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<![CDATA[SOSIALISASI DIGITAL MARKETING BAGI PELAKU UMKM PRODUK PERTANIAN DI DESA PURWOREJO, SRAGEN ]]>
<![CDATA[Ika Feni Setiyaningrum]]>;
<![CDATA[Sri Walyoto]]>;
<![CDATA[Suryati Suryati]]>;
<![CDATA[Zulfanita Dien Rizqiana]]>
<![CDATA[ Transformatif : Jurnal Pengabdian Masyarakat Vol. 2 No. 2 (2021) ]]>
Publisher : <![CDATA[UIN Raden Mas Said Surakarta ]]>
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DOI: 10.22515/tranformatif.v2i2.3909
<![CDATA[Hadirnya teknologi menjadi keharusan bagi pelaku UMKM saat ini untuk memanfaatkannya agar usaha yang dimiliki semakin berkembang. Keberadaan marketplace dan media sosial dapat dijadikan sebagai sarana untuk melakukan penjualan dan promosi secara online. Akan tetapi, pada kenyataannya masih banyak pelaku UMKM yang belum memanfaatkan karena berbagai faktor, antara lain adalah kurangnya pemahaman masyarakat dalam mengoperasikan teknologi sebagai sarana berjualan maupun adanya ketakutan masyarakat akan adanya kasus penipuan. Masyarakat Desa Purworejo, Sragen termasuk salah satu pelaku UMKM yang memiliki usaha pertanian, berupa Beras “Utama†dan sambel “Mbok Tamaâ€. Namun demikian, masyarakat di daerah tersebut juga belum memanfaatkan teknologi secara maksimal untuk menopang usaha yang mereka miliki. Oleh karena itu, kami memilih masyarakat di wilayah ini untuk melaksanakan program pengabdian masyarakat yang bertajuk digitalisasi marketing untuk membekali pelaku UMKM agar dapat menjalankan usaha mereka lebih optimal.]]>
<![CDATA[Customer Guilt and its Relation to Purchase Intention of Green Products: A Study to University ‘Green’ Activist Students ]]>
<![CDATA[Septin Puji Astuti]]>;
<![CDATA[Yasaroh Dyah Rakhmawati]]>;
<![CDATA[Zulfanita Dien Rizqiana]]>;
<![CDATA[Rizki Kusumawardhani]]>
<![CDATA[ Jurnal Organisasi dan Manajemen Vol. 18 No. 2 (2022) ]]>
Publisher : <![CDATA[LPPM Universitas Terbuka ]]>
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DOI: 10.33830/jom.v18i2.3008.2022
<![CDATA[Purpose – This paper aims to investigate the structural model of customer guilt, perceived customer effectiveness, self-monitoring, and green purchase intention. Methodology – The present study is a survey of university students in four universities in Greater Surakarta. These students are involved in student organisations such as scout and university student hiking club. PLS-SEM is implemented in this study to compute structural relationships among variables. Findings – The result shows that customer guilt and self-monitoring affect green purchase intention. However, this study cannot prove that perceived consumer effectiveness is the mediator of customer guilt and self monitoring to green purchase intention. Originality – This study proposes a model for green purchase intention of specific groups of young people who are more aware of environmental issues.]]>
<![CDATA[Pendekatan Ridge Regression untuk Analisis Kualitas Layanan dan Kepuasan Pelanggan Kereta Api Perkotaan: Studi Commuterline Solo-Yogyakarta ]]>
<![CDATA[Astuti, Septin Puji]]>;
<![CDATA[Falantana, Alvian Anggi]]>;
<![CDATA[Rizqiana, Zulfanita Dien]]>;
<![CDATA[Kusumawardani, Rizky]]>
<![CDATA[ Jurnal Transportasi Multimoda Vol. 21 No. 2 (2023): Desember ]]>
Publisher : <![CDATA[Puslitbang Transportasi Antarmoda-Kementerian Perhubungan Republik Indonesia ]]>
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DOI: 10.25104/mtm.v21i2.2153
<![CDATA[Sekarang ini, kereta api menjadi moda transportasi yang prospective bagi para komuter. Oleh karena itu, jalur komuter dikembangkan di beberapa kota di Indonesia untuk menyediakan kendaraan umum bagi masyarakat. Kereta Rel Listrik (KRL) Solo-Yogyakarta adalah salah satu jalur komuter yang ada di Indonesia. Jalur ini mulai beroperasi sejak tahun 2021. Untuk meningkatkan layanan commuterline, penelitian ini dilakukan untuk mengidentifikasi hubungan antara kepuasan pelanggan dan kualitas layanan. Lima dimensi dari Kualitas Layanan yang diusulkan oleh Parasuraman digunakan dalam penelitian ini. ridge regression diterapkan dalam penelitian untuk mengatasi kolinearitas antarvariabel independennya. Hasilnya menunjukkan bahwa semua variabel kualitas layanan memiliki pengaruh signifikan terhadap kepuasan pelanggan KRL Solo-Yogyakarta. Variabel keberwujudan dan empati adalah dua variabel yang memiliki pengaruh terbesar terhadap kepuasan pelanggan KRL Solo-Yogyakarta yaitu sebesar 0,399 dan 0,326 untuk variabel keberwujudan dan empati.]]>
<![CDATA[Long Short Term Memory For Comparison Between Bank Syariah Indonesia And PT Bank Artos Indonesia Shares ]]>
<![CDATA[Rizqiana, Zulfanita Dien]]>;
<![CDATA[Akhsan, Izzat Muhammad]]>;
<![CDATA[Priyanto, Intan Indrasara]]>;
<![CDATA[Maharani, Aninda Sabila]]>
