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Muhammad Wali
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INDONESIA
Jurnal Indonesia : Manajemen Informatika dan Komunikasi
Published by STMIK Indonesia Banda Aceh
ISSN : 27768074     EISSN : 27237079     DOI : https://doi.org/10.35870/jimik
Core Subject : Science, Education,
Computer Science & IT Languange, Linguistic, Communication & Media Library & Information Science
Jurnal Indonesia: Manajemen Informatika dan Komunikasi is a scholarly publication dedicated to advancing the fields of information technology and communication management in Indonesia. The journal serves as a platform for researchers, academicians, practitioners, and policymakers to share their insights, knowledge, and expertise in these domains. This journal is a peer-reviewed online journal dedicated to high-quality research publications focused on research, implementation. Jurnal Indonesia: Manajemen Informatika dan Komunikasi is a scholarly publication dedicated to advancing the fields of information technology and communication management in Indonesia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Jaringan Komputer dan Komunikasi
Articles 684 Documents
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Peningkatan Akurasi Nilai Harga Saham Menggunakan Metode Long Short-Term Memory (LSTM) pada PT Unilever Tbk Arinal, Veri; Puspita, Melli
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 1 (2025): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v6i1.1190

Abstract

The rapid development of technology has an impact on the economy of society, one of which is investing in stocks. Stocks are a proof of an individual's ownership of an asset in a company. However, stock prices have a very high level of fluctuation, so an accurate method is needed to help predict stock prices. LSTM and GRU were chosen due to their intrinsic ability to handle long-term and short-term issues in time series data. LSTM has a complex memory structure that allows decision-making based on long-term and short-term information. Meanwhile, GRU has a simpler structure with a focus on gate mechanisms to control the flow of information, resulting in a lighter and faster model. Therefore, this study will compare two RNN methods, namely Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU), in predicting stock prices using the stock price data of PT. Unilever (UNVR) with evaluation metrics MAPE and RMSE. The combination of parameters used to evaluate the MAPE and RMSE values in this study includes learning rate, timesteps, batch size, and epoch. The results of this study indicate that the GRU method is more accurate compared to the LSTM method. This is evidenced by the evaluation results of the LSTM method with the lowest MAPE value of 2.42% and the lowest RMSE value of 0.01807, while the evaluation results of the GRU method with the lowest MAPE value of 2.14% and the lowest RMSE value of 0.01775. The combination of parameters used in this study also has an impact on the final MAPE and RMSE results, especially with the use of learning rates of 0.001 and 0.0001. Thus, it can be concluded in this study that the GRU method is more accurate and effective compared to the LSTM method in predicting stock prices.
Implementasi Algoritma Rabin-Karp dalam Pendeteksian Plagiarisme pada Dokumen Makalah Mahasiswa Zidan, Muhammad Rohyan; Setiawan, Kiki
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 1 (2025): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v6i1.1191

Abstract

Term papers are scholarly works prepared by students as part of their assessment in the educational process according to their academic level. Concerns about the increasing incidence of plagiarism in academic documents are becoming more significant. To assess the extent of plagiarism in a document, the use of a plagiarism detection system based on the Rabin-Karp algorithm is essential. This algorithm is employed to compare the similarities between a PDF document and existing sources, helping to identify patterns resembling the original references. This plagiarism detection system provides relevant data to measure the originality of a work and determine the necessary preventive or corrective actions. The data collection methods applied include literature review and interviews, while the system development follows the prototyping approach, which features clear, structured, and practical stages.
Deteksi Kerusakan Jalan Berdasarkan Citra Digital Menggunakan Convolutional Neural Network (CNN) Mulyana, Dadang Iskandar; Wahyudi, Ilham
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 1 (2025): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v6i1.1192

Abstract

Highways are a connection between an area or region to another destination. The rapid construction of highways in big cities is not comparable to the improvement and rearrangement of damaged roads in several areas. Most of the damaged roads are caused by heavy vehicle traffic or heavy loads with quite frequent intensity, as well as natural disasters such as floods and earthquakes. This of course disrupts the traffic system, and is quite dangerous for drivers who often pass through areas where there are many damaged roads. With these obstacles, this study aims to build a system that can detect road damage through digital image capture using the convolutional neural network method. The results of this study obtained a road damage detection accuracy value reaching 80%.
Klasifikasi Absensi Face Geo-Location Menggunakan Metode CNN pada PT Indomarco Prismatama Mulyana, Dadang Iskandar; Aribatullah
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 1 (2025): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v6i1.1193

