Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal SCIENCE TECH: Jurnal Ilmiah Ilmu Pengetahuan dan Teknologi Jurnal Teknik Industri Terintegrasi (JUTIN)
Anwar, Andries
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Penerapan Model ARIMA dalam Peramalan Permintaan untuk Meningkatkan Efesiensi Manajemen Persediaan pada CV Kopi Biji Palembang Gymnastiar, Muhammad; Anwar, Andries
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 8 No. 4 (2025): October
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v8i4.48943

Abstract

This study is motivated by unpredictable demand fluctuations at CV Kopi Biji Palembang, which often result in the risk of both overstock and stockout. The research aims to improve inventory management efficiency through the application of the ARIMA (Autoregressive Integrated Moving Average) model for coffee demand forecasting. This quantitative study utilizes six months of historical demand and inventory data, with steps including parameter identification (p,d,q), stationarity testing, and model evaluation using AIC, BIC, and MAPE. The results show that the ARIMA (1,1,1) model provides highly accurate predictions with a MAPE of 0.65%, effectively reducing overstock and stockout risks, lowering storage costs, and supporting more precise procurement planning. This study recommends integrating ARIMA forecasting results with EOQ and safety stock calculations to optimize inventory decision-making. 
Integrasi SERVQUAL, Kaizen, dan Time Study dalam Evaluasi Lean Management untuk Peningkatan Kinerja Layanan Mahasiswa Arimbi, Puri Sastia; Pasmawati, Yanti; Hardini, Septa; Anwar, Andries
Science Tech: Jurnal Ilmu Pengetahuan dan Teknologi Vol 12 No 1 (2026): February
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/st.vol12.no1.a20699

Abstract

This study aims to evaluate the implementation of Lean Management in improving service performance at the Student Service Center of Universitas Bina Darma. The service problems include long waiting times, queue congestion, and the absence of clear task distribution among staff, which potentially leads to process waste and reduced service quality. The study employed a descriptive quantitative approach integrating three methods: SERVQUAL to measure student satisfaction (363 respondents), Kaizen to assess employee performance (5 staff members), and time study to analyze process efficiency and waste. Data were analyzed using satisfaction gap calculation, performance indicator assessment, standard time measurement, and classification of value-added and non-value-added activities. The results show that the empathy and assurance dimensions have positive gaps, while responsiveness shows a negative gap indicating low service speed. Standardization and just in time are categorized as high, whereas waste elimination and employee involvement remain low. Although operator capacity is sufficient, the lack of task distribution causes queues and dominant waiting waste as well as non-value-added activities. Therefore, Lean Management improves service performance, but optimization requires workflow restructuring, process digitalization, and increased employee involvement in continuous improvement.
Analisis Efektivitas Customer Relationship Management (CRM) Berbasis Otomatisasi dan Artificial Intelligence Muiz, Choirummansyah; Pasmawati, Yanti; Anwar, Andries; Rizal, Syahril
Science Tech: Jurnal Ilmu Pengetahuan dan Teknologi Vol 12 No 1 (2026): February
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/st.vol12.no1.a20718

Abstract

Digital transformation in higher education has accelerated the integration of Customer Relationship Management (CRM) systems with Artificial Intelligence (AI) to enhance service quality and user loyalty. However, empirical studies examining the combined effects of service personalization, response speed, and interaction automation on user loyalty within higher education remain limited. This study aims to analyze the effectiveness of AI-based CRM implementation in the Career Center website of Universitas Bina Darma. A quantitative approach was employed using survey data collected from 215 respondents. Multiple linear regression analysis was conducted to examine the effects of Service Personalization (X1), Response Speed (X2), and Interaction Automation (X3) on User Loyalty (Y). The results indicate that all variables have a positive and significant effect on user loyalty (p < 0.05). Service personalization emerged as the most dominant factor (β = 0.413), followed by interaction automation (β = 0.265) and response speed (β = 0.231). The model demonstrates moderate explanatory power with an R² of 0.267 and an Adjusted R² of 0.257. These findings suggest that in the higher education context, AI-driven personalization and adaptive service delivery play a more critical role in fostering user loyalty than mere technical efficiency. Practically, the study recommends prioritizing data-driven personalization strategies in developing AI-based CRM systems in universities.
Co-Authors Arimbi, Puri Sastia Gymnastiar, Muhammad Muiz, Choirummansyah Septa Hardini Syahril Rizal, Syahril Yanti Pasmawati