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Business Growth through Consumer Insights: The Economic Influence of Taste, Product Excellence, and Price Haikal, Fikri; Ambarwati, Rita; Adji, Kumara
International Journal of Economics Development Research (IJEDR) Vol. 5 No. 6 (2024): International Journal of Economics Development Research (IJEDR)
Publisher : Yayasan Riset dan Pengembangan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/ijedr.v5i6.7088

Abstract

This research aims to analyze the influence of taste, product excellence, and cost impact or price on purchasing decisions for Sempol Gendut.Located on JL DR Wahidin GG 4 RT 011 RW 002 Bulusidokare Village, Sidoarjo District, Sidoarjo Regency, East Java, 61216. The data collection method uses a questionnaire and observation. The sampling method employed is simple random sampling, and the data analysis is conducted using the SEM PLS approach.Data processing in this study was carried out using Smart PLS version 4.0. Hypothesis testing was conducted through path direct effect tests and indirect effect tests. The analysis results revealed that the taste variable has a positive and significant influence on purchasing decisions, while the product excellence and cost variables also demonstrated positive and significant effects.
Enhancing Sales Prediction for MSMEs: A Comparative Analysis of Neural Network and Linear Regression Algorithms Taufiqih, Rahmad; Ambarwati, Rita
Jurnal Teknologi dan Manajemen Informatika Vol. 10 No. 1 (2024): Juni 2024
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jtmi.v10i1.11875

Abstract

The increasingly fierce competition in the Micro, Small, and Medium Enterprises (MSME) industry has made business actors predict sales to find out future sales predictions and prepare strategies to deal with market trends that will occur in the future. Most MSMEs still do not have a prediction system. So, to set sales targets each year, they always use manual estimates by reviewing the previous year's sales data. Therefore, this research aims to predict sales and analyze the error value of sales data forecasting so that it can provide recommendations for strategies to increase sales. This research will apply neural network and linear regression algorithms to predict sales from 2020 to 2022. Based on the results of method testing, the artificial neural network algorithm is more suitable for forecasting sales than the linear regression algorithm. The test results obtained an RMSE value of 40,070 in the neural network method using one hidden layer and an RMSE value of 66,998 derived from the feature selection T-test and iterative T-test with a minimum tolerance value of 0.05 in the linear regression method.
Prediction analysis of retail store sales level using neural network algorithm method based on customer segments Yuniar, Mylenia Martina; Ambarwati, Rita
International Journal of Industrial Optimization Vol. 5 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v5i2.9889

Abstract

Marketing activities are of significant importance to business operations, as they are uniquely positioned to provide value to consumers. The marketing mix represents one of the strategic approaches employed to attain these organizational objectives. However, the company's sales data is only available for consultation in the archives. By understanding customer preferences and requirements, the company can readily develop an effective marketing strategy to compete with similar businesses. Accordingly, this study employs the neural network methodology to forecast sales based on the company's historical sales data. The research method employs a neural network due to its capacity for processing substantial data sets with flexibility. Moreover, the Root Mean Square Error (RMSE) must be employed to ascertain the precision of the utilized model. The findings of this study indicate that the discrepancy between the actual and predicted values is minimal, suggesting that the model is able to accurately represent the data. Similarly, the results of the RMSE (Root Mean Square Error) demonstrate that the model's accuracy is improving, with minimal values observed in each segment. A 4P marketing mix strategy may be employed to enhance the company's sales potential. Based on the findings of the research, it can be posited that the results of the prediction data set, the visual prediction results, and the RMSE using the Neural Network method can be utilized effectively and accurately to forecast sales and assist company owners and management in considering target sales levels in the future.
Pengaruh Viral Marketing, Brand Ambassador, Brand Trust, dan Kualitas Produk Terhadap Keputusan Pembelian pada Live Tiktok Shop Nurhafizah, Intan; Adji Kusuma, Kumara; Sukmono, Rita Ambarwati
Jambura Journal of Educational Management Volume 6 Nomor 1, Maret 2025
Publisher : JURUSAN MANAJEMEN PENDIDIKAN FAKULTAS ILMU PENDIDIKAN UNIVERSITAS NEGERI GORONTALO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37411/jjem.v6i1.3759

