Jurnal Tirtayasa Ekonomika (Tirtayasa Economica Journal)
Tirtayasa Ekonomika Journal |ISSN: 2540-931X (Online)| is published by Faculty of Economics and Business, University Sultan Ageng Tirtayasa. Tirtayasa Ekonomika Journal provides a forum for publishing the original research articles, review articles from contributors, and the novel technology news related to economics and business research. This journal encompasses original research articles, review articles, and short communications, including: (1) Accounting; (2) Business; (3) Economics (general), and (4) Islamic economics.
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"Vol 16, No 2 (2021)"
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<![CDATA[Pengaruh Pertumbuhan Aset dan Struktur Modal terhadap Profitabilitas Perusahaan Sub Sektor Telekomunikasi di BEI ]]>
<![CDATA[Yunika Priscilla]]>;
<![CDATA[Anwar Ramli]]>;
<![CDATA[Anwar Anwar]]>
<![CDATA[ Tirtayasa Ekonomika Vol 16, No 2 (2021) ]]>
Publisher : <![CDATA[FEB Universitas Sultan Ageng Tirtayasa ]]>
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DOI: 10.35448/jte.v16i2.12050
<![CDATA[Penelitian ini bertujuan untuk mengetahui pengaruh pertumbuhan aset dan struktur modal (DER) terhadap profitabilitas (ROE) dengan menggunakan variabel kontrol ukuran perusahaan. Populasi dalam penelitian ini yaitu seluruh perusahaan yang ada di sub sektor telekomunikasi, sedangkan sampel yang digunakan adalah 5 perusahaan sub sektor telekomunikasi dengan periode pengamatan 2008-2019, dimana pengambilan sampelnya menggunakan teknik purposive sampling. Pengumpulan data menggunakan teknik dokumentasi dan analisis data menggunakan regresi linear berganda.Penelitian ini memperoleh hasil bahwa adanya pengaruh positif dan signifikan antara variabel pertumbuhan aset terhadap profitabilitas (ROE), hal ini berarti semakin tinggi persentase pertumbuhan aset maka semakin bertambah pula kemampuan perusahaan untuk menghasilkan laba (profit) serta menunjukkan bahwa pertumbuhan aset yang meningkat akan diikuti pula dengan meningkatnya profitabilitas perusahaan dalam hal ini laba bersih yang menjadi hak pemegang saham perusahaan (ROE).Struktur modal (DER) berpengaruh negatif dan signifikan tehadap profitabilitas (ROE), arah yang negatif ini berarti semakin besar nilai DER yang dimiliki perusahaan yang diidentifikasikan dengan nilai total utang yang besar maka akan memperkecil nilai profitabilitas (ROE) yang diperoleh perusahaan. Dan secara bersama-sama (simultan) pertumbuhan aset dan DER berpengaruh signifikan terhadap profitabilitas (ROE), dimana pertumbuhan aset menggambarkan pertumbuhan aktiva perusahaan yang akan mempengaruhi profitabilitas perusahaan sedangkan struktur modal (DER) digunakan perusahaan agar mampu memaksimumkan profitabilitas dan nilai suatu perusahaan. <img 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]]>
<![CDATA[Pengaruh Green Marketing dan Pengetahuan terhadap Keputusan Pembelian Kopi Starbucks di Pulau Jawa ]]>
<![CDATA[Rosyhana Damastuti]]>;
<![CDATA[Nuning Setyowati]]>;
<![CDATA[Isti Khomah]]>
<![CDATA[ Tirtayasa Ekonomika Vol 16, No 2 (2021) ]]>
Publisher : <![CDATA[FEB Universitas Sultan Ageng Tirtayasa ]]>
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DOI: 10.35448/jte.v16i2.11714
<![CDATA[Green marketing berkaitan dengan dalam pemasaran produknya mempertimbangkan masalah lingkungan yang ada. Salah satu caranya dengan menggunakan tumbler atau reusable cup dalam pembelian kopi Starbucks. Hal tersebut merupakan salah satu cara untuk mengurangi penggunaan kemasan plastik sekali pakai yang dapat menyebabkan peningkatan jumlah sampah yang dikhawatirkan dapat menganggu lingkungan. Variabel green marketing dengan pengetahuan digunakan untuk mengetahui keputusan pembelian, pengetahuan ini berkaitan dengan pengetahuan konsumen mengenai segala informasi produk tersebut. Data