cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Prof. Dr. H. Jufriadif Na`am, S.Kom, M.Kom
Contact Email
jufriadifnaam@upiyptk.ac.id
Phone
+6287895670026
Journal Mail Official
infeb@upiyptk.ac.id
Editorial Address
Kampus Universitas Putra Indonesia YPTK Padang Jl. Raya Lubuk Begalung Padang, Sumatera Barat - 25221
Location
Kota padang,
Sumatera barat
INDONESIA
Jurnal Informatika Ekonomi Bisnis
Published by Universitas Putra Indonesia YPTK Padang
ISSN : 27148491     EISSN : -     DOI : https://doi.org/10.37034/infeb
Core Subject : Economy,
Economics, Econometrics & Finance
Jurnal Informatika Ekonomi Bisnis adalah Jurnal Nasional, yang didedikasikan untuk publikasi hasil penelitian yang berkualitas dalam bidang Informatika Ekonomi dan Bisnis, namun tak terbatas secara implisit. Jurnal Informatika Ekonomi Bisnis menerbitkan artikel secara berkala 4 (empat) kali setahun yaitu pada bulan Maret, Juni, September, dan Desember. Semua publikasi di jurnal ini bersifat terbuka yang memungkinkan artikel tersedia secara bebas online tanpa berlangganan. Jurnal Informatika Ekonomi Bisnis sebagai media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis dalam bidang informatika ekonomi dan bisnis. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada masyarakat luas, serta sebagai sumber referensi akademisi dalam bidang informatika ekonomi dan bisnis.
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Bisnis, Menejemen, dan Akutansi (Lain-Lain)
Articles 616 Documents
 46   47   48   49   50 
Building Customer Trust: An Empirical Study in Marketplace Riwu, Yonas Ferdinand; Natonis, Sari Angriany; Arthana, I Komang; Anabuni, Anderias U. T.; Aman, Dominikus K.T
Jurnal Informatika Ekonomi Bisnis Vol. 6, No. 4 (December 2024)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v6i4.1002

Abstract

This study aims to analyze how online customer trust is affected by online customer ratings and online customer reviews on the Tokopedia marketplace. This study used quantitative data and was analyzed with the help of SEM-Partial Least Squares (PLS). Data in this study as many as 96 respondents were obtained through online questionnaires with purposive sampling techniques. Results show that online customer reviews have an influence and significance on customer trust, this shows that others have had experience with the product or service. When potential customers see positive reviews from fellow customers, it validates the credibility and quality of the offer, thus building trust. Honest reviews from real customers carry more weight than promotional content from brands. Customers tend to trust their colleagues' opinions more than marketing messages because they perceive them as untendentious and reliable. When individuals feel associated with positive experiences shared by others, they feel more emotionally connected to the brand, which reinforces trust and drives purchase decisions. Then online customer rating has a significant effect on customer trust, it shows that when a product or service gets a high rating from a large number of customers, it signals to potential customers that the item is considered good by those who have used it before. People tend to believe in the majority. If most customers give a high rating to a product or service, potential buyers will tend to go with the flow and also have high trust in the item Customer ratings give a perception of the credibility of a brand or company. When a brand has consistently high rankings, it shows that the brand is considered reliable by customers, which in turn builds trust.
Nilai Ekonomi Pekarangan: Program Pekarangan Pangan Lestari Kabupaten Agam Lusiani, Gustina; Maryanti
Jurnal Informatika Ekonomi Bisnis Vol. 6, No. 4 (December 2024)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v6i4.1015

Abstract

This study aims to analyze the economic value of the Sustainable Food Garden Program (P2L) in Agam Regency. A quantitative method was applied with a sample of 50 respondents selected using proportionate random sampling. Data was collected through questionnaires and documentation and analyzed using farm income tests, B/C and R/C ratios, as well as paired t-tests. Results indicate that the average annual net income from home gardens reaches IDR 1,551,432, with a B/C ratio of 3.85 and an R/C ratio of 4.73, suggesting the economic feasibility of this activity. The P2L program contributes 5.04% to total household income, helping to reduce household expenses for vegetables and herbal medicines. Based on paired t-test results, household income was found to increase by IDR 129,286 per month after program implementation, significant at a 95% confidence level. The P2L program has proven effective in improving family welfare through optimal use of home garden space.
Pengaruh Strategi Pameran dan Penjualan Pribadi terhadap Penjualan Jasa Trucking PT Amerta Jaya Usahatama Alamsyah, Kemal; Astuti, Budi
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 1 (March 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i1.1086

