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All Journal TEKNIK INFORMATIKA TELKOMNIKA (Telecommunication Computing Electronics and Control) Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Transformasi: Jurnal Pengabdian Masyarakat Sistemasi: Jurnal Sistem Informasi Indonesian Journal of Information System JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) Jurnal Sisfokom (Sistem Informasi dan Komputer) SEIKO : Journal of Management & Business Jiko (Jurnal Informatika dan komputer) JURIKOM (Jurnal Riset Komputer) YUME : Journal of Management Journal of Humanities and Social Studies JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Media Informatika JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Management and Bussines (JOMB) Journal of Education Research Universitas Muhammadiyah Yogyakarta Undergraduate Conference Proceeding Blend Sains Jurnal Teknik eProceedings of Engineering Eduvest - Journal of Universal Studies Jurnal Hukum Caraka Justitia Electronic Integrated Computer Algorithm Journal JER AQILA : Acceleration, Quantum, Information Technology and Algorithm Journal Journal of Production, Enterprise, and Industrial Applications Proceeding of Community Service and Engagement JRTI (Jurnal Riset Tindakan Indonesia)
Lukman Abdurrahman
Universitas Telkom
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Neuroscience Public Health Social Sciences Other

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Innovation in Information Technology: A Hybrid Systematic Literature Review and Bibliometric Analysis Faezal Erlangga; Lukman Abdurrahman
Jurnal Economic Resource Vol. 9 No. 1 (2026): October - March
Publisher : Fakultas Ekonomi & Bisnis Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57178/jer.v9i1.2137

Abstract

This study aims to provide an overview of the development and scope of research on Innovation in Information Technology through a hybrid approach combining Systematic Literature Review and bibliometric analysis. The study examines 121 articles selected from the Scopus database using the PRISMA 2020 framework. A bibliometric analysis was conducted using VOSviewer to identify publication trends, research distribution, and relationships among key keywords. The results indicate that research on Innovation in Information Technology remains relatively limited and is dominated by developed countries, with a primary focus on technological aspects and organizational contexts. These findings offer both theoretical and practical implications for advancing research and formulating sustainable information technology innovation strategies in the future.
The role of information systems in the digital transformation of palm oil plantations: a systematic literature review Muhammad Fitrah Sulthon; Lukman Abdurrahman
JRTI (Jurnal Riset Tindakan Indonesia) Vol. 10 No. 4 (2025): JRTI (Jurnal Riset Tindakan Indonesia)
Publisher : IICET (Indonesian Institute for Counseling, Education and Therapy)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/30036575000

Abstract

This study examined the role of information systems in supporting digital transformation in oil palm plantations using a systematic literature review (SLR). Despite the increasing adoption of digital technologies, the strategic integration of information systems in plantation management remains limited. The review was conducted by searching three major scientific databases Scopus, Web of Science, and Google Scholar for articles published between 2020 and 2025. A total of 127 articles were initially identified, of which nine studies were selected based on predefined inclusion and exclusion criteria, including relevance to oil palm plantations, focus on information systems, and methodological rigor. The quality of the selected articles was assessed using a structured evaluation framework to ensure reliability. The results showed that 89% of the reviewed studies reported significant improvements in operational efficiency and data accuracy, while 78% highlighted enhanced decision-making supported by information systems. Web-based and integrated systems were the most commonly implemented technologies, appearing in 67% of the studies, particularly for data integration, monitoring, and reporting. However, 56% of the studies identified human resource limitations and 44% reported system integration issues and organizational resistance as major barriers. The study concluded that information systems serve not only as operational tools but also as strategic enablers of sustainable digital transformation in oil palm plantations, emphasizing the need for integrated systems and strong organizational support.
Analisis Algoritma Wave Function Collapse sebagai Metode Prosedural Generator untuk Pembuatan Medan Permainan Digital Farhan Febryan; Lukman Abdurrahman
Blend Sains Jurnal Teknik Vol. 4 No. 4 (2026): Edisi April
Publisher : Ilmu Bersama Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56211/blendsains.v4i4.1405