pada penelitian ini diolah dengan menggunakan analisis regresi linier berganda dengan menggunakan aplikasi SPSS. Hasil penelitian menunjukkan bahwa terdapat pengaruh secara bersama-sama kesadaran lingkungan, fitur produk hijau, harga produk hijau, promosi produk hijau, dan pengetahuan terhadap keputusan pembelian kopi Starbucks di Pulau Jawa. Sedangkan secara sendiri-sendiri terdapat pengaruh secara signifikan antara kesadaran lingkungan, fitur produk hijau, harga produk hijau, promosi produk hijau, dan pengetahuan terhadap keputusan pembelian kopi Starbucks di Pulau Jawa.]]>
<![CDATA[Dampak Pandemi Covid - 19 Terhadap Harga Saham Pada Sub Sektor Telekomunikasi Yang Terdaftar Di BEI ]]>
<![CDATA[Dyah Atika Mahanani]]>;
<![CDATA[Ida Aryati D P W]]>;
<![CDATA[Ratna Damayanti]]>
<![CDATA[ Tirtayasa Ekonomika Vol 16, No 2 (2021) ]]>
Publisher : <![CDATA[FEB Universitas Sultan Ageng Tirtayasa ]]>
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DOI: 10.35448/jte.v16i2.10547
<![CDATA[ABSTRACTPurpose of this research is to find out how big the difference stock prices in Telecommunications Sub-Sector before and after statement of Covid-19 Pandemic in Indonesia. Population in this study was taken from 6 companies in Telecommunications Sub-Sector listed on Indonesia Stock Exchange. Sampling technique in this study using purposive sampling technique, resulting in number of samples that meet criteria of this study in form of 4 telecommunications companies including PT. Telkom Indonesia (Persero), Tbk, PT. XL Axiata, Tbk, PT. Smartfren Telecom, Tbk, and PT. Indosat, Tbk. Secondary data source of share prices from companies in Telecommunication Sub-Sector obtained through official website of Indonesia Stock Exchange (IDX) (www.idx.co.id) in form of closing price data from before and after Covid-19 pandemic in Indonesia. Results show that there is a significant difference between stock prices before and after Covid-19 pandemic in Indonesia.]]>
<![CDATA[Audit Quality and Auditor Switching in LQ45 Index Listed Firms of the Indonesia Stock Exchange ]]>
<![CDATA[Chandra Prasadhita]]>
<![CDATA[ Tirtayasa Ekonomika Vol 16, No 2 (2021) ]]>
Publisher : <![CDATA[FEB Universitas Sultan Ageng Tirtayasa ]]>
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DOI: 10.35448/jte.v16i2.12984
<![CDATA[Auditor switching is important to maintain audit quality. This study aims to find empirical evidence regarding the effect of auditor switching on the audit quality of companies listed on the LQ45 index of the Indonesia Stock Exchange. Switching Public Accounting Firm and switching audit partner is the dependent variable in this study. Audit quality as the dependent variable is measured by the value of discretionary accruals. The saturated sampling method was used with the entire population of companies listed on the LQ45 index of the Indonesia Stock Exchange with a total of 45 companies in 2019 - 2020. Multiple regression analysis techniques were used. The results of the study stated that Public Accounting Firm switching and audit partners switching does not affect audit quality.Keywords : Public Accounting Firm Switching, Audit Partners Switching, Audit Quality.]]>
<![CDATA[Anteseden Repurchase Intention Aplikasi Shopee Dengan Kepuasan Sebagai Variabel Mediasi Di Kabupaten Banyumas ]]>
<![CDATA[Reza Rahmadi Hasibuan]]>;
<![CDATA[Agustin Riyan Pratiwi]]>
<![CDATA[ Tirtayasa Ekonomika Vol 16, No 2 (2021) ]]>
Publisher : <![CDATA[FEB Universitas Sultan Ageng Tirtayasa ]]>
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DOI: 10.35448/jte.v16i2.10514
