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Journal : Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara)

PENGGUNAAN METODE LINEAR REGRESSION UNTUK PREDIKSI PENJUALAN SMARTPHONE Tri Indarwati; Tri Irawati; Elistya Rimawati
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 6, No 2 (2018): Jurnal TIKomSiN
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2863.777 KB) | DOI: 10.30646/tikomsin.v6i2.369

Abstract

Planning and analyzing market needs precisely and efficiently if managed optimally is needed to achieve company success. In practice, existing transaction data used as a reference in planning and analyzing market needs. This company needs a tool to predict future sales. This information is needed because a good sales prediction will help understand what items must be distributed according to market needs so that companies can reduce uncertainty in decision making. The purpose of this study is to create an information system can do smartphone sales forecasting at 82 Cell Mayang with the Linear Regression method. The sales forecasting system is using the Linear Regression method, The goal to create a sales forecasting system by determining the sales volume with a certain period by looking at the cost of advertising and the number of sales. The research method used includes observation, interviews and literature studies. Designing using DAD includes entity relation diagrams, context diagrams, the hierarchy of input process output and data flow diagrams. The programming language used is Visual Basic.Net and the sql server 2008 database. Features in the sales forecasting application include processing data items, customer data, incoming product data, sales data, and forecasting data. The test results show the MAPE value is 0.032 and the MSE value is 5.16. From this value, it can be said that the prediction of smartphone sales with the Linear Regression method on 82 Cell Mayang is categorized as very good. Whereas for the blackbox testing that has been carried out, it shows that the smartphone sales forecasting system in 82 Cell Mayang, Sukoharjo has been going well.Keywords: forecasting, sales prediction, incoming product data, linear regression, visual basic
Prediksi Penjualan Kertas Menggunakan Metode Double Exponential Smoothing Erinsyah Aditya Nugroho Putro; Elistya Rimawati; Retno Tri Vulandari
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 9, No 1 (2021): Jurnal TIKomSiN, Vol.9, No. 1, 2021
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v9i1.548

Abstract

One of the important thing in business is the inventory of goods and services. Business goal can be reached when business owner know how the number of their inventory. Printing business is using forecasting model in their purchasing raw materials to estimate and calculate their selling prediction. That model is used to minimize economic losses when the costumer canceled order because paper was ran out and to prevent paper damage does not occur date to storage that to long. Double Exponential Smoothing method is used in this research to predict the sales of Paper A and HVS A3+ paper and calculates the prediction error with MAPE (Mean Absolute Percentage Error). This study aims to make an accurate forecasting application. The prediction results from application are in the form of prediction calculations for sales in the following month which will be used to optimize the purchase of paper to be sold. In applying the research results of Paper A and HVS A3 +, the best alpha was obtained in the 12th period, namely 0.3 and 0.6 with a MAPE error of 12% and 18% and an accuracy rate of 88% and 82% where the alpha was used to predict period 13 and produces a forecast value of 446 for Paper A and 474 for HVS A3 +
EVALUASI PENERAPAN SISTEM INFORMASI MANAJEMEN RUMAH SAKIT (SIMRS) DI RUMAH SAKIT “X” MENGGUNAKAN METODE END USER COMPUTING SATISFACTION (EUCS) Nurul C, Aulia Riezky; Rimawati, Elistya
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 12, No 2 (2024): Jurnal TIKomSiN Vol 12, No. 2 Oktober 2024
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v12i2.888

Abstract

During the implementation of SIMRS there are still some problems that occur such as incomplete features, there are still errors in the features accessed and still desktop-based. Therefore, researchers evaluate the Hospital Management Information System (SIMRS) based on user satisfaction and provide results in the form of recommendations for developing SIMRS. This research uses the End User Computing Satisfaction (EUCS) method which consists of 5 dimensions, namely Content, Accuracy, Display, User-Friendliness, and Timeliness. The data collection method is observation, interview, and distributing questionnaires to 125 SIMRS user employees using systematic random sampling techniques, the data is processed using SPSS version 23. The results showed that the level of satisfaction of “X” SIMRS users was 76.4%, which means that users are satisfied in using SIMRS and provide recommendations for improvements to SIMRS so that it can run well and user satisfaction continues to increase.
PERAMALAN HARGA TELUR AYAM DENGAN METODE EXPONENSIAL SMOOTHING WINTERS DI KABUPATEN SUKOHARJO Nugraheni, Ria Pertiwi; Rimawati, Elistya; Vulandari, Retno Tri
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 13, No 1 (2025): Jurnal Tikomsin
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v13i1.951

Abstract

Forecasting is the process of estimating future price trends based on historical price data. The price of rice and eggs in Sukoharjo Regency, based on data from Dinas Perdagangan, Koperasi, dan UMKM Sukoharjo from January 2016 to August 2019, has shown frequent fluctuations. To address this issue, an accurate forecasting method is needed to help predict future prices of rice and eggs, minimize price volatility, and assist in decision-making for both consumers and stakeholders. This study applies the Exponential Smoothing Winters method, a seasonal forecasting technique that incorporates level, trend, and seasonal components. A price prediction application was developed using the VB.NET programming language and SQL Server database. The application generates predictive calculations for rice and egg prices, complemented by graphical displays and report outputs. The results of the study show Mean Absolute Percentage Error (MAPE) values of 14.57% for broiler eggs and 6.74% for native chicken eggs. These results indicate that the method provides a relatively high level of accuracy.