Abstract

Pengembangan aplikasi permainan dimaksudkan untuk menghibur dan memberikan edukasi kepada para pemain dan penggunanya, tetapi tahap pembuatan aplikasi permainan tidak mudah dan cenderung rumit, biaya yang besar serta waktu yang banyak sangat dibutuhkan dalam pembuatan aplikasi permainan, ini sering sekali menjadi kendala utama dalam pembuatan aplikasi permainan hingga menyebabkan penundaan dalam pengembangan aplikasi permainan. Konesep dari algoritma Wave Function Collapse dibuat untuk memangkas biaya dan waktu dalam pengembangan aplikasi permainan, algoritma ini merupakan algoritma Content Generator yang dimaksudkan sebagai alat bantu untuk membuat atau menciptakan suatu konten yang dibutuhkan didalam aplikasi permainan secara procedural, baik itu level, desain, bahkan item dan objek game itu sendiri. Setelah penelitian dilakukan, didapati bahwa algoritma ini cocok untuk membangun dunia yang tidak terlalu besar, dalam kata lain setidaknya dalam cakupan 50 x 50 grid, jika dilakukan dengan lebih, maka akan memakan waktu serta membutuhkan memori yang besar.
Sentiment Analysis of Fintech Application Users in Indonesia Using Machine Learning Algorithms Made Marshall Vira Deva; Lukman Abdurrahman; Hanif Fakhrurroja
Acceleration, Quantum, Information Technology and Algorithm Journal Vol. 3 No. 1 (2026): VOLUME 3, NO 1: JUNE 2026
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/aqila.v3i1.171

Abstract

This study focuses on Indonesian users' sentiments regarding 9 fintech apps based on their Google Play Store reviews. The rapid growth of the fintech industry in Indonesia makes it crucial to understand user perceptions and satisfaction. Around 2,554 reviews from users of Kredivo, ShopeePay, Dana, GoPay, LinkAja, Bareksa, Flip, Jenius, and OVO were analyzed. The user review text and data were preprocessed using text cleaning, slang normalization, stopword removal, stemming, and the Sastrawi library and were moved through the TF-IDF vectorizer (term frequency-inverse document frequency). The four algorithms were Naive Bayes, Logistic Regression, Support Vector Machine (SVM), and Random Forest. The results showed that SVM (Linear) achieved the best overall balanced performance with an accuracy of 80.23%, precision of 77.79%, recall of 80.23%, and the highest F1-score of 78.53%, outperforming Naive Bayes (accuracy 81.21%, F1-score 78.32%), Logistic Regression (accuracy 80.43%, F1-score 77.81%), and Random Forest (accuracy 78.08%, F1-score 75.81%). While Naive Bayes recorded the highest raw accuracy, SVM was selected as the best model due to its superior F1-score, which provides a more balanced evaluation across all sentiment classes. Machine learning provided a snapshot of the reviews’ sentiments, with 42.4% positive, 51.4% negative, and 6.1% neutral. Kredivo and ShopeePay had the most favorable sentiments of 72.4% and 70.9%. The most salient sentiment indicators include 'bagus' (good) and 'bantu' (help) as top positive classifiers, while 'buruk' (bad) and 'kecewa' (disappointed) emerged as the most prominent negative classifiers, with 'mudah' (easy) and 'cepat' (fast) also strongly associated with positive sentiment. The results of this study give fintech firms a better grasp of user satisfaction, and fintech user positive sentiments.
Optimizing Information Technology Investment Using the Total Cost of Ownership (TCO) Approach: A Case Study of a Property Company Tania Ayu Sekar Arum; Lukman Abdurrahman
Eduvest - Journal of Universal Studies Vol. 6 No. 6 (2026): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v6i6.52965

Abstract

Information technology (IT) investment has become an essential component for improving operational efficiency, service quality, and business competitiveness in the property industry. However, many companies still focus only on initial acquisition costs without considering the overall expenses incurred throughout the lifecycle of IT assets. This study aims to evaluate and optimize IT investment at Ray White CBD Bandung using the Total Cost of Ownership (TCO) approach. The research employed a quantitative descriptive method using primary and secondary data collected through interviews, observation, and document analysis. The TCO approach was used to identify and calculate all IT-related costs, including acquisition, maintenance, support, and training costs during the 2022–2024 period. The findings reveal that software costs represented the largest component of IT investment, followed by equipment maintenance, printer assets, and employee training. The study also identified several hidden costs, such as downtime, vendor dependency, and troubleshooting time, which significantly influenced operational efficiency and financial performance. The implementation of the TCO approach helped the company understand the real cost structure of IT ownership and improve budget planning. In conclusion, the TCO approach provides a comprehensive framework for making strategic, sustainable, and cost-effective IT investment decisions in property companies.
Evaluation And Analysis Of Application Of The Scrum Method To Increase The Success Of Go-Live Phase In Sap Analytics Cloud Dashboard Implementation Projects (Case Study Of Mining Owner & Mining Contractor Industry) Sabil Nararya; Lukman Abdurrahman; Basuki Rahmad
JHSS (JOURNAL OF HUMANITIES AND SOCIAL STUDIES) Vol 9, No 2 (2025): Journal of Humanities and Social Studies
Publisher : UNIVERSITAS PAKUAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/jhss.v9i2.11661