Abstract

The rapid development of information technology forces companies to continue to improve operational efficiency, including in managing employee attendance. An accurate and efficient attendance system is essential to monitor employee attendance and ensure operational effectiveness. However, traditional attendance using fingerprints still has weaknesses, such as the potential for data manipulation through NIK input without physical presence. This study aims to develop a facial recognition-based attendance system using the Convolutional Neural Network (CNN) method that can ensure employee attendance in real-time. This technology is expected to improve the accuracy and reliability of the attendance system, as well as reduce the potential for fraud. The implementation of this system at PT Indomarco Prismatama, known as the Indomaret retail network, aims to simplify the attendance process for field employees and make it easier for management to monitor employee attendance in various locations.
Implementasi Sistem Penerjemahan Bahasa Isyarat dengan Metode Pengenalan Ucapan Mulyana, Dadang Iskandar; Septiani, Novi
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 1 (2025): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v6i1.1194

Abstract

The rapid development of technology certainly brings many benefits to the surrounding environment, several factors are helped by the advancement of technological tools, especially to help people with disabilities, currently people with disabilities, especially the mute, often have difficulty communicating, several factors affect the limited understanding of people with disabilities with the surrounding community, for example, the limited hearing of people with mute. With this background, a tool is needed that is able to translate Indonesian into sign language so that it can help people with disabilities and the community in communicating and living in society. This study uses the speech recognition method in its application, the results of the study reached an accuracy value of 80%.
Penerapan Metode Requirement Engineering dalam Pengembangan Website E-Commerce sebagai Media Promosi dan Pemasaran pada Kelompok UMKM Tenun Ikat Meylano, Nunsio Handrian; Woda, Yanter Wilve Baly; Mukin, Dimas Pangestu; Pereira, Frederico Lino; Theresia, Destiana Evarista
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 1 (2025): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v6i1.1195

Abstract

The utilization of digital marketing platforms, particularly E-Commerce, aims to support SMEs in engaging directly with consumers online, increasing sales conversion rates, reducing marketing costs, providing real-time customer service, and enhancing product competitiveness. E-Commerce enables businesses to reach broader markets without geographical limitations, whether locally, nationally, or internationally. Adopting this technology is a strategic step for business sustainability, as enterprises that do not leverage E-Commerce risk losing their competitive edge. Economic developments driven by technological innovation have significantly influenced business strategies, including those of the Tenun Ikat Mbola So SME group. Through the implementation of an E-Commerce application as a digital marketing platform, this SME can expand its market reach, reduce reliance on traditional marketing methods, and optimize marketing and promotional cost efficiency.
Analisis Kepuasan Pengguna dalam Penerapan E-Procurement pada Divisi Supply Chain Management PT ASDP Indonesia Ferry (Persero) Kantor Pusat Annadiyanti, Annisa Agni; Andrian, Rian
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 1 (2025): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v6i1.1196

Abstract

This study aims to analyze the level of user satisfaction in the use of the E-Procurement system in the Supply Chain Management Division of PT. ASDP Indonesia Ferry (Persero) Head Office. The method used is quantitative with the Partial Least Squares-Structural Equation Modeling (PLS-SEM) approach using SmartPLS 3.2.9 software. This approach is used to measure the relationship between latent variables that affect satisfaction, effectiveness, transparency, and accuracy of the E-Procurement system. The study population involved 30 people in the Supply Chain Management Division of the Head Office, with data collected through an online questionnaire using Google Form. The results showed that the use of E-Procurement can significantly reduce procurement costs and time, with a T-statistic value of 5.558 (> 1.96) and P < 0.05. However, this system does not increase transparency because its effect is not significant with a T-statistic value of 0.069 (<1.96). In addition, the implementation of E-Procurement also did not improve the accuracy of the procurement process, as indicated by the T-statistic value of 0.035 (<1.96). The main obstacles to implementation include limited user understanding, inadequate instructions, and poor data quality. This study concludes that although E-Procurement has the potential to improve efficiency, additional efforts such as intensive training, regulatory improvements, and better data management are needed to support its overall success.
Implementasi Algoritma Convolutional Neural Network dalam Menentukan Kelayakan Kayu Putra, Rafino Ramdhaniar Prasetyo; Fachrie, Muhammad
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 1 (2025): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v6i1.1198

