Maria Ulfah Siregar is a lecturer in the Informatics Department, Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta, Indonesia. She received her bachelor's degree from Institut Teknologi Sepuluh November (ITS) Surabaya, Indonesia, majoring in Informatics in 2002. Then, she obtained her master's degree from Universiti Kebangsaan Malaysia (UKM), majoring in Computer Science in 2007. Next, she got a doctoral degree in Computer Science in 2017 from the University of Sheffield. You can contact me via email at: .
EDUCATION
Bachelor's degree from Institut Teknologi Sepuluh November (ITS) Surabaya, Indonesia, majoring in Informatics in 2002.
Master's degree from Universiti Kebangsaan Malaysia (UKM), majoring in Computer Science in 2007.
Doctoral degree in Computer Science in 2017 from the University of Sheffield.
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Science, Artificial Intelligence, Computational Theory and Mathematics
14
Scopus Publications
277
Scholar Citations
10
Scholar h-index
10
Scholar i10-index
Scopus Publications
Vehicle Routing Problem: A Performance Comparison of Hybrid Evolutionary Algorithm with Local Search Strategies Maria Ulfah Siregar, Thoriq Firdaus Arifin, Muhammad Javier Badruttamam, Maulida Suryaning Aisha, Ibnu Raju Humam, et al. Jurnal Online Informatika, 2026 The Vehicle Routing Problem (VRP), one of the most challenging problems in logistics and transport, has been an area of optimization solutions to minimize costs and optimize the operational process. This study examines a hybrid of metaheuristic algorithms that are combinations of the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), and Local Search (LS) to tackle various complexities of VRP. The hybrid approach offered better exploration and exploitation by integrating global explorations with GA and PSO and local refinement with SA and LS. The performance was performed using real datasets and generated randomly with problem sizes ranging from 9 to 100 customers. PSO-LS and GA-LS are LS-based hybrids that produce lower standard deviations, showing a stable and consistent result for small to medium problems. For example, PSO-LS computed 3.31 for 9 customers and 5.76 for 50 customers. However, SA-based hybrids, such as PSO-SA and GA-SA, presented more variability, with SA-GA reaching 100 customers as much as 7.83. These findings highlight key trade-offs while optimizing VRP between stability, efficiency, and problem scale.
A Systematic Literature Review and Bibliometric Analysis of Software Tampering: Trends and Safeguards Fadila Amanda, Maria Ulfah Siregar, Bambang Sugiantoro, Agung Fatwanto, Mhd. Reza MI Pulungan, Zarina Shukur International Journal on Informatics Visualization, 2026 Software tampering severely compromises software security. This malicious activity involves manipulating or modifying computer software for unauthorized gains. This study examines trends in software tampering research using a Systematic Literature Review (SLR) and bibliometric analysis. Applying the PRISMA method yielded 112 relevant studies. Bibliometric analysis using co-authorship and co-occurrence analysis in VOSviewer identified key patterns. SLR identified 56 studies for content analysis. This study's key findings are collaborative research, in which 13 authors demonstrated interconnected work; keyword analysis, in which 56 relevant keywords emerged; geographical leadership, in which the United States led publications in 2019 (8 studies); and prevention methods, in which 40 techniques were identified. Limitations include limited author collaboration, inadequate security measures, and detection-focused methods that do not guarantee absolute security. Future research directions include proactive prevention methods, the encouragement of interdisciplinary collaboration, and enhanced security measures. Implications for practice and policy inform software development security standards, guide cybersecurity investments, and support evidence-based decision-making. This study provides valuable insights for researchers, practitioners, and policymakers. It highlights the need for collaborative research, enhanced security measures, and innovative prevention strategies. Understanding software tampering trends and challenges enables effective countermeasures. Stakeholders can enhance software security and mitigate threats by addressing these gaps. Furthermore, this research underscores the importance of integrating software tampering prevention into the software development lifecycle. By prioritizing security, developers can minimize vulnerabilities and protect users. This study provides a foundation for addressing software tampering threats and for advancing research and practice in this area.