<![CDATA[Kepuasan konsumen merupakan faktor yang sangat penting dalam membentuk perilaku pembelian ulang pada pembelanjaan online. Shopee memegang posisi pertama sebagai top e-commerce selama sepuluh periode secara berkelanjutan yang dihasilkan dari peringkat pada AppStore. Pada periode II 2019, aplikasi Shopee menjadi peringkat teratas pada AppStore. Tetapi dilihat pada jumlah rata-rata konsumen pada aplikasi setiap bulannya, Tokopedia memimpin peringkat teratas dibandingkan Shopee. Penelitian ini memiliki tujuan untuk mengetahui tingkat repurchase intention di aplikasi Shopee. Teknik pengambilan sampel dengan menggunakan random sampling dengan jumlah sampel sebanyak 100 responden dan menggunakan analisis data Structural Equation Modeling (SEM). Secara spesifik penelitian ini dapat disimpulkan bahwa diskon tidak berpengaruh terhadap kepuasan, diskon tidak berpengaruh terhadap repurchase, kemudahan berpengaruh terhadap kepuasan, kemudahan tidak berpengaruh terhadap repurchase, kepuasan berpengaruh terhadap repurchase. Kata Kunci: Shoppe, repurchase intention dan SEM.]]>
<![CDATA[Upaya Peningkatan Omzet Umkm Pada Masa Pasca Pandemi Covid-19 Melalui Kinerja Akuntan Dan Motivasi Usaha Di Kabupaten Banyumas ]]>
<![CDATA[Aning Fitriana]]>;
<![CDATA[Adhelia Desi Prawestri]]>
<![CDATA[ Tirtayasa Ekonomika Vol 16, No 2 (2021) ]]>
Publisher : <![CDATA[FEB Universitas Sultan Ageng Tirtayasa ]]>
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DOI: 10.35448/jte.v16i2.11329
<![CDATA[The purpose of this study was to analyze the performance of accountants and business motivation to increase turnover at MSMEs in Banyumas Regency. This study uses multiple linear regression analysis and SEM (Structural Equation Modeling). The results obtained indicate that the accountant's performance has a significant and positive effect on increasing turnover. Business motivation has a significant and positive influence on the increase in turnover and accountant performance as well as business motivation jointly influences the increase in turnover. ]]>
<![CDATA[Keputusan Pembelian Berdasarkan Desain Dan Kustomisasi Pada Produk Masker (Studi Pada Generasi Milenial Di Masa Pandemik) ]]>
<![CDATA[Hilmi, Luqman Dzul]]>
<![CDATA[ Tirtayasa Ekonomika Vol 16, No 2 (2021) ]]>
Publisher : <![CDATA[FEB Universitas Sultan Ageng Tirtayasa ]]>
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DOI: 10.35448/jte.v16i2.10470
<![CDATA[Must to use masks during this pandemic directly benefits the mask business in the form of increased mask sales. This condition requires business people to offer masks in addition to functioning as personal protective equipment, they also consider product design and product custom. The goal is to strengthen customers in the decision to buy masks that in addition to their needs, also their interests. In addition, advances in internet technology have made its use increasing. The increase is from the aspect of usage intensity to the level of browsing to internet-based media. The existence of the internet actually makes customers, especially the millennial generation, have more and more information in making purchase decisions, namely for mask products. Therefore, in this study using a quantitative approach with multiple regression analysis. Sampling of 129 millennial generation respondents used the accidental sampling method, namely accidental sampling of prospective respondents met, so that consideration of the suitability of the requirements must be fulfilled. Based on the results of data analysis, it was found that: 1) product design has a positive and significant effect on purchasing decisions; 2) product custom has a positive and significant effect on purchasing decisions; and 3) product design and custom have a positive and significant effect on purchasing decisions.]]>
<![CDATA[Kompentensi Tenaga Penjual, Kualitas Pelayanan, Penanganan Komplain, Dan Citra Perusahaan Terhadap Loyalitas Nasabah Asuransi ]]>
<![CDATA[Herwi Yanto]]>;
<![CDATA[Kartika Hendra TS]]>;
<![CDATA[Supawi Pamenang]]>
<![CDATA[ Tirtayasa Ekonomika Vol 16, No 2 (2021) ]]>
Publisher : <![CDATA[FEB Universitas Sultan Ageng Tirtayasa ]]>