Abstract

PT Amerta Jaya Usahatama sebagai perusahaan yang bergerak dalam bidang jasa pengiriman harus selalu mempunyai tujuan untuk berkembang. Tujuan tersebut dapat dicapai melalui upaya untuk dapat mempertahankan dan meningkatkan tingkat keuntungan atau laba operasional perusahaan melalui pengimplementasian stratergi pemasaran yang tepat. Penelitian ini bertujuan untuk menganalisis pengaruh strategi pameran dan penjualan pribadi terhadap penjualan di PT Amerta Jaya Usahatama dengan menganalisis media pemasaran yang digunakan yaitu media promosi pameran, dan penjualan pribadi. Jenis metode yang digunakan dalam penelitian ini adalah kualitatif deskriptif serta teknik pengumpulan data yang digunakan ialah wawancara, observasi, dan dokumentasi. Hasil penelitian menunjukkan bahwa setelah dilakukannya pameran dan penjualan pribadi yang dilakukan oleh PT Amerta Jaya Usahatama mengalami peningkatan dalam penjualan. Hal ini membuktikan bahwa dengan adanya pameran dan penjualan pribadi memberikan dampak yang signifikan terhadap penjualan pada tahun 2023.
Multiple Event Study of Covid-19 Wave In Indonesia Gessal, Zevania E.V.; Kotambunan, Eunike R.J.; Sumanti, Elvis Ronald
Jurnal Informatika Ekonomi Bisnis Vol. 6, No. 4 (December 2024)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v6i4.1022

Abstract

The Covid-19 pandemic not only affects public health but also strongly affects economic health throughout the world, more specifically in Indonesia. This study aims to see whether there are differences in the reactions of investors when there is a surge in the first wave, second wave and third wave in determining investment decisions. This research is a quantitative study using the event study method to see investor reactions from the covid-19 wave surge that affects daily stock price index movements in Indonesia. The population used in this study is stock prices in Indonesia from dates where there are spikes and decreases in Covid-19 cases. The research sample uses several Indonesian Stock Indexes. From the research that has been done, the resulting data shows that investors in Indonesia do not react significantly to the peak and valley waves of Covid-19. Only on some specific dates there is a significant change in reaction related to the Covid-19 wave. This explains that in Indonesia, information about the Covid-19 wave does not have a significant influence on the reaction of investors in determining their investment decisions, they are more focused on several other factors.
Netflix's Global Market Entry and Adaptation Strategies Critical Review Jati, Intan Mustika; Serenade, Vincensia; Umar
Jurnal Informatika Ekonomi Bisnis Vol. 6, No. 4 (December 2024)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v6i4.1049

Abstract

This review analyzes Netflix's evolution from a local DVD rental service to a global streaming leader with 221 million subscribers across 190 countries. It focuses on Netflix's strategies for international expansion, including its innovative distribution methods, personalized user experiences, and localization efforts. By adapting its business model to meet diverse cultural and regulatory demands, Netflix has successfully navigated significant challenges such as cultural barriers and competition from local and global players like Disney+ and Amazon Prime. The review synthesizes insights from two academic articles: The Business Strategy Analysis of Netflix by Yu-Hao Hsiao, which emphasizes Netflix’s subscription model and technological advancements, and Strategy for Growth and Market Leadership: The Netflix Case by Kishwar Joonas et al., which explores marketing strategies and competitive dynamics. Key findings highlight the importance of original content development, technological innovations like AI and machine learning for user engagement, and effective localization strategies. This analysis aims to provide valuable perspectives for other technology companies seeking global expansion while maintaining a competitive edge. Ultimately, it underscores the significance of aligning long-term strategic vision with short-term tactical adaptations in navigating the complexities of the global entertainment landscape. Through this critical evaluation, we gain insights into how multinational corporations can thrive in an increasingly digitalized world.
Integration of Operations Management and Marketing Strategies at Agoda: A Case Study Gusniar, Bella; Serenade, Vincensia; Nono, Yuprianingsi Fatmawati
Jurnal Informatika Ekonomi Bisnis Vol. 6, No. 4 (December 2024)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v6i4.1050