Abstract

Wood eligibility is the most important factor in the furniture industry. However, currently there are still many producers who ignore the feasibility of wood so that it can affect production results and selling prices. With the development of technology such as digital image processing, the process of selecting feasible wood can be done without the need for human visuals. This research proposes to classify wood eligibility based on digital images of wood eligibility using the Deep Leraning method. Convolutional Neural Network (CNN) which is one type of Deep Learning algorithm is proposed as a method to analyze wood worthiness images. The dataset of wood worthiness images was obtained through observations made by researchers at CV Kanindotama. The dataset used in this study amounted to 105 wood images divided into 83 training data and 22 test data. The model built using the ResNet50V2 architecture gets the greatest accuracy of only 69.51% for training data and 62.5% for test data. While the model built using the MobileNetV2 architecture gets an accuracy of up to 98.29% for training data and 100% for test data. This proves that the MobileNetV2 architecture is better than ResNet50V2. In addition, it can be said that the CNN algorithm can be used to analyze the feasibility of wood well.
Analisis Sentimen terhadap RSUD Salatiga Menggunakan SVM dan TF-IDF Azzahra, Windy Livia; Mailoa, Evangs
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 1 (2025): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v6i1.1208

Abstract

The Salatiga Regional General Hospital (RSUD) plays an important role in providing healthcare services. This research analyzes public sentiment towards RSUD Salatiga using the SVM method with a linear kernel for sentiment analysis and TF-IDF for feature extraction. The dataset consists of 414 processed reviews, including case folding, data cleaning, tokenization, normalization, stopword removal, and stemming. Evaluation shows that the model achieved an accuracy of 84.00%; precision of 84.00%; recall of 83.25%; and an F1-score of 83.53%. A total of 55.8% of reviews indicated positive sentiment and 44.2% negative sentiment, highlighting the need for improvements in the queue system, waiting times, and parking facilities. The SVM and TF-IDF methods were chosen for their ability to handle large text data with high accuracy. This research provides practical contributions in the form of recommendations such as the implementation of a technology-based queue system. Limitations include the limited amount of data and platform bias, so exploring other algorithms, such as Naive Bayes and Random Forest, is recommended.
Perancangan Sistem Informasi Akuntansi Web untuk Agen Properti dengan Metodologi Scrum Ardiansyah, Muhammad; Phang, Raymond
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 1 (2025): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v6i1.1209

Abstract

This research aims to design and develop a web-based accounting information system for real estate agency companies using the Scrum methodology. The system is specifically tailored to address the unique needs of the real estate industry, such as managing sales transactions, calculating agent commissions, client communication, property activity reporting, and structured financial reporting. The Scrum methodology, employed during the development process, offers high flexibility and adaptability, enabling developers to quickly and effectively respond to user feedback. By utilizing technologies like PHP, MySQL, HTML, and CSS, the system development process is accelerated, structured, and maintainable. The system is designed to enhance efficiency, transparency, and accuracy in managing property transaction data, enabling management to access real-time activity reports, effectively organize properties, and transparently evaluate sales transactions. The results demonstrate that the system significantly improves the productivity of real estate companies, enhances financial reporting transparency, and supports better data-driven decision-making. Through this system, business processes become more integrated, fostering more productive team collaboration and increasing the company's competitiveness within the real estate industry. Additionally, the system includes an audit trail feature that ensures data accuracy and simplifies both internal and external audit processes. This adds value by building trust among users, including internal management and external stakeholders such as investors or regulators. By combining modern technologies and the Scrum methodology, this study aims to serve as a significant reference for similar system development initiatives within the real estate sector and beyond.

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