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All Journal Gaung Informatika Jurnal Ilmiah Flash Jurnal Teknik Informatika STMIK Antar Bangsa Technologia: Jurnal Ilmiah JISA (Jurnal Informatika dan Sains) Reputasi: Jurnal Rekayasa Perangkat Lunak Indonesian Journal of Networking and Security - IJNS SPEED - Sentra Penelitian Engineering dan Edukasi Journal of Paddisengeng Technology
Herryansyah .
Universitas Bina Sarana Informatika
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Library & Information Science

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PEMANFAATAN TEKNOLOGI WEB SERVICE PADA SISTEM JOB MONITORING COMPLAINT UNTUK OTOMATISASI PELAPORAN Feri Prasetyo; Diah Wijayanti; Sari Dewi; Azis Sukma Dhiana; Herryansyah Herryansyah
Technologia : Jurnal Ilmiah Vol 17 No 3 (2026): Technologia (Juli)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/jit.v17i3.23362

Abstract

Kemajuan teknologi informasi telah memberikan kontribusi besar terhadap peningkatan efisiensi dan akurasi dalam pengelolaan data. Saat ini di PT. Ekspedi Amanda Jaya untuk permintaan complaint dari bagian ke bagian lainya itu masih menggunakan manual atau lewat telpon langsung, sehingga masih kurang efektif dan efisien karena setiap permintaan tidak di lengkapi dengan dokument permintaan dan terkadang menyebabkan permintaan tidak dapat di realisasikan dengan baik dan dari atasan bagian tidak mengetahui permasalahan yang sedang terjadi sehingga bisa menyebabkan keterlambatan. Penelitian ini bertujuan untuk mengembangkan sistem yang mampu melakukan otomatisasi pelaporan keluhan dan pemantauan kinerja secara real-time, sehingga proses administrasi menjadi lebih efisien dan transparan. Salah satu bentuk penerapannya adalah pemanfaatan teknologi Web Service dalam sistem pelaporan dan pemantauan pekerjaan (Job Monitoring Complaint). Metode penelitian yang digunakan adalah Research and Development (R&D) dengan tahapan meliputi analisis kebutuhan, perancangan sistem, implementasi, dan pengujian. Hasil penelitian menunjukkan bahwa penerapan Web Service dapat meningkatkan kecepatan proses pelaporan hingga 75% dibandingkan sistem manual. Uji performa dilakukan menggunakan Apache JMeter waktu respons rata-rata sebesar 0,34 detik per permintaan, dengan tingkat keberhasilan 99,6%. karena penggunaan Application Programming Interface (API) berbasis REST, Dengan demikian sistem ini dapat menjadi solusi efektif bagi untuk pelaporan yang cepat, akurat, dan terdokumentasi dengan baik.
AI-Driven Career Pathways: Predictive Counseling Systems for Aligning Student Potential with Future Job Markets Loso Judijanto; Herryansyah Herryansyah; Seno Lamsir
Journal of Paddisengeng Technology Vol. 1 No. 1 (2025)
Publisher : PT. Sinergi Bersahaja Sejahtera

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65224/jopate.v1i1.189

Abstract

Background. Rapid technological advancements and evolving labor markets have created significant challenges in aligning students’ academic pathways with future career opportunities. Traditional counseling approaches often lack predictive capacity, leaving students underprepared for emerging job sectors. Artificial Intelligence (AI)-driven predictive counseling systems offer new possibilities by integrating student potential, skills, and aspirations with real-time labor market trends. Purpose. This study aims to examine the effectiveness of AI-driven career counseling systems in predicting and aligning student potential with future job markets. Specifically, it explores the extent to which AI-based predictive models can enhance the accuracy of career guidance and reduce mismatches between educational outcomes and employment demands. Method. Using a quantitative design, the research collected data from 312 university students across three institutions in Indonesia. Students engaged with an AI-powered career counseling platform that generated personalized career recommendations based on academic performance, psychological profiling, and labor market analytics. Data were obtained through system usage logs, surveys, and follow-up evaluations. Statistical analyses, including regression and ANOVA, were employed to assess the impact of AI counseling on student decision-making and career clarity. Results. Findings reveal that AI-driven counseling significantly improves students’ career awareness and alignment with future labor demands. Students using the predictive system demonstrated higher confidence in their career choices and reduced anxiety about employability. Additionally, the AI system identified potential career trajectories in emerging sectors, such as digital finance, green technologies, and AI ethics, which were often overlooked in traditional counseling. Conclusion. The study underscores the transformative role of AI in educational counseling, emphasizing its potential to bridge gaps between academic preparation and job market realities. Implementing predictive AI models in career services can empower students to make informed choices, while enabling institutions to adapt curricula to future workforce needs.
Co-Authors Andi Arfian Azis Sukma Dhiana Dede Mustomi Diah Wijayanti Dwi Atmodjo WP Dwi Atmodjo WP Eko Haryadi Feri Prasetyo Hartana, Hartana Herdiansah, Arief Husni Saepulloh Indra Nanda Juarni Siregar Loso Judijanto Nanda, Indra Sari Dewi Seno Lamsir Siregar, Juarni Syafrianto Syafrianto Wijayanti, Diah