Abstract

This study delves into how Agoda, a prominent online travel platform, seamlessly integrates its operational and marketing strategies to thrive in the highly competitive travel industry. By analyzing Agoda's business model and strategic practices, the research uncovers how this synergy creates a significant competitive edge. Agoda's success is deeply rooted in its innovative use of technology, data analytics, and customer-focused approach. By harnessing data, Agoda personalizes recommendations and deals, enhancing customer satisfaction. The company also optimizes its operations through technology, boosting efficiency and cutting costs.Agoda's global expansion strategy is another key factor, as it adapts to local markets while maintaining a cohesive brand identity. This strategic harmony between operations and marketing allows Agoda to stay ahead in the rapidly changing global travel market. The findings of this research offer valuable lessons for other industry players, emphasizing the importance of data-driven decisions, tailored customer experiences, and a strong focus on customer needs. Agoda's journey provides an inspiring example of how integrating operations and marketing can lead to sustainable growth and competitiveness in a dynamic industry. This research contributes to the ongoing discussion about successful business strategies within the online travel sector, offering practical insights for companies aiming to enhance their market position.
Problematika Penggunaan Artificial Intelligence pada Mahasiswa Universitas PGRI Jombang Masruchan; Nurmilah, Rifa
Jurnal Informatika Ekonomi Bisnis Vol. 6, No. 4 (December 2024)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v6i4.1066

Abstract

This article discusses the challenges of using artificial intelligence among students at Universitas PGRI Jombang. In this context, this study examines the use of artificial intelligence, the risk of dependency, and its impact on the development of personal property rights, especially critical and contextual analysis. All of this shows that the use of artificial intelligence among students at Universitas PGRI Jombang faces many problems, including plagiarism, decreased student criticism, and decreased student performance. This study uses observation interview methods and studies among students at Universitas PGRI Jombang. This article provides an overview of the challenges of integrating AI into education and highlights the need for effective research methods to provide maximum benefits without damaging the development of students' intellectual and skill skills.
A Comparative Analysis of Machine Learning Models for Obesity Prediction Airlangga, Gregorius
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 1 (March 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i1.1089

Abstract

Obesity is a global health challenge with significant implications for public health systems and individual well-being. Predictive modeling using machine learning (ML) offers a powerful approach to identify individuals at risk of obesity and inform early intervention strategies. This study evaluates the performance of ten ML models, including Logistic Regression, Support Vector Machines, Decision Trees, K-Nearest Neighbors, Naive Bayes, Random Forest, Gradient Boosting, AdaBoost, XGBoost, and LightGBM, in predicting obesity using a publicly available dataset. A rigorous preprocessing pipeline, incorporating missing value handling, categorical encoding, normalization, and outlier detection, was applied to ensure data quality and compatibility with ML algorithms. Performance metrics such as accuracy, precision, recall, and F1-score were evaluated using 10-fold stratified cross-validation. Among the models, LightGBM demonstrated the highest test accuracy (99.19%) and F1-score (99.20%), outperforming Gradient Boosting and Random Forest, which also showed competitive results. The study highlights the superior predictive capabilities of ensemble methods while underscoring the trade-offs between model complexity and interpretability. Logistic Regression provided a strong baseline, demonstrating the importance of preprocessing, but was outperformed by advanced ensemble techniques. This research contributes to the growing field of ML-driven healthcare solutions, offering valuable insights into the strengths and limitations of various predictive models. The findings support the integration of advanced ML techniques in public health systems and pave the way for future research on hybrid and explainable models for obesity prediction and management.
A Comparative Analysis of Deep Learning Architectures for Obesity Classification Using Structured Data Airlangga, Gregorius
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 1 (March 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i1.1090