A Better Performance of GAN Fake Face Image Detection Using Error Level Analysis-CNN Maria Ulfah Siregar, Nurochman Nurochman, Anif Hanifa Setianingrum, Dwi Larasati, William Santoso, Meisia Dhea Stefany International Journal on Informatics Visualization, 2025 The use of face images has been widely established in various fields, including security, finance, education, social security, and others. Meanwhile, modern scientific and technological advances make it easier for individuals to manipulate images, including those of faces. In one of these advancements, the Generative Adversarial Network method creates a fake image similar to the real one. An error-level analysis algorithm and a convolutional neural network are proposed to detect manipulated images generated by generative adversarial networks. There are two scenarios: a stand-alone convolutional neural network and a combination of error-level analysis and a convolutional neural network. Furthermore, the combined scenario has three sub-scenarios regarding the compression levels of the error-level analysis algorithm: 10%, 50%, and 90%. After training the data obtained from a public source, it becomes evident that using a convolutional neural network combined with compression of error level analysis can improve the model’s overall performance: accuracy, precision, recall, and other parameters. Based on the evaluation results, it was found that the highest quality convolutional neural network training was obtained when using 50% error level analysis compression because it could achieve 94% accuracy, 93.3% precision, 94.9% recall, 94.1% F1 Score, 98.7% ROC-AUC Score, and 98.8% AP Score. This research is expected to be a reference for implementing image detection processes between real and fake images from generative adversarial networks.
Comparison of Classification Algorithm and Language Model in Accounting Financial Transaction Record: A Natural Language Processing Approach Bagas Adi Makayasa, Maria Ulfah Siregar, Agung Fatwanto, Bambang Sugiantoro International Journal on Advanced Science Engineering and Information Technology, 2024 The problem of financial recording not following the principles of accounting science has the potential to cause unnecessary problems. However, micro, small, and medium enterprises with their distinctive characteristics, though not all, still face many obstacles in writing financial reports. Even though there is already much financial software available, our study aims to investigate opportunities for implementing automation of accounting financial transaction records using the NLP approach, to interpret financial transactions based on text written on the transaction form into accounting journals (debits and credits). Experiments were carried out by comparing the performance of three classification algorithms, namely SVM, K-Nearest Neighbor, and Random Forest, with traditional (TF-IDF and BOW) and contextual (Word2Vec) Language Models. There are 200 financial transaction datasets consisting of ten classes. The data is divided into two parts, namely, the balance dataset and the imbalance dataset. The pair SVM and Word2Vec in the balanced dataset gave the highest accuracy (92.5%), precision (92.5%), recall/sensitivity (93.33%), and F1 score (92%). However, compared with the results of related semantic research (the average performance reaches 95%), the results obtained in this study are still lower. One point that may have a significant effect is the amount of data in the corpus, which is still lacking. Researchers suggest increasing the number of datasets and using a combination of other language models such as Glove, Bert etc. This study can also be used as a model for more complex financial transaction cases in future research.
Automated SPARQL Template for Flexible Question Answering Dewi Wardani, Andreas Wijaya, Ardhi Wijayanto, Maria Ulfah Siregar, Yessi Yunitasari International Journal on Advanced Science Engineering and Information Technology, 2024 The knowledge bases required the query language SPARQL, which consists of subject, property, and object. SPARQL is a structured query language and is difficult to understand. That issue becomes a problem in natural language processing queries. One situation in question answering is how to translate natural language into a structural SPARQL. This work aims to develop an automated SPARQL template algorithm regardless of the pattern structure of the query triples. It provides a more varied SPARQL query for data retrieval named Flexible SPARQL. This approach initially lies in combining elements of RDF with basic techniques of natural language processing to generate a template of SPARQL. In this work, the approach to making automatic templates is proposed without regard to the pattern of the triple structure or the location of the subject and object. Template-based research that exists today still uses rules to determine the position of subjects, objects, and properties in the SPARQL structure. Therefore, this work used the QALD 7 question set and DBpedia dataset. The previous systems utilized the same questions and data sets. Despite the simple proposed approaches that do not use complex, sophisticated techniques, they have shown promising results compared to the previous systems. The accuracy result from 215 questions is 73% and micro-Recall 0.701, micro-Precision 0.664, micro-F-Measure 0.682, macro-Recall 0.711, macro-Precision 0.592, macro-F-Measure 0.646. Overall, the Flexible SPARQL system has higher results on several measurements that define a promising approach. However, it's important to note that Flexible SPARQL generally tends to fail at generating complex SPARQL, which is a limitation of the system.
