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The Impact of Website Usability and Mobile Optimization on Customer Satisfaction and Sales Conversion Rates in E-commerce Businesses in Indonesia Nawir, Fadliyani; Hendrawan, Satya Arisena
The Eastasouth Journal of Information System and Computer Science Vol. 2 No. 01 (2024): The Eastasouth Journal of Information System and Computer Science (ESISCS)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esiscs.v2i01.324

This study investigates the impact of website usability and mobile optimization on customer satisfaction and sales conversion rates in e-commerce businesses in Indonesia. Utilizing a quantitative approach, data were collected from 170 respondents using a Likert scale ranging from 1 to 5. The analysis was conducted using Structural Equation Modeling-Partial Least Squares (SEM-PLS 3). The results indicate that all hypothesized relationships are positive and significant. Specifically, improvements in website usability and mobile optimization significantly enhance customer satisfaction, which in turn positively influences the sales conversion rate. The findings underscore the critical importance of optimizing website usability and mobile interfaces to boost customer satisfaction and drive higher sales conversions in the competitive e-commerce landscape of Indonesia.

The Effect of Using End-to-End Encryption in Improving Data Security in Cloud Computing Satya Arisena Hendrawan; Legito; Muhammad Bitrayoga; Jatmiko Wahyu Nugroho; Arnes Yuli Vandika
International Journal of Health, Economics, and Social Sciences (IJHESS) Vol. 7 No. 1: January 2025
Publisher : Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/ijhess.v7i1.6941

Cloud Computing offers various advantages, but also presents major challenges related to data security. End-to-end encryption (E2EE) is considered as a solution to mitigate threats to the security of data stored and processed in the cloud. This research aims to examine the effect of implementing E2EE encryption in improving data security in Cloud Computing. Using a qualitative approach with literature study and secondary data analysis, this research focuses on three main threat categories: data leakage, unauthorized access, and cyberattacks. The results show that E2EE encryption can reduce the incidence of data leakage by 80%, unauthorized access by 83.3%, and cyberattacks by 78.6%. Despite its effectiveness, E2EE encryption implementation faces challenges in encryption key management and potential degradation in system performance. Therefore, good key management and multifactor authentication are essential to ensure data security. This study concludes that although end-to-end encryption improves security, a thorough policy, including key management and access control, is needed to maximize data protection in Cloud Computing.

Analisa dan Perancangan E-Commerce Kerajinan Tangan Penyandang Disabilitas (Studi Kasus: Desa Krebet Ponorogo, Jawa Timur) Satya Arisena Hendrawan; Anang Martoyo; Diky Wardhani
Journal of Informatics and Advanced Computing (JIAC) Vol 2 No 2 (2021): Journal of Informatics and Advanced Computing
Publisher : Teknik Informatika Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar

Lembaga Rumah Kasih Sayang telah memproduksi produk kreatif hasil kerajinan tangan penyandang disabilitas. Produk yang terjual pun tidak sesuai harapan yang diinginkan lembaga. Sebulan hanya ada 1 sampai 3 produk yang terjual dan itu pun konsumen membeli datang ke tempat atau titip ke saudara terdekat. Keberlangsungan adanya teknologi informasi sangat bermanfaat terutama di zaman saat ini. Manusia dapat menggunakan seperangkat smartphone dapat mengakses dan mendapatkan informasi serta dapat transaksi jual-beli. Telah terpikirkan oleh Lembaga Rumah Kasih Sayang (RKS) untuk menerapkan sistem informasi E-Commerce yang nantinya akan membantu memasarkan dan menjual produk tersebut. Tujuan penelitian ini adalah menganalisa dan merancang E-Commerce bagi Lembaga RKS sehingga dapat produktif. Sistem E-Commerce sudah berjalan dan itu mengalami perubahan dari sisi penjualan yang lebih meningkat.

Analisa dan Perancangan E-Commerce Kerajinan Tangan Penyandang Disabilitas (Studi Kasus: Desa Krebet Ponorogo, Jawa Timur) Satya Arisena Hendrawan; Anang Martoyo; Diky Wardhani
Journal of Informatics and Advanced Computing (JIAC) Vol 2 No 2 (2021): Journal of Informatics and Advanced Computing
Publisher : Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/jiac.v2i2.3262

Lembaga Rumah Kasih Sayang telah memproduksi produk kreatif hasil kerajinan tangan penyandang disabilitas. Produk yang terjual pun tidak sesuai harapan yang diinginkan lembaga. Sebulan hanya ada 1 sampai 3 produk yang terjual dan itu pun konsumen membeli datang ke tempat atau titip ke saudara terdekat. Keberlangsungan adanya teknologi informasi sangat bermanfaat terutama di zaman saat ini. Manusia dapat menggunakan seperangkat smartphone dapat mengakses dan mendapatkan informasi serta dapat transaksi jual-beli. Telah terpikirkan oleh Lembaga Rumah Kasih Sayang (RKS) untuk menerapkan sistem informasi E-Commerce yang nantinya akan membantu memasarkan dan menjual produk tersebut. Tujuan penelitian ini adalah menganalisa dan merancang E-Commerce bagi Lembaga RKS sehingga dapat produktif. Sistem E-Commerce sudah berjalan dan itu mengalami perubahan dari sisi penjualan yang lebih meningkat.