<![CDATA[ JISA(Jurnal Informatika dan Sains) Vol 7, No 2 (2024): JISA(Jurnal Informatika dan Sains) ]]>
Publisher : <![CDATA[Universitas Trilogi ]]>
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DOI: 10.31326/jisa.v7i2.2131
<![CDATA[The growth of the capital market in Indonesia has increased from year to year. Based on data from the Indonesia Central Securities Corporation (KSEI), there has been an increase in investor growth in the capital market by 2.34%, mutual funds by 2.44%, and shares by 1.34% until August 2024. The demographic of individual investors in the capital market is dominated by Generation Z who are younger than from 30 years as much as 55.07% in August 2024 (KSEI, 2024). Shares are a form of investment that has the potential for large profits but with small risks. One sector that Gen Z is interested in investing in is the financial sector. The aim of this research is to compare the share prices of Bank Syariah Indonesia and Bank PT Ban Artos Indonesia Tbk using a Neural Network with the Long Short Term Memory (LTSM) algorithm. The data used in this research is secondary data on BSI and PT Bank Artos Indonesia Tbk share prices taken from the investing.com website. The data period used is from 01 September 2021 – 01 September 2024. Based on the results of stock price forecasting using a Neural Network with the LTSM algorithm, RMSE value for both models is for BSI 75.0757 and 91.795 for PT. Bank Artos Indonesia Tbk. A comparison of the predicted share prices of PT Bank Arto Indonesia Tbk and BSI shows that BSI's share price performance is superior to that of PT Bank Arto Indonesia Tbk.]]>
<![CDATA[Long Short Term Memory For Comparison Between Bank Syariah Indonesia And PT Bank Artos Indonesia Shares ]]>
<![CDATA[Rizqiana, Zulfanita Dien]]>;
<![CDATA[Akhsan, Izzat Muhammad]]>;
<![CDATA[Priyanto, Intan Indrasara]]>;
<![CDATA[Maharani, Aninda Sabila]]>
<![CDATA[ JISA(Jurnal Informatika dan Sains) Vol 7, No 2 (2024): JISA(Jurnal Informatika dan Sains) ]]>
Publisher : <![CDATA[Universitas Trilogi ]]>
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DOI: 10.31326/jisa.v7i2.2115
<![CDATA[The growth of the capital market in Indonesia has increased from year to year. Based on data from the Indonesia Central Securities Corporation (KSEI), there has been an increase in investor growth in the capital market by 2.34%, mutual funds by 2.44%, and shares by 1.34% until August 2024. The demographic of individual investors in the capital market is dominated by Generation Z who are younger than from 30 years as much as 55.07% in August 2024 (KSEI, 2024). Shares are a form of investment that has the potential for large profits but with small risks. One sector that Gen Z is interested in investing in is the financial sector. The aim of this research is to compare the share prices of Bank Syariah Indonesia and Bank PT Ban Artos Indonesia Tbk using a Neural Network with the Long Short Term Memory (LTSM) algorithm. The data used in this research is secondary data on BSI and PT Bank Artos Indonesia Tbk share prices taken from the investing.com website. The data period used is from 01 September 2021 – 01 September 2024. Based on the results of stock price forecasting using a Neural Network with the LTSM algorithm, RMSE value for both models is for BSI 75.0757 and 91.795 for PT. Bank Artos Indonesia Tbk. A comparison of the predicted share prices of PT Bank Arto Indonesia Tbk and BSI shows that BSI's share price performance is superior to that of PT Bank Arto Indonesia Tbk.]]>
<![CDATA[APPLICATION OF TIME SERIES CLUSTER ANALYSIS IN CLUSTERING THE CENTRAL JAVA PROVINCE BASED ON THE POVERTY DEPTH INDEX ]]>
<![CDATA[Dien Rizqiana, Zulfanita]]>
<![CDATA[ Parameter: Journal of Statistics Vol. 3 No. 1 (2023) ]]>
Publisher : <![CDATA[Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako ]]>
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DOI: 10.22487/27765660.2023.v3.i1.16408
<![CDATA[Poverty is a problem that continues to be faced, especially in developing countries such as Indonesia. Poverty is included in one of the Sustainable Development Goals (SDGs) programs, which is related to hunger and health. The time series data can be clustered based on the characteristics of the time series data and adjusted to the time series pattern. The choice of distance and method used must be adjusted to the dynamic structure of time series data. The purpose of this research is to cluster districts/cities in Central Java Province based on the poverty depth index value from 2017 to 2022. The variable that used in this research is the Poverty Depth Index of 35 districts in Central Java Province from 2017 to 2022. This research used cluster time series with DTW similarity measurment. Based on theDTW and cophenetic coefficient correlation value using three linkage methods, the average linkage method has the highest cophenetic coefficient correlation value of 0.8017988. Testing the quality of clusters using the silhouette coefficient using DTW distance and average linkage method and 2 clusters are included in the good cluster category with a silhouette coefficient value of 0.60. The resulting clusters using the DTW distance and average linkage method are cluster 1 consisting of 25 districts / cities and cluster 2 consisting of 10 districts.]]>