The effects of artificial intelligence on the Kenyan society Rebeccah Ndungi, Maria Ulfah Siregar Indonesian Journal of Electrical Engineering and Computer Science, 2023 <span lang="EN-US">Artificial intelligence technology (AI) is an array of computer technologies that provide machines with human-like abilities in perception, action, and cognition. It can mimic human intellect in a broad variety of situations thanks to its advanced processing of information and mega-thinking procedures and powers. AI's power to mimic the intellect of humans means it will disrupt or significantly affect practically every major industry, including but not limited to manufacturing, healthcare, agriculture, and logistics. AI helps several industries move forward. Developed Western nations and leading digital titans like Google and Facebook have invested significantly in AI, utilizing its human skills in various vital societal sectors. Regrettably, most poor countries, particularly those in the sub-Saharan African region, do not have the necessary administration, learning, data reserves, and legislation to support the adoption and implementation of AI. Nevertheless, certain countries in sub-Saharan Africa, such as Kenya, have incorporated and used AI technologies in several key areas for the benefit of their inhabitants. This article explores how AI has affected Kenya and demonstrates how other sub-Saharan African countries might use AI-related technology to their full potential.</span>
The Formal Graph of APRDF Dewi Wardani, Maria Ulfah Siregar, Ardhi Wijayanto, Yessi Yunitasari International Journal on Advanced Science Engineering and Information Technology, 2023 A new alternative model for expressing more complex knowledge has been proposed as an attributed predicate RDF (APRDF). By handling attributes that represent any additional triples of the main triple, APRDF serves as a predicate. Therefore, the formal graph model of APRDF must be defined. Lastly, this work recommends that the APRDF's conventional diagram is a digraph-hypergraph mix. The previous formal graph of RDF is a hypergraph even though, visually intuitively, it is a digraph. It also contains inconsistency. The other new serialization needs to describe its formal model. Eventually, this work can provide the formal graph model of APRDF and maintain consistency. There have been a few definitions proposed. The direct impact of this formal model is that APRDF outperformed the other model significantly when retrieving complex queries within its formal graph. In querying, the initial implementation of the proposed formal graph takes an average of 62 milliseconds. Compared to the other graph models, the proposed formal graph can reduce query time by an average of 90,7 milliseconds on the BF-arch graph and 121,05 milliseconds on the naive/default graph. As the formal graph model is preserved, the attributed predicate of APRDF assumed will drive a new model in the retrieving process that more in using a predicate formed as a link in a graph. It will also be impacted in the mining process by more elaborate links/edges (link mining).
Formalizing Attack Tree on Security Object for MySANi in Legal Metrology Muhammad Azwan Ibrahim, Faizan Qamar, Zarina Shukur, Nasharuddin Zainal, Nazri Marzuki, Maria Ulfah Siregar Systems, 2023 Illegal software manipulation is one of the biggest issues in software security. This includes the legally relevant software which are now crucial modules in weight and measuring instruments such as weighbridges. Despite the advancement and complexity of weight and measuring instruments, the inspection methodology is weak and lacks of innovation. The conventional inspection method is merely based on the observation printed certificate of the software. This paper introduces Malaysia Software-Assisted Non-Automatic Weighing Instrument (NAWI) Inspection (MySANI), a method used to enhance the software inspection scheme in legal metrology. MySANI introduces security objects in order to assist and enhance the inspection process. The security evaluation is based on the best practices in IT in metrology, where the attack model on relevant assets of the security objects is simulated for the Attack Probability Tree. The attack tree is verified by integrating formal notation and comparison with finite state transition system domain to verify the correctness properties of the tree design before the model can be further used in a risk analysis procedure within the Attack Probability Tree framework. Results show that the designed attack tree is consistent with the designed simulation.
Housing Price Prediction Using a Hybrid Genetic Algorithm with Extreme Gradient Boosting Maria Ulfah Siregar, Pahlevi Wahyu Hardjita, Farhan Armawan Asdin, Dewi Wardani, Ardhi Wijayanto, Yessi Yunitasari, Muhammad Anshari ACM International Conference Proceeding Series, 2022 Predicting property prices provides a better service for customers to evaluate and estimate price movement before their purchases. Some features including OverallQual and GrLivArea, which were selected when applying GA, become important features that can influence property prices. This research proposes a hybrid Genetic algorithm combined with the Extreme Gradient Boosting algorithm to predict real estate housing prices. The proposed scheme is evaluated by Root Mean Square Error, processing time, and the number of deleted features. The proposed scheme has been compared with the sole Extreme Gradient Boosting. The experimental results show that the proposed scheme produces the smallest root mean square error value of 0.129 compared to 0.133 of the sole Extreme Gradient Boosting. Furthermore, the predicted time of the proposed scheme is much better than the sole method.