Usability and User Experience Analysis of Language Learning Applications with Augmented Reality Technology Hendrawan, Satya Arisena; Putra, Haris Satria; Loebis, Iin Almeina; Fitriyasari, Maliatul; Basri, Hasan
Journal International of Lingua and Technology Vol. 4 No. 1 (2025)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/jiltech.v4i1.819

The integration of Augmented Reality (AR) technology into language learning applications has become increasingly popular due to its potential to enhance user engagement and improve learning outcomes. However, the usability and user experience (UX) of such applications are critical factors that determine their effectiveness. This study explores the usability and UX of language learning applications utilizing AR technology, aiming to evaluate how these applications meet the needs and preferences of users, and how they influence learning efficiency. The research adopts a mixed-methods approach, combining quantitative surveys and qualitative interviews with users who have engaged with AR-based language learning applications. Participants were asked to assess the usability aspects, such as ease of navigation, user interface design, and responsiveness, as well as their overall experience and satisfaction. The results show that users generally find AR-based language learning applications engaging and enjoyable, particularly for vocabulary acquisition and interactive learning activities. However, challenges related to technical issues, such as device compatibility and software glitches, were identified as barriers to a seamless experience. The study concludes that while AR has the potential to revolutionize language learning, further improvements in application stability, content design, and personalization are necessary to optimize usability and user satisfaction.

Market Segmentation for Local Product Marketing Strategy Using K-Means and Dempster-Shafer Algorithm Implementation Hendrawan, Satya Arisena; Yusnitasari, Tristyanti; Oswari, Teddy
Journal Innovations Computer Science Vol. 4 No. 1 (2025): May
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i1.244

Market segmentation represents a critical challenge in local product marketing, particularly when addressing complex consumer behavior patterns and uncertain classification environments in today's digital economy. This research develops and validates a hybrid model integrating K-Means Clustering with Dempster-Shafer theory to enhance segmentation accuracy and reliability for local product markets. The K-Means algorithm groups consumers based on demographic, psychographic, and behavioral characteristics, while Dempster-Shafer theory quantifies uncertainty and provides confidence measures for segment assignments. Data collection involved comprehensive consumer surveys and transaction records from 2,847 participants across multiple local product categories over a 12-month period. The hybrid model achieved superior performance with 87.5% accuracy, 85.3% precision, 86.1% recall, and 85.7% F1-score, representing improvements of 5.4% over standard K-Means and 8.2% over hierarchical clustering methods. Four distinct market segments were identified: Young Urban Professionals (28%), Value-Conscious Families (35%), Traditional Loyalists (22%), and Digital Natives (15%), each exhibiting unique purchasing patterns, digital engagement levels, and price sensitivity characteristics. Cross-validation yielded a consistency score of 0.91 with segment stability demonstrated through 8.3% churn rate and conflict measure K = 0.12, indicating substantial agreement among evidence sources. The methodology successfully addresses uncertainty in consumer classification while providing actionable insights for targeted marketing strategies, pricing optimization, and customer retention programs. Local product marketers can implement this framework to develop evidence-based marketing approaches that accommodate both traditional and digital consumer preferences, enabling competitive positioning in increasingly complex market environments. The research establishes a scalable and practical solution for small to medium enterprises seeking sophisticated market analysis capabilities without requiring extensive computational infrastructure or technical expertise.

ANALISIS PERBANDINGAN METODE PENDUKUNG KEPUTUSAN PEMILIHAN SKINCARE MENGGUNAKAN METODE SAW, WP, dan SMART Nuraeni, Yayang Ayu; Nurjanah, Noneng; Hendrawan, Satya Arisena; Muhiban, Ayi
TRANSFORMASI Vol 21, No 1 (2025): TRANSFORMASI
Publisher : STMIK BINA PATRIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56357/jt.v21i1.416

Increasing public awareness of the importance of skin care to maintain health has encouraged the emergence of various products on the market. In recent years, the skincare industry has experienced very rapid growth. This study aims to enable users to choose skincare that is safe, appropriate, and in accordance with their facial skin type with the methods used being Simple Additive Weighting (SAW), Weighted Product (WP), and Simple Multi-Attribute Rating (SMART). The results of the calculation process based on the level of suitability, it was found that using the SAW and SMART methods was better than the WP method, namely with a percentage value of suitability between 99.85719% in the SAW method, 99.85715% in the WP method, and 99.85715% in the SMART method. So the SAW and SMART methods are the most relevant methods to solve the problem of providing loans.Keywords : Skincare, Simple Additive Weighting, Weighted Product, Simple Multi-Attribute Rating, Decision Support System.

