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All Journal SPEKTRUM INDUSTRI Journal of Indonesian Tourism and Development Studies Journal of Engineering and Management in Industrial System Jurnal Optimasi Sistem Industri Journal Industrial Servicess Jurnas Nasional Teknologi dan Sistem Informasi Jurnal Ilmiah Teknik Industri Industria: Jurnal Teknologi dan Manajemen Agroindustri Journal of Research and Technology Indonesian Journal of Artificial Intelligence and Data Mining JURNAL MANAJEMEN INDUSTRI DAN LOGISTIK Journal TEPAT: Teknologi Terapan untuk Pengabdian Masyarakat Jurnal Ilmiah Teknik Industri Jurnal Penelitian Enjiniring Fakultas Teknik Unhas Jurnal Teknologi dan Manajemen
Armin Darmawan
Department Of Industrial Engineering, Universitas Hasanuddin
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Transportation Other

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Comparative Deep Learning Analysis: Unveiling the Power of LSTM, BiLSTM, GRU, and BiGRU for Agricultural Stock Price Forecasting on the Indonesian Stock Exchange Fadhlurrahman, Muhammad; Darmawan, Armin
Jurnal Nasional Teknologi dan Sistem Informasi Vol 12 No 1 (2026): April 2026
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v12i1.2026.73-70

Abstract

This study aims to analyze the performance of deep learning algorithms in predicting agricultural sector stock prices on the Indonesia Stock Exchange (IDX) by comparing four models: Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), Gated Recurrent Unit (GRU), and Bidirectional GRU (BiGRU). Daily historical data of six agricultural sector stock issuers (AALI, BISI, DSNG, LSIP, SIMP, SSMS) for the period 2017–2025 was used as the dataset. The research methods included data pre-processing (normalization, 80:20 training-test data split), model training with optimal hyperparameters (unit=512, dropout rate = 0.3, epoch = 50–150, learning rate = 0.0001), and evaluation using Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), R² Score , and computation time metrics. The results show that BiGRU is the most accurate model with the lowest RMSE (7.43–17.20) and the highest R² (0.99 on BISI and SSMS), thanks to the Bidirectional architecture that processes bidirectional data to capture complex temporal patterns. However, GRU is more efficient with a training time of 40–43 seconds, suitable for real-time applications . LSTM and BiLSTM have lower accuracy, especially on volatile stocks such as DSNG (RMSE LSTM = 130.51). This study provides practical recommendations: BiGRU for long-term investment strategies that prioritize accuracy, while GRU for quick decisions based on efficiency. Theoretical implications strengthen the effectiveness of the Bidirectional architecture in financial time series analysis
Improving Service Quality Of Delivery Services Based On Heterogeneous Customer Behavior In A Developing Country: A Context During Covid-19 Rahmat Hidayat Muslimin; Armin Darmawan; Syamsul Bahri; Amrin Rapi
Jurnal Manajemen Industri dan Logistik Vol. 6 No. 1 (2022): 10 original research articles were authored/co-authored by 40 authors from 4 co
Publisher : Politeknik APP Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30988/jmil.v6i1.968

Abstract

Delivery services are going through a transition phase globally due to changes in the market dynamics and growing e-commerce industries. As the delivery services of public logistics organizations have a lasting impact on customer behavior, logistics organizations are using innovative, customer-centric, and cost-effective strategies to offer customers convenient, attractive, and effective service solutions. The current study has been undertaken to analyze the effectiveness of each element of quality services of delivery services. Qualitative and quantitative research approaches were implemented based on a hundred respondents in identifying the critical issues based on the SERVQUAL method, heterogeneous customer satisfaction index (HCSI), and mapping out prioritizing the most critical problem. The study results reveal that customers are susceptible to the responsive, assurance, and empathy dimensions. These three of five dimensions are adversely influencing the satisfaction of customers.
Co-Authors -, Nilda A Alief Rachmat Alamsyah Alamsyah Ali, Syafrillah Amrin Rapi Amrin Rapi Amrin Rapi Amrin Rapi Asmal, Sapta Bahri, Syamsul Bahri, Syamsul Bohari, Abdul Rahman Dwi Handayani Fadhlurrahman, Muhammad Fansuri, Ilham Fauziah Fauziah Irfan Rahman IRWAN SETIAWAN Kifayah Amar Muhammad, Maula Sidi MULYADI HAMBALI, MULYADI Mulyadi Mulyadi Mulyadi Mulyadi Mulyadi Mulyadi Muslimin, Rahmat Hidayat Muthalib, Irwan Setiawan Nur Khaerani Busri Nur Khaerani Busri Parenreng, Syarifuddin Mabe Pujikharisma, Andi Rahmadani, Fachriah Nur Rahman, Irfan Rahmat Hidayat Muslimin Saiful - Salam, Awal Rakhmat Samjas, Mutawakkil Syafrillah Ali Syamsul Bahri Syamsul Bahri Syamsul Bahri Syamsul Bahri Syamsul, Diniary Ikasari Tahir, Nurfaidah Yusdi, Andry