Optimized Random Forest Classifier Basedon Genetic Algorithm for Heart Failure Prediction Maria Ulfah Siregar, Ichsan Setiawan, Najmunda Zia Akmal, Dewi Wardani, Yessi Yunitasari, Ardhi Wijayanto 2022 7th International Conference on Informatics and Computing Icic 2022, 2022 Heart failure is a serious long-term condition that usually gets worse over time. On the other hand, some people do not aware to check their heart health regularly. In this study, the Random Forest will be optimized using the Genetic Algorithm to obtain the best parameters and will be applied to the heart failure dataset from Kaggle. We experimented with two iterations for every nine combinations of the parameters. We compared the results of optimized random forest, stand-alone random forest, decisiontree, and Naïve Bayes algorithms. Our finding is that the optimized method is slightly better than the other algorithms. The best F1-score is obtained atthe second iteration which is 0.90789 compared to0.89404 obtained with the sole random forest, 0.85034 obtained with the decision tree, and 0.86195 obtained with Naive Bayes. The best recall value is 0.91925obtained in the first iteration, and in the second iteration. The best recall is also obtained with the sole random forest algorithm. The best precision valueis 0.89937 which was obtained in the first. By these results, the optimized random forest algorithm could be used to result in reliable predictions about heart failure.
Verification of a Rule-Based Expert System by Using SAL Model Checker Maria Ulfah Siregar, Sayekti Abriani Icicos 2019 3rd International Conference on Informatics and Computational Sciences Accelerating Informatics and Computational Research for Smarter Society in the Era of Industry 4 0 Proceedings, 2019
Experiences using Z2SAL Maria Ulfah Siregar, John Derrick, Siobhan North, Anthony J. H. Simons Proceedings Icacsis 2014 2014 International Conference on Advanced Computer Science and Information Systems, 2014
RECENT SCHOLAR PUBLICATIONS
Vehicle Routing Problem: A Performance Comparison of Hybrid Evolutionary Algorithm with Local Search Strategies MU Siregar, TF Arifin, MJ Badruttamam, MS Aisha, IR Humam, M Hafiz, ... Jurnal Online Informatika 11 (1), 82-97 , 2026 2026
A Systematic Literature Review and Bibliometric Analysis of Software Tampering: Trends and Safeguards F Amanda, MU Siregar, B Sugiantoro, A Fatwanto, MRMI Pulungan, ... JOIV: International Journal on Informatics Visualization 10 (1), 369-375 , 2026 2026
Analisis Ketertarikan Pengguna Microsoft Excel Online untuk Pengolahan Data Silsilah Keluarga Menggunakan TAM dan TPB FR Nufaily, MU Siregar JISKA (Jurnal Informatika Sunan Kalijaga) 10 (3), 279-293 , 2025 2025 Citations: 2
Classification of Senile Cataract Disease Using Convolutional Neural Network Method and Explainable Artificial Intelligence AG Hardandrito, MU Siregar International Journal of Science and Environment (IJSE) 5 (3), 247-256 , 2025 2025
Analisis Perbandingan Learnability antara Framework dan Native PHP pada Mahasiswa Informatika Universitas XYZ DY Jaya, MU Siregar Journal Information Technology Trends (JITRENDS) 2 (02) , 2025 2025
Price Forecasting of Chili Variant Commodities Using Radial Basis Function Neural Network AU Ramadhan, MU Siregar, S Nafisah, M Anshari, R Ndungi, ... IJID (International Journal on Informatics for Development) 12 (1) , 2025 2025 Citations: 1
A Better Performance of GAN Fake Face Image Detection Using Error Level Analysis-CNN MU Siregar, N Nurochman, AH Setianingrum, D Larasati, W Santoso, ... JOIV: International Journal on Informatics Visualization 9 (2), 770-778 , 2025 2025 Citations: 3