Market Segmentation for Local Product Marketing Strategy Using K-Means and Dempster-Shafer Algorithm Implementation Hendrawan, Satya Arisena; Yusnitasari, Tristyanti; Oswari, Teddy
Journal Innovations Computer Science Vol. 4 No. 1 (2025): May
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i1.244

Market segmentation represents a critical challenge in local product marketing, particularly when addressing complex consumer behavior patterns and uncertain classification environments in today's digital economy. This research develops and validates a hybrid model integrating K-Means Clustering with Dempster-Shafer theory to enhance segmentation accuracy and reliability for local product markets. The K-Means algorithm groups consumers based on demographic, psychographic, and behavioral characteristics, while Dempster-Shafer theory quantifies uncertainty and provides confidence measures for segment assignments. Data collection involved comprehensive consumer surveys and transaction records from 2,847 participants across multiple local product categories over a 12-month period. The hybrid model achieved superior performance with 87.5% accuracy, 85.3% precision, 86.1% recall, and 85.7% F1-score, representing improvements of 5.4% over standard K-Means and 8.2% over hierarchical clustering methods. Four distinct market segments were identified: Young Urban Professionals (28%), Value-Conscious Families (35%), Traditional Loyalists (22%), and Digital Natives (15%), each exhibiting unique purchasing patterns, digital engagement levels, and price sensitivity characteristics. Cross-validation yielded a consistency score of 0.91 with segment stability demonstrated through 8.3% churn rate and conflict measure K = 0.12, indicating substantial agreement among evidence sources. The methodology successfully addresses uncertainty in consumer classification while providing actionable insights for targeted marketing strategies, pricing optimization, and customer retention programs. Local product marketers can implement this framework to develop evidence-based marketing approaches that accommodate both traditional and digital consumer preferences, enabling competitive positioning in increasingly complex market environments. The research establishes a scalable and practical solution for small to medium enterprises seeking sophisticated market analysis capabilities without requiring extensive computational infrastructure or technical expertise.

Strategies for Utilizing AI and Data Analytics to Improve the Effectiveness of Public Services in Indonesia: A Local Government Level Approach Judijanto, Loso; Taufiqurokhman, Taufiqurokhman; Hendrawan , Satya Arisena; Herwanto, Herwanto
West Science Business and Management Vol. 1 No. 05 (2023): West Science Business and Management
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsbm.v1i05.470

This research investigates the strategies for utilizing artificial intelligence (AI) and data analytics to enhance the effectiveness of public services within Indonesian local governments. A quantitative analysis was conducted, involving a diverse sample of 200 participants, including local government officials, IT professionals, and citizens across various regions. The study employs a structural equation modeling approach, assessing the relationships between the implementation of AI, data analytics, and the effectiveness of public services. The measurement model confirms the reliability and validity of the constructs, while the structural model reveals significant positive paths from both data analytics and AI utilization to public service effectiveness. The findings contribute to the evolving landscape of technological integration in public administration, offering evidence-based insights for policymakers and practitioners.

ANALISIS PERBANDINGAN METODE PENDUKUNG KEPUTUSAN PEMILIHAN SKINCARE MENGGUNAKAN METODE SAW, WP, dan SMART Nuraeni, Yayang Ayu; Nurjanah, Noneng; Hendrawan, Satya Arisena; Muhiban, Ayi
TRANSFORMASI Vol 21, No 1 (2025): TRANSFORMASI
Publisher : STMIK BINA PATRIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56357/jt.v21i1.416

Increasing public awareness of the importance of skin care to maintain health has encouraged the emergence of various products on the market. In recent years, the skincare industry has experienced very rapid growth. This study aims to enable users to choose skincare that is safe, appropriate, and in accordance with their facial skin type with the methods used being Simple Additive Weighting (SAW), Weighted Product (WP), and Simple Multi-Attribute Rating (SMART). The results of the calculation process based on the level of suitability, it was found that using the SAW and SMART methods was better than the WP method, namely with a percentage value of suitability between 99.85719% in the SAW method, 99.85715% in the WP method, and 99.85715% in the SMART method. So the SAW and SMART methods are the most relevant methods to solve the problem of providing loans.Keywords : Skincare, Simple Additive Weighting, Weighted Product, Simple Multi-Attribute Rating, Decision Support System.

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