Abstract

To evaluate the company's business development carried out by the Board of Directors, an ERP dashboard system is needed that can provide information on business development in real time. So it takes the implementation of the SAP Analytics Cloud Dashboard system. However, company stakeholders engaged in the mining owner and mining contractor sector want the project to be monitored in every process. So that if there are errors or changes in the process of making a report on the dashboard, then this can be known earlier and changed as needed. Seeing the conditions of this need, a company engaged in consulting as a solution management service provider that initially proposed using the ASAP method, otherwise known as Accelerated SAP, is proposing to change the project method to the scrum method in the SAP Analytics Cloud implementation project in companies engaged in the mining owner and mining contractor industry. This research was conducted with the limitations and objectives to evaluate and analyze the effect of the application of the scrum method on the SAP Analytics Cloud Dashboard implementation project in increasing the success of the go-live phase of the project.
Bank Mandiri Stock Performance Prediction Via SVM, LSTM, and Random Forest Rahmat Rambe; Hanif Fakhrurroja; Lukman Abdurrahman
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 15 No. 2 (2026): MAY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v15i02.2589

Abstract

Reliable stock price prediction is critical for effective investment decisions; however, high volatility and nonlinear dynamics continue to challenge forecasting accuracy. Despite the extensive use of machine learning in financial research, short-term comparative studies on Indonesian banking stocks remain scarce. This study evaluates the performance of Support Vector Machine (SVM), Long Short-Term Memory (LSTM), and Random Forest models in predicting Bank Mandiri’s stock prices using daily data from Yahoo Finance covering June to December 2024. The data, including price indicators and trading volume, were normalized, transformed into time-series sequences, and divided into training and testing sets. SVM was applied for directional classification, while LSTM and Random Forest were used for regression-based price prediction. Model performance was assessed using accuracy and mean squared error (MSE). The findings show that LSTM achieves the lowest prediction error (MSE = 0.0045), indicating superior ability to model temporal and nonlinear price patterns. In contrast, Random Forest records the highest classification accuracy (0.9932), demonstrating strong performance in predicting price direction. Overall, LSTM is most effective for short-term price forecasting under volatile market conditions, whereas Random Forest remains a robust option for directional classification.
Information technology value engineering through partial adjustment valuation theory Lukman Abdurrahman; Candiwan Candiwan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 1: February 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i1.27478

Abstract

The paper proposes a systems management approach that utilizes information technology (IT) treatment as a framework to help firms enhance future performance by optimising key parameters. The method certifies a valuation approach that enables businesses to better manage their IT infrastructure and improve performance. A case study of A case study of PT Telekomunikasi Indonesia (Telkom) and PT XL Axiata (XL) (2004–2018) shows the method’s effectiveness. Once the IT value is identified, specific parameters can be engineered to improve performance without changing other variables. The approach uses a partial adjustment valuation model, enabling performance gains at lower costs. The results show significant improvements in both firms’ performance values and ratios compared to their originals. This supports adopting a cost leadership strategy, making IT based businesses more efficient, cost-effective, and better performing across financial, business, and strategic dimensions.
FinBERT-Based Sentiment Integration in Hybrid CNN– BiLSTM Models For Stock Price Forecasting Mohammad Tyas Pawitra; Lukman Abdurrahman; Hanif Fakhrurroja
JURNAL TEKNIK INFORMATIKA Vol. 19 No. 1: 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.v19i1.49466

Abstract

This study investigates sentiment-aware deep learning models for short-term stock price forecasting using NVIDIA (NVDA) as a representative high-volatility technology stock. Four architectures—CNN, LSTM, BiLSTM, and a hybrid CNN–BiLSTM—are evaluated under two configurations: without sentiment and with FinBERT-based financial news sentiment integrated as a continuous contextual feature. Historical OHLV data are combined with sentiment information to enable multimodal learning under a controlled experimental setting. The results demonstrate that recurrent architectures consistently outperform convolution-only models, highlighting the importance of temporal dependency modeling in financial time series. Among all configurations, the hybrid CNN–BiLSTM with FinBERT sentiment achieves the best overall performance, yielding the highest R², the lowest MAE and RMSE, and the smallest overfitting gap. Bootstrap-based confidence intervals indicate stable generalization, while Wilcoxon signed-rank tests confirm that the observed performance improvements are statistically significant. The study also presents a near real-time deployment framework with low inference latency, demonstrating practical applicability for decision-support systems. Overall, the findings show that effective alignment between local feature extraction, bidirectional temporal modeling, and contextual sentiment integration is critical for improving stock price.  forecasting accuracy and robustness.
Evaluasi Implementasi Rencana Induk Kota Cerdas di Pemerintah Kota Indonesia melalui SLR Rahmat Rambe; Lukman Abdurrahman
Journal of Education Research Vol. 7 No. 1 (2026)
Publisher : Perkumpulan Pengelola Jurnal PAUD Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37985/jer.v7i1.3001