<![CDATA[The Implementation of AI and Immersive Technology in E-Commerce: The Role of Customer Engagement as a Mediating Variable ]]>
<![CDATA[Aliyah, Kisti Nur]]>;
<![CDATA[Rizqiana, Zulfanita Dien]]>
<![CDATA[ Relevance: Journal of Management and Business Vol. 7 No. 1 (2024): (June-Issue) ]]>
Publisher : <![CDATA[UIN Raden Mas Said Surakarta ]]>
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DOI: 10.22515/relevance.v7i1.9124
<![CDATA[The headway of information and communication technology has led to significant changes in various industries, particularly in e-commerce. The integration of artificial intelligence (AI) and immersive technologies such as augmented reality (AR) and virtual reality (VR) has created new opportunities for e-commerce to improve customer experiences. This study analyzes the effects of implementing AI and immersive technology in e-commerce, focusing on customer engagement as a mediating factor. A sample of 99 participants was examined and analyzed using PLS-SEM by SmartPLS 4 software, and the findings indicate that AI and immersive technology have a positive, significant impact on online purchase intention. Customer engagement cannot mediate the relationship between artificial intelligence and online purchase intention. However, it does mediate the relationship between immersive technology and online purchase intention. Keywords: Artificial Intelligence; Immersive technology; Customer Engagement; Purchase Intention; e-commerce]]>
<![CDATA[Pendekatan Ridge Regression untuk Analisis Kualitas Layanan dan Kepuasan Pelanggan Kereta Api Perkotaan: Studi Commuterline Solo-Yogyakarta ]]>
<![CDATA[Astuti, Septin Puji]]>;
<![CDATA[Falantana, Alvian Anggi]]>;
<![CDATA[Rizqiana, Zulfanita Dien]]>;
<![CDATA[Kusumawardani, Rizky]]>
<![CDATA[ Jurnal Transportasi Multimoda Vol 21 No 2 (2023): Desember ]]>
Publisher : <![CDATA[Sekretariat Badan Kebijakan Transportasi ]]>
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DOI: 10.25104/mtm.v21i2.2153
<![CDATA[Sekarang ini, kereta api menjadi moda transportasi yang prospective bagi para komuter. Oleh karena itu, jalur komuter dikembangkan di beberapa kota di Indonesia untuk menyediakan kendaraan umum bagi masyarakat. Kereta Rel Listrik (KRL) Solo-Yogyakarta adalah salah satu jalur komuter yang ada di Indonesia. Jalur ini mulai beroperasi sejak tahun 2021. Untuk meningkatkan layanan commuterline, penelitian ini dilakukan untuk mengidentifikasi hubungan antara kepuasan pelanggan dan kualitas layanan. Lima dimensi dari Kualitas Layanan yang diusulkan oleh Parasuraman digunakan dalam penelitian ini. ridge regression diterapkan dalam penelitian untuk mengatasi kolinearitas antarvariabel independennya. Hasilnya menunjukkan bahwa semua variabel kualitas layanan memiliki pengaruh signifikan terhadap kepuasan pelanggan KRL Solo-Yogyakarta. Variabel keberwujudan dan empati adalah dua variabel yang memiliki pengaruh terbesar terhadap kepuasan pelanggan KRL Solo-Yogyakarta yaitu sebesar 0,399 dan 0,326 untuk variabel keberwujudan dan empati.]]>
<![CDATA[Detection and forecasting of housing price bubbles in Indonesia, Malaysia, and Singapore ]]>
<![CDATA[Suryati, Suryati]]>;
<![CDATA[Rizqiana, Zulfanita Dien]]>
<![CDATA[ Indonesian Journal of Islamic Economics Research Vol 5, No 2 (2023): Indonesian Journal of Islamic Economics Research ]]>
Publisher : <![CDATA[Fakultas Ekonomi dan Bisnis Islam UIN Salatiga ]]>
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DOI: 10.18326/ijier.v5i2.9783
<![CDATA[Houses are commodities to fulfill basic human needs, so the demand tends to continually increase. The research aims to assess the potential for a housing price bubble and to forecast house prices in the future. The data used in this study are secondary data from three countries, Indonesia, Malaysia, and Singapore. The method used to detect a housing bubble involves comparing the data of the House Price Index with the Consumer Price Index. The observations show that the trend in house prices in Malaysia and Singapore continues to increase each year. Indonesia exhibits a fluctuating trend in house prices. The highest value of Malaysia's housing bubble ratio is 1.94 in the 2nd quarter of 2020. Based on the ARIMA modeling results, the forecasting of the House Price Index in Indonesia, Malaysia, and Singapore shows a positive trend.]]>