Abstract

Penelitian ini memiliki tujuan untuk menguji dan memahami pengaruh dari Viral Marketing, brand ambassador, brand trust, dan kualitas produk terhadap keputusan pembelian pada short live tiktok shop. Penelitian ini menggunakan penelitian kuantitatif. Pada penelitian ini seluruh masyarakat yang pernah membeli produk di live tiktok shop yang jumlah tepatnya tidak diketahui, dijadikan sebagai populasi pengambilan sampel dengan menggunakan metode non-probability sampling melalui teknik purposive sampling. Pengambilan data pada penelitian ini dengan melalui observasi dan menyebarkan kuisioner yang diukur dengan menggunakan skala likert. Pengolahan data dilakukan dengan menggunakan aplikasi software SmartPLS
Leveraging Social Network Analysis for Enhancing Safety Reporting in the Workplace: A Case Study of the IZAT Application Widya, Paramitha Puspa; Ambarwati, Rita; Dedy, Dedy; Alimova, Mashhura Toirхonovna
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 26 No. 1 (2024): June 2024
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.26.1.9-24

Abstract

Unsafe Condition Reporting is an important source of information for companies to determine whether the reporting can be identified effectively as the key to reducing work accidents. This research aims to ascertain the Social Network Analysis visualization network in the context of reporting unsafe conditions in the IZAT application and categorizing data processing outcomes. The findings revealed that the data collection process yielded 26,658 data items. The Unsafe Condition content comprised 79,667 words, with 2,388 unique words identified. The average number of occurrences per word was 33.36139. Certain network property calculations can be inferred from these results. Then, the word mapping with five related topics was carried out. The results of the categorization of the unsafe condition word mapping can be used as evaluation material for companies to prevent work accidents. In particular, the network visualization results can identify the most discussed topics and social network relationships of reporting in the IZAT application.
Efficiency Redefined: An ANP-Optimized Work Scheduling on Employee Productivity in the Manufacturing Industry Muzakki, Ilham; Ambarwati, Rita
Jurnal Minds: Manajemen Ide dan Inspirasi Vol 11 No 2 (2024): December
Publisher : Management Department, Universitas Islam Negeri Alauddin Makassar, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/minds.v11i2.49505

Abstract

Scheduling is one of the important factors that affect employee productivity in a company. PT Maspion, as one of the large companies with a large number of employees, faces challenges in optimal work scheduling to meet varied production needs. This study aims to optimize work scheduling using the Analytic Network Process (ANP) method by considering several dimensions of criteria such as consistency, predictability, adequacy, and control. The research method used is a descriptive quantitative approach with primary data obtained through interviews and questionnaires to 30 experts in the field of work scheduling. The results show that consistent, predictable, adequate, and controlled work scheduling can increase employee productivity and employee well-being. In conclusion, the application of the ANP method in work scheduling can help companies in increasing employee productivity and welfare.
Enterprise Internal Strategy at Management Information System “Khanza” Muhammadiyah Sidoarjo Hospital Wahyuni, Eka Risma; Ambarwati, Rita; Hariasih, Misti
Jurnal Aplikasi Bisnis dan Manajemen Vol. 11 No. 2 (2025): JABM Vol. 11 No. 2, May 2025
Publisher : School of Business, Bogor Agricultural University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/jabm.11.2.648

