Prof. Drs. Mustafid, M.Eng. Ph.D.

Nama Dosen:
Prof. Drs. Mustafid, M.Eng. Ph.D.

Program Studi:
Statistika (Universitas Diponegoro)

Kepakaran Dosen:
Prof. Mustafid memiliki kepakaran utama pada bidang pengendalian kualitas statistika dan sistem informasi. Keahlian ini mencakup pengembangan metode statistik untuk memastikan kualitas proses dan produk melalui teknik analisis data, serta integrasi sistem informasi dalam pengambilan keputusan berbasis data.
Fokus risetnya juga meluas pada penerapan statistika dalam teknologi digital, seperti analitik data, machine learning, dan intelligent analytics. Penerapannya dapat ditemukan dalam berbagai bidang, antara lain pengelolaan sistem bisnis, analisis perilaku konsumen, optimasi proses industri, hingga pengembangan smart system (misalnya smart city, e-commerce, dan pertanian cerdas). (stat.fsm.undip.ac.id)

Publikasi:

  1. Enhancing adaptability and accelerating convergence in non-stationary reinforcement learning via GAN-Q-learning integration
    https://doi.org/10.1016/j.eswa.2025.130694
  2. Sales Prediction in Omnichannel Distribution Systems Based on Consumer Behavior Using Process Mining and ARIMAX
    https://doi.org/10.1155/2026/6319448
  3. Integration of six sigma and association rule for customer complaints provider by.U on Google Play Store Site
    https://doi.org/10.1063/5.0201234
  4. Minimum, Maximum, and Average Implementation of Patterned Datasets in Mapping Cryptocurrency Fluctuation Patterns
    https://doi.org/10.62527/joiv.8.1.1896
  5. Model Analytic in Fintech User Comment Features Using LDA-CNN on Imbalanced Data
    https://doi.org/10.22266/ijies2024.0831.90
  6. Performance Measurement in a Custom Production Process Model Using the Process Mining Approach: A Systematic Literature Review
    https://doi.org/10.1109/ACCESS.2024.3471234
  7. Q-Learning Energy Management System (Q-EMS) in Wireless Sensor Network
    https://doi.org/10.1109/SIML62064.2024.00015
  8. Sistem business intelligence untuk mendukung perguruan tinggi yang kompetitif
    https://doi.org/10.21456/vol3iss1pp18-24 (Undip E-Journal System)
  9. Back-matter
    https://doi.org/10.21456/vol11iss2ppix (Undip E-Journal System)