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All Journal JATI (Jurnal Mahasiswa Teknik Informatika) West Science Interdisciplinary Studies West Science Interdisciplinary Studies
Parhusip , Jadiaman
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Humanities Computer Science & IT Economics, Econometrics & Finance Environmental Science Social Sciences

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ANALISIS DISTRIBUSI RATA-RATA WAKTU RESPON APLIKASI BERBASIS WEB MENGGUNAKAN KURVA NORMAL DAN SIMPANGAN BAKU Setiawan, Arico; Alexandro, Yosua; Parhusip , Jadiaman
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 1 (2025): JATI Vol. 9 No. 1
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i1.12176

Abstract

Penelitian ini menganalisis distribusi waktu respons rata-rata aplikasi berbasis web menggunakan pendekatan kurva normal dan simpangan baku. Permasalahan utama yang diangkat adalah ketidakpastian dalam pola distribusi waktu respons akibat berbagai kondisi operasional, seperti lonjakan lalu lintas pengguna. Penelitian ini bertujuan memberikan wawasan tentang stabilitas performa aplikasi dan menyarankan perbaikan untuk meningkatkan pengalaman pengguna. Data yang digunakan adalah data sekunder dari laporan kinerja server pada platform cloud computing. Metode yang diterapkan mencakup perhitungan statistik deskriptif, visualisasi data, dan uji normalitas untuk menilai kesesuaian distribusi waktu respons dengan pola normal. Hasil menunjukkan bahwa waktu respons aplikasi sebagian besar mengikuti distribusi normal namun dengan simpangan baku yang signifikan, mencerminkan variasi performa web berdasarkan pada berbagai faktor seperti jenis tugas, status tugas, dan prioritas tugas. Identifikasi pola distribusi ini membantu pengelola aplikasi dalam mengoptimalkan desain sistem dan alokasi sumber daya. Penelitian ini menawarkan kontribusi praktis untuk pengembang dan administrator sistem dalam meningkatkan kinerja aplikasi web berbasis cloud.
Revolutionizing Supply Chain Management: Internet of Things (IoT) and Machine Learning on Logistics Transparency and Efficiency in the Retail Industry in Indonesia Judijanto, Loso; Parhusip , Jadiaman; Sumerli A. , Chevy Herli; Mu'min, Halek
West Science Interdisciplinary Studies Vol. 3 No. 03 (2025): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v3i03.1763

Abstract

The integration of Internet of Things (IoT) and Machine Learning (ML) technologies is transforming supply chain management, particularly in the retail industry. This study examines the impact of IoT implementation and ML application on logistics transparency and operational efficiency in Indonesia’s retail sector. Using a quantitative research approach, data were collected from 115 professionals and analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS). The findings reveal that IoT and ML significantly enhance logistics transparency, which, in turn, positively influences operational efficiency. This study highlights the mediating role of logistics transparency and underscores the importance of leveraging digital technologies for improving supply chain performance. These findings provide actionable insights for stakeholders aiming to optimize their logistics operations in dynamic and competitive markets. 
Revolutionizing Supply Chain Management: Internet of Things (IoT) and Machine Learning on Logistics Transparency and Efficiency in the Retail Industry in Indonesia Judijanto, Loso; Parhusip , Jadiaman; Sumerli A. , Chevy Herli; Mu'min, Halek
West Science Interdisciplinary Studies Vol. 3 No. 03 (2025): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v3i03.1763

Abstract

The integration of Internet of Things (IoT) and Machine Learning (ML) technologies is transforming supply chain management, particularly in the retail industry. This study examines the impact of IoT implementation and ML application on logistics transparency and operational efficiency in Indonesia’s retail sector. Using a quantitative research approach, data were collected from 115 professionals and analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS). The findings reveal that IoT and ML significantly enhance logistics transparency, which, in turn, positively influences operational efficiency. This study highlights the mediating role of logistics transparency and underscores the importance of leveraging digital technologies for improving supply chain performance. These findings provide actionable insights for stakeholders aiming to optimize their logistics operations in dynamic and competitive markets. 
Co-Authors Alexandro, Yosua Judijanto, Loso Mu'min, Halek Setiawan, Arico Sumerli A. , Chevy Herli