Abstract

Background: Management Strategy using SI/TI Strategy in operational management and logistics at Muhammadiyah Sidoarjo Hospital with the SIMRS Khanza application is one of the programs that supports active management and logistics at Muhammadiyah Sidoarjo Hospital. The primary objective is to know SIMRS Khanza's operational management and logistics performance to improve service quality.Purpose: Find the Management Strategy using IS/IT Strategy in operational and logistics management at Muhammadiyah Hospital Sidoarjo with the SIMRS Khanza application.Design/methodology/approach: This research uses a descriptive qualitative approach. According to Porter's Value Chain Model, the data collection and analysis stages used value chain analysis. The study results show that Muhammadiyah Sidoarjo Hospital needs to improve operational and logistical management by emphasising IS/IT strategic planning and developing hospital websites and medical records to support services, health services, administration, and research. Analysis of Porter's Value Chain Model explains that the Sidoarjo Muhammadiyah Hospital carried out two activities related to improving services at the Sidoarjo Muhammadiyah Hospital. Findings/Result: The main activities include Inbound logistics, Operations, Outbound Logistics, Marketing and Sales, and Service. Supporting activities include Firm Infrastructure, Human Resource Management, Technology Development, and Procurement. Muhammadiyah Hospital conducted two exercises to improve services at Muhammadiyah Sidoarjo Hospital.Conclusion: This study found that the main activities in service improvement include inbound logistics, operations, outbound logistics, marketing and sales, and service.Originality/value (State of the art): This study is original in applying Porter's Value Chain Model to analyse IS/IT strategy in operational and logistics management at Muhammadiyah Hospital Sidoarjo, primarily through implementing the SIMRS Khanza application. Keywords: IS/IT strategy, management hospital, management strategy, operational and logistics, value chain
The Influence of Promotion, Celebrity Support, E-WOM (Electronic Word of Mouth) and Halal Awareness on Purchasing Decisions for Skincare Product at Marketplace in East Java Fitriani, Lita Marshella; Febriansah, Rizky Eka; Sukmono, Rita Ambarwati
Indonesian Interdisciplinary Journal of Sharia Economics (IIJSE) Vol 8 No 2 (2025): Sharia Economics
Publisher : Sharia Economics Department Universitas KH. Abdul Chalim, Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31538/iijse.v8i2.6387

Abstract

The influence of promotions, celebrity endorsements, E-WOM (Electronic Word of Mouth), and halal awareness plays an important role in influencing purchasing decisions for skincare products in the East Java marketplace. Promotions, celebrity endorsements, E-WOM (Electronic Word of Mouth), and halal awareness are factors that influence consumers' decisions to make purchases. This research aims to determine the influence of promotions, celebrity endorsements, E-WOM (Electronic Word of Mouth), and halal awareness on purchasing decisions for skincare products on marketplaces in East Java. This research method uses descriptive analysis with a quantitative approach. Primary data was obtained by sharing the questionnaire link using Google Form. The data analysis technique uses Partial Least Square 4.0. The results of this research show that promotions, celebrity endorsements, E-WOM (Electronic Word of Mouth), and halal awareness have a positive and significant effect on purchasing decisions.
Harnessing Lean and FMEA techniques to eliminate waste and enhance performance in poultry processing Husna, Rofiatul; Ambarwati, Rita; Turekulova, Dametken Medihanovna
Jurnal Sistem dan Manajemen Industri Vol. 9 No. 1 (2025): June
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v9i1.10078

Abstract

This study integrates lean manufacturing and failure mode and effects analysis (FMEA) to identify and mitigate production waste and risk in a poultry processing facility. The study identifies dominant waste types, waiting, motion, and over-processing by applying value stream mapping (VSM), fishbone diagram, and FMEA. The highest risk priority number (RPN) of 210 was found in the chilling process, indicating a critical need for corrective action. Implementing proposed improvements such as layout redesign and chiller capacity expansion resulted in measurable gains: a 5.8% reduction in labor costs, a 2.3% drop in operational expenses, and a 1.2% decrease in raw material waste. Compared to prior studies that applied Lean or FMEA separately, this research offers a structured Lean–FMEA framework tailored for the poultry industry. This model enhances efficiency while ensuring food safety and serves as a replicable method for similar industries.
How FOMO and Price Affect Online Purchase of Imitation Products Rahmawati, Dwi Maya; Ambarwati, Rita; Turekulova , Dametken Medihanovna
Journal The Winners Vol. 26 No. 1 (2025): The Winners (In Progress)
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/tw.v26i1.12969

