Perancangan Aplikasi Peramalan untuk Metode Exponential Smoothing Menggunakan Aplikasi Lazarus (Studi Kasus: Data Konsumsi Listrik Kota Samarinda)

Septiyanor, Hairi; Syaripuddin, Syaripuddin; Goejantoro, Rito

doi:10.20956/ejsa.v2i2.13364

Jurnal

Perancangan Aplikasi Peramalan untuk Metode Exponential Smoothing Menggunakan Aplikasi Lazarus (Studi Kasus: Data Konsumsi Listrik Kota Samarinda)

ESTIMASI: Journal of Statistics and Its Application · Vol. 2 No. 2 (2021) · pp. 57–70

DOI: 10.20956/ejsa.v2i2.13364
ISSN: 2721-379X, 2721-3803
Published: 2021-07-23
Publisher: Hasanuddin University
Language: en

Abstract

Exponential smoothing is forecasting method used to predict the future. Lazarus is an open source software based on free pascal compiler. at this research, program Lazarus be design used exponential smoothing method to predict electricity consumption data in Samarinda City from September to November 2018. Purposed of this researched is to determine the procedure of building an exponential smoothing forecasting application and obtained forecasting result using the built application. Procedure of built the application are designed interface, designed properties and filled coding. The optimum smoothing parameters were obtained used the golden section method. Based on the analysis, electricity consumption data in Samarinda City shows a trend pattern, then the forecasting was used double exponential smoohting (DES) method are DES Brown and DES Holt. The best forecasting method for at this researched is DES Holt, because DES Holt method produced MAPE 0,0659% less than DES Brown method produced MAPE 0,0843%.

Keywords

Collaboration network of the authors

15 authors · 27 co-authorship links

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Co-author	Organisation	Joint articles
Memi Nor Hayati	Affiliation unknown	2
Fidia Deny Tisna Amijaya	Affiliation unknown	2
Putri Sri Astuti	Affiliation unknown	1
Wasono Wasono	Affiliation unknown	1
Shanaz Tulzahrah	Affiliation unknown	1
Rara Suciati	Affiliation unknown	1
Nur Annisa Fitri	Affiliation unknown	1
Dwi Indra Yunistya	Affiliation unknown	1
Baso Indar	Affiliation unknown	1
Moh. Nurul Huda	Affiliation unknown	1
M. Fathurahman	Affiliation unknown	1
Ardiman Wiranata	Affiliation unknown	1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/ESTIMASI/oai, first harvested 2 Nov 2026, last seen 2 Nov 2026.

Original metadata (oai_dc)

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	<dc:title xml:lang="en">Perancangan Aplikasi Peramalan untuk Metode Exponential Smoothing Menggunakan Aplikasi Lazarus (Studi Kasus: Data Konsumsi Listrik Kota Samarinda)</dc:title>
	<dc:creator xml:lang="en">Septiyanor, Hairi</dc:creator>
	<dc:creator xml:lang="en">Syaripuddin, Syaripuddin</dc:creator>
	<dc:creator xml:lang="en">Goejantoro, Rito</dc:creator>
	<dc:subject xml:lang="en">Electricity Consumption</dc:subject>
	<dc:subject xml:lang="en">Golden Section</dc:subject>
	<dc:subject xml:lang="en">Lazarus</dc:subject>
	<dc:description xml:lang="en">Exponential smoothing is forecasting method used to predict the future. Lazarus is an open source software based on free pascal compiler. at this research, program Lazarus be design used exponential smoothing method to predict electricity consumption data in Samarinda City from September to November 2018. Purposed of this researched is to determine the procedure of building an exponential smoothing forecasting application and obtained forecasting result using the built application. Procedure of built the application are designed interface, designed properties and filled coding. The optimum smoothing parameters were obtained used the golden section method. Based on the analysis, electricity consumption data in Samarinda City shows a trend pattern, then the forecasting was used double exponential smoohting (DES) method are DES Brown and DES Holt. The best forecasting method for at this researched is DES Holt, because DES Holt method produced MAPE 0,0659% less than DES Brown method produced MAPE 0,0843%.</dc:description>
	<dc:publisher xml:lang="en">Hasanuddin University</dc:publisher>
	<dc:date>2021-07-23</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unhas.ac.id/index.php/ESTIMASI/article/view/13364</dc:identifier>
	<dc:identifier>10.20956/ejsa.v2i2.13364</dc:identifier>
	<dc:source xml:lang="en">ESTIMASI: Journal of Statistics and Its Application; Vol. 2, No. 2, Juli, 2021 : Estimasi; 57-70</dc:source>
	<dc:source>2721-379X</dc:source>
	<dc:source>2721-3803</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/ESTIMASI/article/view/13364/7100</dc:relation>
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