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Journal : EDUMATIC: Jurnal Pendidikan Informatika

Single Exponential Smoothing: Metode Peramalan Kebutuhan Vaksin Campak Annisa Azzahra; William Ramdhan; Wan Mariatul Kifti
Jurnal Pendidikan Informatika (EDUMATIC) Vol 6, No 2 (2022): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v6i2.6299

Abstract

The importance of the measles immunization vaccine for children up to the age of 9 months to prevent children from getting sick with measles or reduce the transmission rate in the surrounding environment, especially at the Gambir Health Center.  This demand is still considered ineffective and there is often an oversupply of vaccines, which results in a buildup of vaccines in storage. The purpose of this study was to create a measles vaccine needs forecasting system using the Single Exponential Smoothing (SES) method. The model used to build this system is the Systems Development Life Cycle (SDLC) with stages of analysis, design, implementation, and trial. Data collection techniques use observation, interviews, or smart phones for shooting or sound recording. The analysis technique for system forecasting uses the SES method, while the system testing uses a Blackbox. Our findings show that the lowest MAPE value was obtained at 49.8%. The results of testing the system using a Blackbox that all components in this system are already functioning properly. With this system, it can make it easier for related parties to predict the number of measles vaccines in the new Gambir health center.
Sistem Peramalan Permintaan Darah dengan Metode Simple Moving Average Wan Mhd Iqbal Muttaqin; William Ramdhan; Wan Mariatul Kifti
Jurnal Pendidikan Informatika (EDUMATIC) Vol 6, No 2 (2022): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v6i2.6326

Abstract

Simple Moving Average (SMA) is a method used to forecast a state of affairs in the next period. This method is applied to determine the number of blood requests in PMI in the Asahan Regency area. Blood stock is an important factor to support activities in this PMI organization by paying attention to the condition of this month /period and predicting the next period. The purpose of this study is to build a blood demand forecasting system with the SMA method. The model used to build this system is a waterfall with stages of analysis, design, implementation and testing. The data we use for this forecasting is the demand for blood from July 2021 to June 2022. Data analysis used the SMA method to determine the rate of prediction errors in this system, while testing this system used a black box. The results of our products are in the form of a web consisting of the login menu, the main menu, the calculation results. The calculation results using the SMA method in our system are appropriate, and can display the number of blood demand stocks in each period. The results of testing the system using black box show that this system is running properly without any errors, and it is working properly. Therefore, the existence of this system can help pmi to determine the number of requests based on blood type.
Sistem Penentuan Bonus Karyawan menggunakan Metode Simple Additive Weighting Dwi Putri; William Ramdhan; Masitah Handayani
Jurnal Pendidikan Informatika (EDUMATIC) Vol 6, No 2 (2022): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v6i2.6375

Abstract

The Simple Additive Weighting (SAW) method is one of the methods in determining decisions based on predetermined criteria, such as employee annual bonuses.  However, there are no criteria and systems used to determine who employees are eligible for the yearly bonus based on their purpose The purpose of this study is to create a system of supporting employee annual bonus decisions by applying the SAW method. The waterfall is a model used to build this system through analysis, design, implementation, and testing.  Data collection used observations and interviews, as well as data used by 20 people.  The data analysis technique uses the SAW method by looking at alternatives and rankings of the results obtained.  Testing this system uses a black box by looking at the processes and functions of several components in this system.  These findings result in a system that can provide a decision to determine annual bonuses for employees using the SAW method addition, has been successfully implemented with this method.  In addition, this system also has all its components already functioning, both from the login process to being able to produce feasible decisions and not determining the bonus.
Analytical Hierarchy Process: a method for Determining the Assessment of Soft Skill Competence Rizwan Sai; William Ramdhan; Masitah Handayani
Jurnal Pendidikan Informatika (EDUMATIC) Vol 6, No 2 (2022): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v6i2.6371

Abstract

Analytical Hierarchy Process (AHP) is a method that is often used to determine decisions in system making. To determine the soft-skill competence possessed by a person, a more in-depth analysis needs to be carried out based upon the criteria used. The purpose of this study is to produce a decision support system to assess the soft-skill competence of employees using the AHP method. This system is made based on the stages of the waterfall model which consists of analysis, design, implementation and testing. The collection technique used observation and interviews, and the amount of data was 18 people who were analyzed using the AHP method. System testing is done with a black box which aims to see the functionality to the system. Our findings are in the form of a web-based decision support system. In addition, this system managed to show the best employee with a score of 0.622, and all components run as expected, without any errors. So that this system can be used as a reference to determine the soft skill competencies of employees in this place.
Aplikasi Pendukung Keputusan dalam Mengukur Tingkat Kepuasan Pelayanan Publik menggunakan Metode MFEP Pritty Noviana Sari; William Ramdhan; Abdul Karim Syahputra
Jurnal Pendidikan Informatika (EDUMATIC) Vol 7 No 1 (2023): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v7i1.12448

Abstract

Services that are said to be excellent are services provided by public service providers, namely the government in an effort to meet the needs of people who receive services and are carried out in accordance with the law. The low quality of services provided to the community certainly has an impact on decreasing public trust in the government. The purpose of this study is to build a decision support system using the Multi Factor Evaluation Process (MFEP) method to measure the level of public service satisfaction in the range sub-district area. In building this system, we apply the waterfall model with stages of analysis, design, implementation, and testing. Analysis is carried out to collect the needs in building this system and analysis using the MFEP method. The criteria used to measure service satisfaction are five criteria, namely certainty of time, comfort, loyalty, responsibility, and task completion. The design of the system we built, consists of use case diagrams and flowcharts. At the implementation stage, a system is made using the web-based MFEP method. Meanwhile, testing on this system uses a black-box to see the functionality of the product. Our findings are in the form of a system that can provide decisions to determine the level of public satisfaction. The results of the analysis showed that the service section was selected as an assessment of the level of public satisfaction with a value of 3,766. In addition, the results of black-box testing show that this system is functioning properly without any errors.