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Forecasting Stock Price PT. Telkom Using Hybrid Time Series Regression Linear– Autoregressive Integrated Moving Average Model

Jurnal Matematika, Statistika dan Komputasi · Vol. 18 No. 2 (2022) · pp. 293–307

DOI
10.20956/j.v18i2.18837
ISSN
2614-8811, 1858-1382
Published
2022-01-01
Publisher
Department of Mathematics, Hasanuddin University
Language
en
License
creativecommons.org/licenses/by/4.0

Abstract

English

The hybrid method is a method of combining two forecasting models. Hybrid method is used to improve forecasting accuracy. In this study, the Time Series Regression (TSR) linear model will be combined with the Autoregressive Integrated Moving Average (ARIMA) model. The TSR linear model is used to obtain the model and residual value, then the residual value of the TSR linear model will be modeled by the ARIMA model. This combination method will produce a hybrid TSR linear-ARIMA model. The case study in this research is stock closing price (daily) of PT. Telkom Indonesia Tbk. The stock closing price (daily) of PT. Telkom Indonesia Tbk in 2020 showed an decreasing and increasing trend pattern. The results of this study obtained the best model of hybrid TSR linear-ARIMA (2,1,1) with the proportion of data training and testing is 70:30. In the best model, the MAD value is 56.595, the MAPE value is 1.880%, and the RMSE value is 78.663. It is also found that the hybrid TSR linear-ARIMA model has a smaller error value than the TSR linear model. The results of forecasting the stock price of PT. Telkom Indonesia Tbk for the period 02 January 2021 to 29 January 2021 formed a decreasing trend pattern.

Bahasa Indonesia

Metode hybrid merupakan metode penggabungan dua model peramalan. Metode hybrid digunakana untuk meningkatkan akurasi peramalan.Pada penelitian ini, model Time Series Regression (TSR) linier akan digabungkan dengan model Autoregressive Integrated Moving Average (ARIMA). Model TSR linier digunakan untuk memperoleh model dan nilai residual, kemudian nilai residual dari model TSR linier akan dimodelkan oleh model ARIMA. Metode penggabungan ini akan menghasilkan model hybrid TSR linier-ARIMA. Studi kasus dalam penelitian ini adalah harga penutupan saham (harian) PT. Telkom Indonesia Tbk. Harga penutupan saham (harian) PT. Telkom Indonesia Tbk pada tahun 2020 menunjukkan pola trend turun dan trend naik. Hasil penelitian ini, diperoleh model terbaik hybrid TSR linier-ARIMA (2,1,1) dengan proporsi data in sample dan out sample adalah 70:30. Pada model terbaik, diperoleh nilai MAD sebesar 56,595, nilai MAPE sebesar 1,880%, dan nilai RMSE sebesar 78,663. Diperoleh juga bahwa model hybrid TSR linier-ARIMA memiliki nilai kesalahan yang lebih kecil dibandingkan dengan model TSR linier. Hasil peramalan harga saham PT. Telkom Indonesia Tbk periode 02 Januari 2021 sampai dengan 29 Januari 2021 membentuk pola trend turun.

Keywords

Collaboration network of the authors

40 authors · 93 co-authorship links

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  • Monash University
  • Affiliation unknown
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Co-authorOrganisationJoint articles
Endang NurcahyaniAffiliation unknown6
Bambang IrawanMonash University4
Meiliyani SiringoringoAffiliation unknown3
Sumardi SumardiAffiliation unknown2
YuliantyAffiliation unknown2
Rito GoejantoroAffiliation unknown2
Asrul SaniAffiliation unknown1
Muhammad SudiaAffiliation unknown1
Rochmah AgustrinaAffiliation unknown1
Herta M. ManullangAffiliation unknown1
Darnah DarnahAffiliation unknown1
Selsi SelsiAffiliation unknown1
Risma RasmaniAffiliation unknown1
Tundjung Tripeni HandayaniAffiliation unknown1
Resta TaniaAffiliation unknown1
Wanda AmeliaAffiliation unknown1
vega abresaAffiliation unknown1
Endang Nurcahyani2Affiliation unknown1
Lili ChrisnawatiAffiliation unknown1
Nurshella AphertaAffiliation unknown1
Resya Tamara AgustinAffiliation unknown1
Lutfiah YuniarAffiliation unknown1
Rezza Kusumma DewiyatnoAffiliation unknown1
Kharisma Purnama AgustinAffiliation unknown1
Reni PratiwiAffiliation unknown1
Surya PranggaAffiliation unknown1
Putri Sri AstutiAffiliation unknown1
Sifriyani SifriyaniAffiliation unknown1
Yunda Sasha ParadillaAffiliation unknown1
Melisa ArumsariAffiliation unknown1
Nur Annisa FitriAffiliation unknown1
Novita AndrianiAffiliation unknown1
Adelia RamadhaniAffiliation unknown1
Suyitno SuyitnoAffiliation unknown1
Ineu SintiaAffiliation unknown1
M. FathurahmanAffiliation unknown1
Yusrian PalilingAffiliation unknown1

