Article Per Year (5 Year)
p-Index From 2020 - 2025
1.723
P-Index
This Author published in this journals
All Journal TEKNIK INFORMATIKA J@TI (TEKNIK INDUSTRI) PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal Ilmiah Teknik Industri JURNAL PENDIDIKAN TAMBUSAI Dinasti International Journal of Education Management and Social Science JATI (Jurnal Mahasiswa Teknik Informatika) Abdimas Galuh : Jurnal Pengabdian Kepada Masyarakat Jurnal Abdimas Kartika Wijayakusuma Land Journal Competitive
Erna Mulyati
Program Studi Teknik Industri Politeknik Pos Indonesia, Jl. Sariasih No.54, Bandung
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Nursing Social Sciences Transportation Other

Published : 15 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 15 Documents
Search

 1   2 
Optimizing Migration of Applications Through Effective Risk Measurement Maniah, Maniah; Mulyati, Erna; Hamidin, Dini
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 13 No. 1 (2025): Maret 2025
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v13i1.10800

Abstract

Cloud Computing is a service that provides network storage space and computer resources using an internet connection as an access medium. The process of migrating to cloud computing goes through several stages sequentially and continuously, but sometimes the process of migrating to cloud computing faces obstacles or even failure, this is of course a risk for cloud service users. For this reason, before migrating to the cloud, it is necessary to prepare well, because if not, it will cause losses which will have a risk impact on the company. An effort to minimize risks for cloud service users is to carry out a risk assessment. The aim of this research is to create a model for risk assessment of logistics business applications in cloud migration. The risk value measurement model developed adopts the risk management model from the ISACA Risk IT Framework, the risk management process part of the ISO 31000 standard and adopts the phases of the OCTAVE method. Based on the method of measuring risk values from the results of this research, companies will know how much risk is likely to arise due to the use of cloud data centers, so that risk mitigation can be carried out immediately. This will have an impact on increasing the security of cloud services, and this is the main thing in increasing public confidence in using cloud services.
Implementasi Manajemen Risiko dengan Pendekatan Risk Register Sebagai Upaya Peningkatan Bidang Produksi dan Pemasaran di Moza Mom & Kids Maniah, Maniah; Mulyati, Erna; Casmadi, Yohanes
Jurnal Abdimas Kartika Wijayakusuma Vol 6 No 1 (2025): Jurnal Abdimas Kartika Wijayakusuma
Publisher : LPPM Universitas Jenderal Achmad Yani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26874/jakw.v6i1.669

Abstract

Penerapan manajemen risiko di perusahaan sangat penting, agar pengendalian terhadap aktivitas yang ada dapat dipantau sehingga ketika ada hal-hal yang memungkinkan munculnya risiko akan cepat teratasi. Pengabdian kepada Masyarakat (PkM) Universitas Logistik dan Bisnis Internasional bertujuan untuk mengimplementasikan manajemen risiko dengan pendekatan risk register pada bagian produksi, dengan memperhatikan Kejadian, Penyebab, Dampak Risiko, Risk Type, dan Risk Category dan nilai Level Risiko didapat berdasarkan Likelihood dan Severity. Tujuan PKM adalah untuk mengetahui tingkat risiko dari aktivitas bisnis di bagian produksi yang dijalankan oleh mitra. Berdasarkan analisis risiko di bagian produksi didapat bahwa tingkat risiko yang tinggi dan ekstrim adalah aktivitas terkait dengan sistem inventory, sehingga mitigasi risiko yang dilakukan adalah melakukan pelatihan tentang manajemen risiko dan pengelolaan inventory bahan baku dan produk, gudang, dan pengiriman barang. Bentuk pengukuran kegiatan PKM ini menggunakan Uji Normalitas dan Uji-t berpasangan (Paired sample t-test). Hasil dari kegiatan pelatihan teridentifikasi ada peningkatan pemahaman seluruh peserta pada kategori “Tinggi” yaitu dengan nilai Persen N-Gain lebih dari 37,6%.
The Influence of Order Complexity and Logistics System Capability on Task-Technology Fit and Fulfillment Center Logistics System Capability: A Study on E-Commerce Fulfillment Centers Ramdani, Dani; Purnomo, Agus; Mulyati, Erna
Dinasti International Journal of Education Management And Social Science Vol. 6 No. 6 (2025): Dinasti International Journal of Education Management and Social Science (Augus
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijemss.v6i6.4859