Abstract

Obesity is a significant global health concern, necessitating accurate and efficient diagnostic tools to classify individuals based on obesity levels. This study investigates the performance of five deep learning architectures: Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Bidirectional LSTM (BiLSTM) in classifying obesity levels using structured data. The dataset comprises clinical, demographic, and lifestyle features, and is preprocessed through normalization, label encoding, and Synthetic Minority Oversampling Technique (SMOTE) to address class imbalance. Each model was evaluated using accuracy, precision, recall, and F1-score metrics under stratified 10-fold cross-validation. The results indicate that MLP achieved the highest performance across all metrics, with an accuracy of 99.05%, followed closely by CNN at 98.77%. Sequential models, including LSTM, GRU, and BiLSTM, exhibited comparatively lower performance, achieving accuracies of 83.80%, 86.59%, and 86.78%, respectively. The superior performance of MLP and CNN underscores their suitability for structured datasets with static features, while the sequential models struggled due to the lack of temporal dependencies in the data. This study highlights the importance of aligning model architecture with dataset characteristics for optimal performance. The findings suggest that MLP and CNN are effective choices for obesity classification tasks, providing robust and computationally efficient solutions. Future work could explore hybrid models and incorporate temporal features to enhance the performance of sequential architecture.
Model Pemberdayaan Masyarakat Melalui Pengembangan Ekowisata Kelurahan Sumber Rejo Kecamatan Balikpapan Tengah Prasetya, Candraditya; Harahap, Syanti Dewi
Jurnal Informatika Ekonomi Bisnis Vol. 6, No. 4 (December 2024)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v6i4.1036

Abstract

This Study aims to explain a model of community empowerment through ecotourism development in Sumber Rejo Village, Balikpapan District. Qualitative descriptive methods are used to describe tourism development planning models based on community empowerment and describe ecotourism development strategies. Data analysis was carried out on data from in-depth interviews to determine the community's response regarding the stages of the ecotourism development process through community empowerment. The research results explain that the community is aware of the importance of developing their own capacity to form attitudes, behavior and thought patterns that can foster confidence, enthusiasm and motivation in developing Sumber Rejo Village with its various potentials so that it becomes ecotourism. The community has knowledge and skills in organizational development, as well as building values of togetherness, cooperation, mutual appreciation and respect, mutual help, mutual trust, hard work, a sense of justice and motivation. The research results also explain that the ecotourism development strategy is branding, upgrading, legality, packaging and marketing to maximize the production of processed water spinach and maximize sales results so as to increase opportunities for sustainable development of tourist villages.

Page 48 of 62 | Total Record : 616

 46   47   48   49   50 

Filter by Year

2019 2026


Reset
Filter By Issues
All Issue Vol. 8, No. 1 (March 2026): Accepted Vol. 7, No. 4 (December 2025): Accepted Vol. 7, No. 3 (September 2025) Vol. 7, No. 2 (June 2025) Vol. 7, No. 1 (March 2025) Vol. 6, No. 4 (December 2024) Vol. 6, No. 3 (September 2024) Vol. 6, No. 2 (June 2024) Vol. 6, No. 1 (March 2024) Vol. 5, No. 4 (December 2023) Vol. 5, No. 3 (September 2023) Vol. 5, No. 2 (June 2023) Vol. 5, No. 1 (March 2023) Vol. 4, No. 4 (December 2022) Vol. 4, No. 3 (September 2022) Vol. 4, No. 2 (June 2022) Vol. 4, No. 1 (March 2022) Vol. 3, No. 4 (December 2021) Vol. 3, No. 3 (September 2021) Vol. 3, No. 2 (June 2021) Vol. 3, No. 1 (March 2021) Vol. 2, No. 4 (December 2020) Vol. 2, No. 3 (September 2020) Vol. 2, No. 2 (June 2020) Vol. 2, No. 1 (March 2020) Vol. 1, No. 4 (December 2019) More Issue