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Saran Implementasi Sistem ERP Berdasarkan Keuntungan dan Tantangan: Literature Review: Suggestions for ERP System Implementation Based on Benefits and Challenges: Literature Review Muhammad Syaifuddin, Nur; Zaini, Ahmad; Suriansyah, Muhammad; Puji Widodo, Aris
Technomedia Journal Vol 8 No 3 Februari (2024): TMJ (Technomedia Journal)
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v8i3.2176

Abstract

This research is a literature review that aims to investigate the implementation of Enterprise Resource Planning (ERP) systems and provide practical suggestions based on the benefits and challenges associated with ERP systems. ERP is software designed to integrate various functions and departments in a company into one integrated system. ERP implementation can provide benefits such as increased operational efficiency, better monitoring of company performance, and better decision making. However, ERP implementation also presents challenges such as high costs, change resistance from employees, and integration problems with existing systems. This research uses the Systematic Literature Review (SLR) method to identify, assess and interpret findings related to ERP implementation. The results of this research provide practical suggestions, including a focus on key benefits such as increased efficiency, reduced costs, and improved data quality. In addition, companies also need to overcome challenges such as high costs, change resistance, and integration problems. By paying attention to these suggestions, companies can maximize the benefits of implementing an ERP system and improve their operational performance and strategy. Keywords : Advantages, Challenge, Suggestion, Implementation, ERP
Penerapan Tata Kelola Teknologi Informasi pada Instansi: Systematic Literature Review Alfajri, Willy Bima; Puji Widodo, Aris; Adi, Kusworo
Jurnal Nasional Teknologi dan Sistem Informasi Vol 7 No 3 (2021): Desember 2021
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v7i3.2021.191-198

Abstract

Tata kelola TI sudah banyak diterapkan dalam beberapa instansi pemerintah maupun swasta, penerapan ini bertujuan untuk meningkatkan kualitas instansi dalam pesatnya perkembangan teknologi saat ini. Banyaknya instansi yang menerapkan tata kelola TI tanpa adanya aturan apapun yang membuat belum adanya standarisasi yang harus diikuti setiap instansi dalam penerapan tata kelola TI. Artikel ini membahas tentang framework dan domain apa yang sering digunakan dalam evaluasi tata kelola TI serta instansi apa yang sering melakukan evaluasi terhadap tata kelola TI-nya. Systematic literature review digunakan sebagai metode penelitian dengan mencari artikel terkait dengan tema yang dipilih. 142 artikel ditemukan, dengan kriteria inklusi dan eksklusi digunakan untuk memperoleh hasil penelusuran artikel yang lebih baik. Setelah menerapkan kriteria inklusi dan eksklusi tersisa 77 artikel yang dapat ditinjau lebih jauh. Dari 77 artikel yang masuk dalam kategori studi kandidat, setelah ditinjau judul, abstrak dan kesimpulan artikel hanya 30 artikel yang sesuai dengan tujuan penelitian. Hasil yang didapatkan menyebutkan bahwa Control Objectives for Information and Related Technology (COBIT) 5 adalah framework yang paling banyak diaplikasikan dalam Studi Evaluasi maupun Audit Tata Kelola TI pada instansi di Indonesia. Dan domain deliver, service, support (DSS) adalah domain yang paling banyak digunakan dalam artikel, serta instansi swasta merupakan instansi yang paling banyak melakukan evaluasi terhadap tata kelola TI-nya.
Comparative Performance Analysis of Deep Learning Models for Cryptocurrency Price Forecasting Pambudi, Ryo; Mutiara Kusumo Nugraheni, Dinar; Puji Widodo, Aris
Scientific Journal of Informatics Vol. 12 No. 4: November 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v12i4.35653

Abstract

Purpose: This research aims to find an accurate cryptocurrency price prediction model to mitigate financial risks caused by high price volatility. This research compares the predictive capabilities of five Deep Learning model, namely LSTM, GRU, BiLSTM, Transformer, and Performer, for  predicting cryptocurrency prices with the highest accuracy in the digital financial market. Methods: The methods applied in this research are dataset, preprocessing data, model training, and model evaluation. The dataset used in this study, namely the price per minute data for BTC, ETH, BNB, and XRP, was obtained from Kaggle. Data processing includes normalization using MinMaxScaler and sequence generation through the Sliding Window technique. To validate each deep learning model, and four metrics consisting of MAE, MSE, RMSE, and MAPE are used for evaluation. Result: The Transformer model created the best results for the lowest MAPE value across all datasets, the smallest being BTC and ETH at 0.20%, BNB at 0.29%, and XRP at 0.36% demonstrating high accuracy and generalization. The BiLSTM was ranking second since it captured effectively the bidirectional temporal dependencies; the GRU was moderate but stable in its performance. The data showed that the accuracy of LSTM and Performer varied. Novelty: This study offers a comprehensive comparison of various Deep Learning models in detail, enabling it to find the best model for predicting cryptocurrency prices with high accuracy. This study provides valuable insights for the development of advanced deep learning-based price forecasting systems in the field of digital financial analysis.