Analysis

The purpose of this research is to extract social media Twitter opinion on a tertiary institution using sentiment analysis. The results of sentiment analysis will provide input to universities as a form of evaluation of management performance in managing institutions. Sentiment analysis generated using the Naïve Bayes Classifier method which is classified into 4 classes: positive, normal, negative and unknown. This study uses 1000 data tweets used for training data needs. The data is classified manually to determine the sentiment of the tweet. Then 20 tweet data is used for testing. The results of this study produce a system that can classify sentiments automatically with 75% test results for sentiment, some obstacles in processing real-time tweets such as duplicate tweets (spam tweets), Indonesian structures that are quite complex and diverse.

Employee Performance Assessment Decision Support Using Profile Matching Method Compared to Simple Additive Weight Addition at Dharma Buddhi University, Tangerang

An employee performance evaluation of the Buddhist Dharma University is needed to see the potential of its human resources. To get an employee performance appraisal in one year requires a decision support system that is fast and measurable so that the information obtained is accurate. The method used in assessing employee performance uses profile matching and is compared with the SAW (simple additive weight) method so that the results can be properly compared. The purpose of employee appraisal is so that leaders can easily obtain information about employee performance ratings at Buddhii Dharma University. The results of the value using the profile matching method can be recommended for salary increases and positions of 4 employees. Which can be recommended for salary increases there are 17 employees and those who are not eligible for salary increases and positions are valued at 12 employees. And comparing with the Simple Additive Weight (SAW) method, there are 19 employees who are eligible to raise salaries and 14 employees who are not eligible to raise salaries and positions

Decision Support System for Selection of Assembly Using Profile Matching Method and Simple Additive Weighting Method (Case Study: GKIN Diaspora Church)

The church is a place of worship for Christians who are worshipers, in the church there are many organizers called the assemblies whose task is to regulate and manage all kinds of operational activities related to the worship held on Sundays, the duties and authorities of an assembly are in each position he has. To be a church administrator or assembly can be chosen by the congregation by conducting a selection process from the assemblies in the church and to be appointed by the pastor. The process of selecting the assembly can be an error to choose the assembly that can be subjective. Then a system for decision-making decision support is made using the Profile Matching Method and Simple Additive Weighting (SAW) Method. Where Profile matching is a decision support method using calculation of weight and weighting by dividing the main factors and supporting factors. And using the Simple Additive Weighting (SAW) method is a weighted housing method, by normalizing the decision decision matrix (x) to a scale that can be compared with all available alternative ratings

Optimization of Application of Genetic Algorithm Using C4.5 Method to Predict Breast Cancer Disease

Cancer is a big challenge for humanity. Cancer can affect various parts of the body. This deadly disease can be found in humans of all ages. However, the risk of cancer increases with age. Breast cancer is the most common cancer among women, and is the biggest cause of death for women. Then there are problems in the detection of breast cancer, causing patients to experience unnecessary treatment and huge costs. In a similar study, there were several methods used but there were problems due to the shape of nonlinear cancer cells. The C4.5 method can solve this problem, but C4.5 is weak in terms of determining parameter values, so it needs to be optimized. Genetic Algorithm is one of the good optimization methods, therefore the parameter values ​​of C4.5 will be optimized using Genetic Algorithms to get the best parameter values. The results of this study are that C4.5 Algorithm based on genetic algorithm optimization has a higher accuracy value (96%) than only using the C4.5 algorithm (94.99%) and which is optimized with the PSO algorithm (95.71%). This is evident from the increase in the value of accuracy of 1.01% for the C4.5 algorithm model that has been optimized with genetic algorithms. So it can be concluded that the application of genetic algorithm optimization techniques can increase the value of accuracy in the C4.5 algorithm.

Drop Out Students Identification Using Knowledge Base

The purpose of this study is modeling for the initial identification of college dropout students. Samples were taken from drop out student data for the past 4 years. Information from this sample will be acquired as a knowledge base in system modeling. The research aims to provide a knowledge-based system approach using Dempster Shafer for the management of student drop outs at universities especially in Yogyakarta. The symptoms of DO students are obtained from knowledge about DO that appears on campus in Yogyakarta. The system output is in the form of 3 groups of classification namely initial potential DO, enough potential and once potential. The results of the study produced a system that could help university managers deal with drop-out problems early.

Sales Analysis Using the Forecasting Method

Sales Analysis Using Forecasting Method aims to improve effectiveness and efficiency that facilitates companies in business transaction processes, improve the delivery of information quickly, accurately, and transaction data well and minimize errors. The method used in the presentation of this scientific work is by using a forecasting method which helps determine the approximate stock of goods to come. With 3 forecasting modules are: Moving Average, Weighted Moving Average, Trend Projection is used to perform the forecasting process of the upcoming stock of goods. Can solve problems that exist in the current system so that it can help in improving its services by calculating the stock and helping by determining the average data that has been linked to the forecasting module whose results can be concluded through reports per period. It can be concluded that the results of implementing this new system can help companies in recording each transaction that occurs becomes more efficient and effective, so that it can overcome the problems that exist in the current system. With this we can predict the current flow of goods that have been calculated based on 3 (three) modules that have connections with the system

The Hotel Recommendation System Using SAW (Simple Additive Weighting) And TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) Method

Tourism is one of the important economic sectors in Indonesia that needs to be developed. This is based on data of the number of tourist visits from “Kementrian Pariwisata Republik Indonesia” website that the number of tourists in Indonesia is very much and continues to increase over time. Due to the increasing number of tourist visits from various places, makes many entrepreneurs are competing to establish a hotel as a place of business with variety of price, class, facility and service. Then, the growth of the hotels became very rapid. With so many choices of the hotels, of course it will cause a problems for tourists to decide which hotel is suitable with the desired criteria. With the development of information technology in this era of globalization, technology should be utilized to solve this problem as a decision support system that can recommend which hotel is the most suitable from the tourist desires. The hotel data to be used in this research comes from hotel search site. The methods used for this decision support system are SAW and TOPSIS methods. The reason for using this methods is because SAW has the ability to assess more accurately because it is based on criteria and the computation of TOPSIS method is efficient and fast. The criteria used on choosing the hotel are price, facilities and class. The results of this research has been generated as a web-based application for hotel recommendation. Based on the test results of this hotel recommendation system application, this application works as expected.

Development of the Human Resources Information System (HRIS) Based on Usability Analysis with Usefulness, Satisfaction, Ease to Use (USE) Questionaire and Cognitive Walkthrough Methods

HRIS application is an application that is needed to manage human resources well and integrated the system. Usability in a system is very necessary in the development of a system so that it can affect the use of the application. The author tests the usability user interface on HRIS products using the cognitive walkthrough evaluation method, which works through a series of task scenarios and asks a number of questions from the user's perspective, and the method of usefulness, satisfaction, ease of use (USE) Questionnaire to assess how much usability is done by the user. The cognitive walkthrough testing is done by using the application that has been made by the author, after that the author makes improvements to the system according to the results of the test. Then after being repaired, the system was tested again with the same application, then the results were assessed using the USE Questionnaire and compared with previous results. The result is that the system has increased from previously by 3.67 from a scale of 1-5 to 4.04, up by 0.34.