Abstract

Keberhasilan program smart city di Indonesia sangat bergantung pada master plan yang mengintegrasikan kemajuan teknologi dengan tujuan tata ruang. Namun, penyelarasan antara master plan smart city dan perencanaan spasial masih menjadi tantangan karena perbedaan interpretasi antar daerah. Penelitian ini menggunakan metode Systematic Literature Review (SLR) untuk mengevaluasi implementasi master plan smart city di kota-kota Indonesia. Hasilnya menunjukkan berbagai hambatan, seperti komunikasi yang lemah, keterbatasan sumber daya, komitmen rendah dari pelaksana, dan keterlambatan birokrasi. Kota seperti Jakarta, Bandung, dan Surabaya menghadapi kendala infrastruktur, regulasi yang tidak konsisten, serta keterbatasan dana dan kesadaran publik. Studi ini memberikan rekomendasi seperti peningkatan infrastruktur TIK, kolaborasi pemangku kepentingan, dan penyelarasan rencana induk dengan kerangka pembangunan spasial guna mendorong pertumbuhan kota yang berkelanjutan dan inklusif.
Co-Authors Abdulmana, Sahidan Adinda Laras Ayu Alqahtani, Raied Ali Anindya Tyas Wulandari Ardhana, Sonia Frisca Putri Ari Fajar Santoso Ayta Boangmanalu Ayu, Adinda Laras Azzahra, Nilam Eria Basuki Rahmad Bremana , Rhiko Candido , Wan Liufang Bagus Candiwan Deden Witarsyah Dinda Sekar Cendani Djusnimar Zultilisna Doloksaribu, Lastri M. A Endang Chumaidiyah Erlangga, Faezal Estiningtyas, Elysia Faezal Erlangga Fakhrurroja, Hanif Farhan Febryan Fasya, Muhammad Haikal Fauzi, Rokhman Firdaus, Fitri Adini Fitrah Sulthon, Muhammad Fredella, Anisah Fritasya Dwiputri Suryoputro Garcia-Constantino, Matias Ghina Khaerunnisa Ikhlas Fuad Zamzami Ikhsan , Alif Muhammad Iqbal Santosa Iqbal Santoso Iqbal Yulizar Mukti Karina Tarigan Kinanti Andaiary Kresnaufal Nur Fadhillah Luthfi Ramadani Made Marshall Vira Deva Matias Garcia-Constantino Moch Arif Bijaksana Mohammad Tyas Pawitra Muhamad Daffa Rial Muhammad Fadhly Arham Muhammad Faza Zharfan Muhammad Fitrah Sulthon Muhammad Haikal Fasya Muharman Lubis Mutiara Natiqoh Purwanto Nadiya Mardiyanti Nandika, Luthfi Rahmansyah Naufal M. Fadilah Nazmi Robbiyani Ningrum, Devi Permata Nurhakim, Maiziah Azka Nurul Afifah Possumah, Mercy Kristina Pradana, Vega Putra Raden Ichsan Achmad Falach Rafian Ramadhani Rahmat Mulyana Rahmat Rambe Rahmat Rambe Raied Ali Alqahtani Ramadhan, Muhammad Firly Ramadhani, Rafian Rio Savero Aranov Risky, Surya Achmad Rismadewi, Kessya Azzahra Riyadi, Muhammad Affan Rizka Putri Wahyuni Rohmat, Mila Ruri Fadhilah Ryan Adhitya Anugrah Ryan Adhitya Nugraha Sabil Nararya Safitra, Muhammad Fakhrul Sahidan Abdulmana Sandy, Muhammad Dwi Hary Sinandhi, Raihan Achmad Sinta Aryani Tampubolon, Claery Jessica Tania Ayu Sekar Arum Tania Nielsany Simbolon Taufik Safar Hidayat Tegar Kurnia Fajar Titisari Ramadhane Trias Zulfa Nurafifah Trigama, Ginna Vega Putra Pradana Wiwin Aminah Yudistira, Muhammad Kevin Yuli Adam Prasetyo Zamzami, Ikhlas Fuad