Abstract

This study explores how the complexity of customer orders and the strength of logistics systems impact service quality in E-Commerce fulfillment centers, using the Task-Technology Fit (TTF) model as a framework. The research focuses on E-Commerce companies in the Jabodetabek area, gathering data from 200 employees through a quantitative method using SEM-PLS. Results show that while complex orders can improve the alignment between tasks and technology, they may reduce logistics system effectiveness. However, strong logistics capabilities enhance both TTF and service quality. The study highlights TTF as a key factor linking logistics performance to service outcomes. These findings offer both theoretical insights into the TTF model and practical guidance for E-Commerce businesses aiming to improve service efficiency by better aligning technology, logistics, and task demands.
Logistics Management Optimization through Machine Learning: A Predictive Model for Item Transfer Time in Warehouse Activity-Space Lasmana, Hendri; Purnomo, Agus; Mulyati, Erna
Dinasti International Journal of Education Management And Social Science Vol. 6 No. 5 (2025): Dinasti International Journal of Education Management and Social Science (June
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijemss.v6i5.5083

Abstract

Operational efficiency in warehouse logistics relies heavily on accurately predicting item transfer time. This study presents a machine learning-based framework using Gradient Boosting Classifier to classify transfer durations in the dynamic Jakarta Centrum warehouse, managed by the Corruption Eradication Commission (KPK) and PosIND. Field observations revealed inefficiencies due to unstructured layouts and fluctuating volumes. To improve prediction accuracy, the model incorporates Z-score normalization, SMOTE for class balancing, and hyperparameter tuning using GridSearchCV and PSO. The optimized model successfully classified 258 High, 285 Low, and 277 Medium transfer-time instances. SHAP analysis identified distance, distribution volume, and throughput as key influencing factors. Results demonstrate the potential of predictive modeling to enhance warehouse operations through better space usage, workforce planning, and SLA compliance. This study supports machine learning as a strategic tool for data-driven logistics optimization, with future work recommended to include contextual variables like workforce capacity and shift schedules for improved precision and real-world applicability.
Sentiment Analysis of Pospay Application Reviews Using the Bert Deep Learning Method Mulyati, Erna; Muhammad Ibnu Choldun Rachmatullah; Adri Sapta Firmansyah
JURNAL TEKNIK INFORMATIKA Vol. 18 No. 2: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v18i2.41116

Abstract

E-money usage in Indonesia has grown significantly due to increasing internet penetration and smartphone adoption. Digital transactions are becoming more common, with platforms like GoPay, OVO, and Dana leading the market. The government and financial institutions actively support this shift through regulations and initiatives. This study analyzes user sentiment on the Pospay application using the BERT deep learning method, based on 16,760 Google Play Store reviews. To the best of our knowledge, this is the first study to apply BERT for sentiment analysis of Pospay user reviews in Indonesia. The goal is to understand user perceptions and satisfaction. BERT helps capture subtle nuances in reviews, including informal expressions and abbreviations like "gk" for negative sentiment. The model achieves high accuracy, with precision scores of 0.82 (negative) and 0.93 (positive), and recall scores of 0.92 (negative) and 0.93 (positive). Findings suggest PT Pos should enhance application stability, security, transaction processing, and customer service. Regular updates are recommended to improve performance and user satisfaction.
Co-Authors Adri Sapta Firmansyah Aghitsna Iqbal Alif, Aghitsna Iqbal Agus Purnomo Casmadi, Yohanes Dani Ramdani, Dani Dodi Permadi, Dodi Hamidin, Dini Hidayat, Syamsu Kencana Verawati Krisnawanti Kusdanu, Saptono Lasmana, Hendri Made Prima Widyapurna Mandasari, Cindy Maniah, Maniah Muhammad Amin Muhammad Ibnu Choldun Rachmatullah Saputra, Hijrah Simbolon, Justin Goklas Sondakh, Eduard