Abstract

This research examined how factors such as Fear of Missing Out (FOMO), imitation of products, and price value influence consumers' impulsive buying and purchase intentions regarding imitation products online. A quantitative descriptive method was applied with data collected through surveys by distributing questionnaires. The sample was selected using a non-probability sampling technique with criteria: 1) residing in Indonesia, 2) aged 17 years or older, 3) having previously purchased imitation products online, and 4) willing to complete the entire questionnaire. A total of 207 respondents were analyzed. Data were processed using Partial Least Squares - Structural Equation Modeling (PLS-SEM). The findings suggest that FOMO and imitation products significantly impact online impulsive buying. Additionally, price value and online impulsive buying influence purchase intentions. There is also an indirect effect of FOMO and imitation products on purchase intentions through online impulsive buying. The research fills a gap in prior research that has rarely examined these variables' direct and indirect effects on online impulsive buying and purchase intention for imitation products. Theoretically, this research contributes to digital consumer behavior studies in the post-COVID-19 era, providing companies with a better understanding of factors influencing purchase intentions for imitation products.
Co-Authors Adji Kusuma, Kumara Adji, Kumara Agustina, Aninda Aisyah Andriani Alif , Wildan Alimova, Mashhura ToirÑ…onovna Alimova, Mashhura Toirxonovna Alimova, Mashhura Toirхonovna Alshaf Pebrianggara Alwifaqi, Jindan Anggraini , Dita Putri Anjani, Syafina Putri Arista, Sintha Wahyu Astuti, Rini Puji Bayu Prasetio Bintang Pamungkas, Moch. Ridho Choirunisa Karina Dedy dedy dedy, dedy Detak Prapanca Devan Kertajasa Dewi Komala Sari Dhea Ariesta Djoko Cahyo Utomo Lieharyani Dwi Mega Aprilia Farhan , Akmal FASYA, KHALIDA Fatchiyah, Alifatul Febriliyan Samopa Febriyanti, Kadek Dwi FIKRI HAIKAL Firdaus, Handika Fitriani, Lita Marshella Ghianti, Anneke Chitra Giandi, Oxsy Hadiah Fitriyah Hafif Wisnu Wahyudi Handiwibowo, Gogor Arif Hanifa, Muhammad Hendra Sukmana Herlinda Maya Kumala Sari, Herlinda Maya Kumala Hidayat, Anastasya Putri Husna, Rofiatul Iffat, Emmira Illahi, Utami Nur Imawati , Angraini Putri Indah Lestari, Indah Istiqomah, Rahmatul Kharisma, Risky Ageng Khisamuddin, Muhammad Idrus Khoiriyah, Dwi Himatul Lestari, Putri Indah Lilik Indayani Melania, Dewi Riski Meynur Rohmah Ubaidillah Millenia, Arum Miranda Nindi Grazia Misti Hariasih Mochamad Rizal Yulianto Mohammad Isa Irawan Mubarokah, Annisa’ul Muhammad Fatihul Iman Muhammad Ridho Bintang Janaputra Muthiah, Imroatul Muzakki, Ilham Nafis, Khilyatun Nasrudiansyah, Dicky Septian Nugroho, Brilian Nur Ainun Jariyah Nur Chamila, Ayuni Nur Fazria Masfufah Nurhafizah, Intan Nurjanah, Firda Awalul Octhavia , Ristha Prasetyo, Deddy Prasetyo, Wahyu Eko Rahmadhani, Debi Rahmah, Adinda Syafira Rahmawati, Dwi Maya Ramadani, Mita Putri Rizky Eka Febriansah Rizky Hidayat, Rizky Sigit Hermawan Silmi, Fahmi Amil Sri Susilawati Wati Sriyono Sriyono Sriyono Sriyono Sriyono Sudiarto, Dimas Arfi Sudibyo, Eko Sumartik Sutrisno, Sutrisno Syaifuddin, Aldy Hamid Taufiqih, Rahmad Thamrin, Suyono Tiarazahra, Kania Lovia Tinah, Tinah Toirxonovna, Alimova Mashhura Turekulova , Dametken Medihanovna Turekulova, Dametken Medihanovna UB, A. Riyadh Wahyuni, Eka Risma Wardani, Dwi Sukma Widya, Paramitha Puspa Widyasari, Dwi Fitri Wijayanti , Putri Nur Rizki Wilujeng, Aura Masdena Nur Wiwik Sulistiyowati Yahya, Moch Roziqi Yuniar, Mylenia Martina Zain, Muhammad Fikri Bariq