Comparison of KNN and Random Forest Algorithms on E-Commerce Service Chatbot F Zamakhsyari, BA Makayasa, RA Hamami, MT Akbar, A Cahyono, ... JISKA (Jurnal Informatika Sunan Kalijaga) 10 (1), 100-109 , 2025 2025 Citations: 2
PENGEMBANGAN MEDIA PEMBELAJARAN INTERAKTIF BERBASIS QUIZIZZ DAN GOOGLE SLIDES AF Bahar, BTK Dewi, ES Mansur, MU Siregar Aplikasia: Jurnal Aplikasi Ilmu-ilmu Agama 24 (2), 133-140 , 2024 2024
Utilizing Prolog for Automatic Transformation of English Words NM Barkah, MU Siregar Journal of Information Technology and Cyber Security 2 (2), 76-82 , 2024 2024
A Survey on Software Requirements Engineering in Information Technology Institutions MT Akbar, MU Siregar Elinvo (Electronics, Informatics, and Vocational Education) 9 (2), 253-264 , 2024 2024 Citations: 5
Automated SPARQL Template for Flexible Question Answering D Wardani, A Wijaya, A Wijayanto, MU Siregar, Y Yunitasari International Journal on Advanced Science, Engineering and Information … , 2024 2024
ANALYSIS OF CHATGPT ACCEPTANCE FOR EDUCATION USING MODIFIED TECHNOLOGY ACCEPTANCE MODEL MR Mustofa, MU Siregar Jurnal Teknik Informatika (Jutif) 5 (4), 479-486 , 2024 2024 Citations: 2
Evaluasi Penggunaan Flowgorithm dalam Pembelajaran Algoritma Pemrograman menggunakan Technology Acceptance Model (TAM) MZ Hisamuddin, MU Siregar Edumatic: Jurnal Pendidikan Informatika 8 (1), 84-92 , 2024 2024 Citations: 2
Cyber Crime Identifying Using Machine Learning Techniques-Based Sentiment Analysis Y Yunitasari, LSTT Sofyana, MU Siregar Engineering Headway 6, 237-243 , 2024 2024 Citations: 1
Comparison of Classification Algorithm and Language Model in Accounting Financial Transaction Record: A Natural Language Processing Approach. BA Makayasa, MU Siregar, B Sugiantoro, A Fatwanto International Journal on Advanced Science, Engineering & Information … , 2024 2024 Citations: 5
Eksperimen Perbandingan Evolutionary Programming dan Evolutionary Strategies dalam Permasalahan Maximization Fungsi Polinomial A Nugroho, MU Siregar Computer Science Research and Its Development Journal 15 (3), 167-176 , 2024 2024
The Formal Graph of APRDF. D Wardani, M Ulfah Siregar, A Wijayanto, Y Yunitasari International Journal on Advanced Science, Engineering & Information … , 2023 2023
RANCANGAN APLIKASI CHATBOT TELEGRAM “TANYA ZAID” SEBAGAI MEDIA PEMBELAJARAN NAHWU MR Astari, MSAK Mardlian, S Bahri, MU Siregar Konferensi Integrasi Interkoneksi Islam dan Sains 5 (1), 313-323 , 2023 2023 Citations: 15
Formalizing Attack Tree on Security Object for MySANi in Legal Metrology MA Ibrahim, F Qamar, Z Shukur, N Zainal, N Marzuki, MU Siregar systems 11 , 2023 2023 Citations: 1
MOST CITED SCHOLAR PUBLICATIONS
A new approach to CPU scheduling algorithm: genetic round robin MU Siregar International Journal of Computer Applications 47 (19), 18-25 , 2012 2012 Citations: 33
Pengaruh Faktor Model UTAUT (Unified Theory of Acceptance and Use of Technology) Terhadap Niat Generasi Milenial Dalam Menggunakan Mobile Banking di Indonesia AD Oktavianita, MU Siregar Jurnal Ekonomi Dan Bisnis (EK&BI) 4 (2), 649-660 , 2021 2021 Citations: 24
Preprocessing kNN algorithm classification using K-means and distance matrix with students’ academic performance dataset S Sugriyono, MU Siregar J. Teknol. dan Sist. Komput 8 (4), 311-316 , 2020 2020 Citations: 24
RANCANGAN APLIKASI CHATBOT TELEGRAM “TANYA ZAID” SEBAGAI MEDIA PEMBELAJARAN NAHWU MR Astari, MSAK Mardlian, S Bahri, MU Siregar Konferensi Integrasi Interkoneksi Islam dan Sains 5 (1), 313-323 , 2023 2023 Citations: 15