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DOI: 10.35448/jte.v16i2.10383
<![CDATA[Tujuan penelitian tentang Kompentensi tenaga penjual, kualitas pelayanan, penanganan komplain dan citra perusahaan terhadap loyalitas nasabah pada BUMIDA di wilayah DIY-JATENG. Penelitian dilakukan dengan menggunakan data primer sebanyak 200 responden yang digunakan. Teknik yang digunakan purposive sampling. Adapun pengumpulan data menggunakan kuesiner dengan skla linkert. Pengujian dengan menggunakan analisa regresi linear berganda dan dilakukan uji asumsi klasik serta ujia kualitas data. Adapun hasil penelitian menyimpulkan bahwa kualitas pelayanan dan citra pelanggan berpengaruh positif terhadap loyalitas nasabah, penanganan complain berpengaruh negative terhadap loyalitas nasabah, sedangkan kompetensi tenaga penjual tidak berpengaruh terhadap loyalitas nasabah pada asuransi BUMIDA. Secara simultan kopentensi tenaga penjual, kualitas pelayanan, penanganan komplain dan citraperusahaan berpengaruh terhadap loyalitas nasabah dimana F hitung > F tabel sebesar 149,194 (149,194 > 2,42). Adapun nilai determinasi (R2) sebesar 75,4%. Kata kunci : kopentensi tenaga penjual, kualitas pelayanan, penanganan complain, citra perusahaan]]>
<![CDATA[Minat Beli Konsumen Terhadap Sayuran Organik Pada Pasar Tradisional Ditinjau Dari Persepsi Harga Dan Sikap Konsumen (Studi Pada Pasar Sambas Medan) ]]>
<![CDATA[Cut Ermiati]]>;
<![CDATA[Dita Amanah]]>;
<![CDATA[Selly Utami]]>;
<![CDATA[Dedy Ansari Harahap]]>
<![CDATA[ Tirtayasa Ekonomika Vol 16, No 2 (2021) ]]>
Publisher : <![CDATA[FEB Universitas Sultan Ageng Tirtayasa ]]>
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DOI: 10.35448/jte.v16i2.10324
<![CDATA[Penelitian ini bertujuan untuk menganalisis persepsi harga dan sikap konsumen terhadap minat konsumen membeli sayuran organik. Sampel penelitian ini adalah konsumen Pasar Sambas Medan yang membeli sayuran organik dengan jumlah 100 responden yang dipilih dengan teknik sampel bertujuan (purposive sampling). Teknik pengumpulan data menggunakan angket dengan analisis regresi linier berganda sebagai teknik analisis data. SPSS 22.00 digunakan sebagai alat bantu pengolahan data. Hasil penelitian menunjukkan bahwa persepsi harga dan sikap konsumen secara parsial dan simultan memiliki pengaruh positif terhadap minat beli konsumen sayuran organik. Hasil R square sebesar 0,217 menunjukkan arti bahwa 21,7% minat beli konsumen dijelaskan oleh persepsi konsumen terhadap harga dan sikapnya. Sisanya 7,3% dijelaskan oleh variabel lain di luar penelitian ini. Beberapa keterbatasan dan saran untuk penelitian selanjutnya dibahas dalam artikel ini.]]>
<![CDATA[Determinan Stabilitas Sistem Keuangan Di Indonesia Melalui Pendekatan Makroekonomi ]]>
<![CDATA[Fristi Wiku]]>;
<![CDATA[Fitri Juniwati Ayuningtyas]]>
<![CDATA[ Tirtayasa Ekonomika Vol 16, No 2 (2021) ]]>
Publisher : <![CDATA[FEB Universitas Sultan Ageng Tirtayasa ]]>
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DOI: 10.35448/jte.v16i2.12409
<![CDATA[The condition of financial stability system during the crisis and after the crisis is a benchmark for the financial system in Indonesia, so efforts are needed to avoid or reduce the risk of financial instability system. This situation had an impact on the transmission of monetary policy which could not run effectively and resulted in huge losses for the cost of crisis recovery in a long time. The data analysis method used was the Error Correction Model (ECM). The results showed that in the short term JUB, BI rate, SBI and IHSG had a significant effect on financial stability system, while inflation had no effect on financial stability system. The estimation of the research model in the long term for inflation variables, JUB/M2, BI rate, SBI and IHSG has a significant influence on financial stability system. ]]>