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/jmsk/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">Forecasting Stock Price PT. Telkom Using Hybrid Time Series Regression Linear– Autoregressive Integrated Moving Average Model</dc:title>
	<dc:creator xml:lang="en">Ramadani, Kartika </dc:creator>
	<dc:creator xml:lang="en">Wahyuningsih, Sri </dc:creator>
	<dc:creator xml:lang="en">Hayati, Memi Nor </dc:creator>
	<dc:subject xml:lang="en">Harga saham</dc:subject>
	<dc:subject xml:lang="en">hybrid TSR linier-ARIMA</dc:subject>
	<dc:subject xml:lang="en">peramalan</dc:subject>
	<dc:subject xml:lang="en">trend</dc:subject>
	<dc:description xml:lang="en">The hybrid method is a method of combining two forecasting models. Hybrid method is used to improve forecasting accuracy. In this study, the Time Series Regression (TSR) linear model will be combined with the Autoregressive Integrated Moving Average (ARIMA) model. The TSR linear model is used to obtain the model and residual value, then the residual value of the TSR linear model will be modeled by the ARIMA model. This combination method will produce a hybrid TSR linear-ARIMA model. The case study in this research is stock closing price (daily) of PT. Telkom Indonesia Tbk. The stock closing price (daily) of PT. Telkom Indonesia Tbk in 2020 showed an decreasing and increasing trend pattern. The results of this study obtained the best model of hybrid TSR linear-ARIMA (2,1,1) with the proportion of data training and testing is 70:30. In the best model, the MAD value is 56.595, the MAPE value is 1.880%, and the RMSE value is 78.663. It is also found that the hybrid TSR linear-ARIMA model has a smaller error value than the TSR linear model. The results of forecasting the stock price of PT. Telkom Indonesia Tbk for the period 02 January 2021 to 29 January 2021 formed a decreasing trend pattern.</dc:description>
	<dc:description xml:lang="id">Metode hybrid merupakan metode penggabungan dua model peramalan. Metode hybrid digunakana untuk meningkatkan akurasi peramalan.Pada penelitian ini, model Time Series Regression (TSR) linier akan digabungkan dengan model Autoregressive Integrated Moving Average (ARIMA). Model TSR linier digunakan untuk memperoleh model dan nilai residual, kemudian nilai residual dari model TSR linier akan dimodelkan oleh model ARIMA. Metode penggabungan ini akan menghasilkan model hybrid TSR linier-ARIMA. Studi kasus dalam penelitian ini adalah harga penutupan saham (harian) PT. Telkom Indonesia Tbk. Harga penutupan saham (harian) PT. Telkom Indonesia Tbk pada tahun 2020 menunjukkan pola trend turun dan trend naik. Hasil penelitian ini, diperoleh model terbaik hybrid TSR linier-ARIMA (2,1,1) dengan proporsi data in sample dan out sample adalah 70:30. Pada model terbaik, diperoleh nilai MAD sebesar 56,595, nilai MAPE sebesar 1,880%, dan nilai RMSE sebesar 78,663. Diperoleh juga bahwa model hybrid TSR linier-ARIMA memiliki nilai kesalahan yang lebih kecil dibandingkan dengan model TSR linier. Hasil peramalan harga saham PT. Telkom Indonesia Tbk periode 02 Januari 2021 sampai dengan 29 Januari 2021 membentuk pola trend turun.</dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Hasanuddin University</dc:publisher>
	<dc:date>2022-01-01</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/jmsk/article/view/18837</dc:identifier>
	<dc:identifier>10.20956/j.v18i2.18837</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 18 No. 2 (2022): JANUARY 2022; 293-307</dc:source>
	<dc:source>2614-8811</dc:source>
	<dc:source>1858-1382</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/jmsk/article/view/18837/7618</dc:relation>
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	<dc:rights xml:lang="en">Copyright (c) 2021 Author and publisher</dc:rights>
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