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All Journal IPTEK The Journal of Engineering
Albertus Eka Putra Haryanto
Institut Teknologi Sepuluh Nopember
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Engineering Mechanical Engineering

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Dashboard Pre-Processing Data (DPD) as Data Analysis System with Technological Innovation to Perform Pre-Processing Quantitative Data Mashuri Mashuri; Albertus Eka Putra Haryanto; Yola Argatha Manik; Dinar Sukma Dewi; Tegar Primadana Putra
IPTEK The Journal of Engineering Vol 9, No 1 (2023)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j23378557.v9i1.a13050

Abstract

In essence, data in real-life always needs to be pre-processed or better known as pre-processing data. Pre-processing Data is one of the early techniques for converting raw data from various sources into cleaner information that can be used for further analysis. There are three types of pre-processing data, missing values, checking outlier data, and identifying the types of distribution in the data. Currently, statistical software that offers to be used in pre-processing data analysis has been widely and is quite familiar. However, the user is often can not run the analysis quickly. Therefore, there is the idea to create and develop an application or dashboard that can be used to solve these problems. The application this at is offered and trying to be developed is called "DPD (Dashboard Pre-Processing Data)". This application serves as a tool to pre-process data quickly and efficiently. In addition, with this application, it’s expected that users can identify missing values, data outliers, and some types of data distribution, so users can determine the analysis method that will be used on the research data they have.
Forecasting the Consumer Confidence Index for Economic Conditions Prediction in Ambon, Indonesia Albertus Eka Putra Haryanto; Destri Susilaningrum; Indra Nur Fauzi
IPTEK The Journal of Engineering Vol 9, No 2 (2023)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j23378557.v9i2.a16132

Abstract

Economic developments in Maluku Province show positive growth. However, this is not accompanied by an increase in the confidence index from consumers. It was recorded that from July to September 2022, there was a decrease in the Consumer Confidence Index of around 7.6% to 8.2%. The value of the Consumer Confidence Index can be forecasted using time series analysis. Time series analysis is a method intended to make an estimation and forecasting for the future. Some methods that can be used in forecasting in this study are naive, moving average, single exponential smoothing, double exponential smoothing, and time series regression. This method can be used to forecast the value of the Consumer Confidence Index in Ambon City after the Covid-19 pandemic. It can be concluded from the analysis results that the best model for forecasting the condition of the consumer confidence index value is the Double Exponential Smoothing method with a combination of Alpha = 0,4 and Gamma = 0,5, The forecast results showed a decrease in the value of the consumer confidence index, although the index still showed a relatively optimistic value.
Co-Authors Destri Susilaningrum Dinar Sukma Dewi Indra Nur Fauzi Mashuri Mashuri Tegar Primadana Putra Yola Argatha Manik