Design and Development of Web Based Employee Payroll Information System Using Codeigniter Framework and Extreme Programming Method MU Siregar, DEK Mahardika IJID (International Journal on Informatics for Development) 7 (2), 48-53 , 2018 2018 Citations: 14
Evaluation of IT Service Management (ITSM) Using e-GovQual Dimensions Case Study Regional Office Ministry of Law and Human Rights DIY TE Wijatmoko, MU Siregar IJID (International Journal on Informatics for Development) 8 (2), 55-63 , 2019 2019 Citations: 13
A Usage of McCall's Software Quality Analysis on the Bonus System of PT Surya Pratama Alam MU Siregar, AH Arif JISKA (Jurnal Informatika Sunan Kalijaga) 3 (1), 63-72 , 2018 2018 Citations: 13
The effects of artificial intelligence on the Kenyan society R Ndungi, MU Siregar Indonesian Journal of Electrical Engineering and Computer Science 32 (2 … , 2023 2023 Citations: 12
Application of the Naive Bayes Classifier Method in the Sentiment Analysis of Twitter User About the Capital City Relocation SA Nugraha, MU Siregar International Conference of Science and Engineering 4, 171-175 , 2021 2021 Citations: 11
Recommender systems for specializing new students in the K-13 curriculum using the profile matching, SAW, and a combination of both ME Iswanto, MU Siregar, S 'Uyun, MT Nurruzzaman Jurnal Teknologi Dan Sistem Komputer 9 (2), 96-105 , 2021 2021 Citations: 11
Intelligent system for classification of student personality with naive bayes algorithm D Fahrudy, I Afkarina, M Fadli, R Asasunnaja, WN Ahsan, FE Setyawan, ... SINTECH (Science and Information Technology) Journal 5 (1), 1-9 , 2022 2022 Citations: 8
Optimized Random Forest Classifier Based on Genetic Algorithm for Heart Failure Prediction MU Siregar, I Setiawan, NZ Akmal, D Wardani, Y Yunitasari, A Wijayanto 2022 Seventh International Conference on Informatics and Computing (ICIC) , 2022 2022 Citations: 8
Suatu Pendekatan Hibrid Menggunakan Topsis - Entropi pada Penentuan Siswa Penerima Beasiswa Prestasi Berbasiskan Kriteria Objektif MU Siregar, T Nasiroh, M Mustakim Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) 8 (1), 167-176 , 2021 2021 Citations: 7
Rancang Bangun Sistem Informasi Penyediaan Air Minum dan Sanitasi Berbasis Masyarakat (PAMSIMAS) dengan Metode Extreme Programming H Musafa, MU Siregar Yogyakarta: UIN Sunan Kalijaga Yogyakarta , 2019 2019 Citations: 7
Evaluation of E-Government Using COBIT 5 Framework (Case Study of Sistem Database Pemasyarakatan Implementation in Ministry of Law and Human Rights in the Special Region of … F Novianto, MU Siregar IJID (International Journal on Informatics for Development) 8 (2), 74-83 , 2019 2019 Citations: 6
Rancang Bangun Sistem Informasi Penyediaan Air Minum Dan Sanitasi Berbasis Masyarakat (Pamsimas) Dengan Metode Extreme Programming MU Siregar, H Musafa JISKA (Jurnal Informatika Sunan Kalijaga) 4 (2), 88-93 , 2019 2019 Citations: 6
A Survey on Software Requirements Engineering in Information Technology Institutions MT Akbar, MU Siregar Elinvo (Electronics, Informatics, and Vocational Education) 9 (2), 253-264 , 2024 2024 Citations: 5
Comparison of Classification Algorithm and Language Model in Accounting Financial Transaction Record: A Natural Language Processing Approach. BA Makayasa, MU Siregar, B Sugiantoro, A Fatwanto International Journal on Advanced Science, Engineering & Information … , 2024 2024 Citations: 5
An Implementation of Profile Matching Method to Determine Agricultural Crops that Suit the Land AF Negarawan, MU Siregar, A Fatwanto, MDR Wahyudi International Conference on Science and Engineering (ICSE-UIN-SUKA 2021 … , 2021 2021 Citations: 4
