Wahyuddin S. was born at Malaka-Bone-Sulawesi Selatan in 1992. In 2011 he attended STMIK Dipanegara Makassar and was completed in 2015. He was completed after attending 7 semesters and active on an XPcom (Extreme Programmer Computer) campus organization. He was also active as a lecturer assistant for three semesters and taught several courses on programming. He continued his Master of Information systems at UNIKOM Bandung in 2016 and was completed in April 2019. He worked as a lecturer at a campus (STMIK AMIKA Soppeng) 2019 to present and also a Freelance Web Programmer. Has competence in the field of software engineer, application developer, multimedia, web developer, network security, and data analyst.
EDUCATION
Magister of Information System UNIKOM
RESEARCH INTERESTS
Data Mining, Big Data
15
Scopus Publications
1135
Scholar Citations
17
Scholar h-index
35
Scholar i10-index
Scopus Publications
Shapelet Transformation of Multivariate Time Series for IoT Anomaly Detection Wahyuddin S., Ahmad Saikhu, Agus Budi Raharjo Engineering Technology and Applied Science Research, 2026 The proliferation of Internet of Things (IoT) devices has generated substantial volumes of multivariate time-series data in multiple domains. Such data are susceptible to anomalies that may indicate system malfunctions or security threats. This research introduces a novel shapelet transformation approach for classifying multivariate time-series data to improve anomaly detection in IoT systems. Our approach distinguishes itself from the classic Shapelet Transform by specifically optimizing the extraction process to handle high-dimensional IoT data more efficiently, contrasting with methods such as Fast Shapelets, which are primarily designed for speed without focusing on multivariate contexts. This methodology centers on extracting short, informative subsequences, known as shapelets, from time series to facilitate classification. This approach is validated using the industrial IoT fault detection dataset for predictive maintenance in automation, which contains 1,000 entries of sensor data collected from machines in an industrial automation environment. This dataset includes three main sensor measurements: vibration (mm/s), temperature (°C), and pressure (Bar). The evaluation process involves partitioning the data into training and test sets and employing cross-validation to ensure robustness. The performance of the proposed method is benchmarked against traditional algorithms. Results demonstrate notable improvements: the F1-score is 0.6451 for temperature, 0.5778 for vibration, and 0.6984 for pressure, with an overall accuracy of 94%. This study establishes a framework for enhancing IoT system reliability by advancing anomaly detection, data mining, and machine learning.
Optimizing Shapelet Lengths for Effective Time Series Classification Wahyuddin S, Ahmad Saikhu, Agus Budi Raharjo Icadeis 2025 2025 International Conference on Advancement in Data Science E Learning and Information System Integrating Data Science and Information System Proceeding, 2025 In this paper, we propose a novel framework for optimizing shapelet lengths to enhance time series classification accuracy. Our approach involves a systematic exploration of shapelet lengths, combined with a multi-objective optimization strategy that balances model complexity and classification accuracy. We introduce a method for dynamically selecting shapelet lengths based on data characteristics, allowing for a more tailored extraction process. We evaluate our framework on several benchmark time series datasets, comparing its performance against traditional shapelet-based methods and other classification techniques. Our results demonstrate that optimizing shapelet lengths leads to significant improvements in classification accuracy and robustness, particularly in datasets with varying temporal patterns. This work contributes to the field of time series analysis by addressing a critical gap in shapelet-based methodologies. By providing a structured approach to shapelet length optimization, we aim to enhance the applicability of shapelet methods across diverse domains, paving the way for more accurate and interpretable time series classification solutions.
Time Series Shapelets Classification Method for Predicting Global Temperature Anomalies S Wahyuddin, Ahmad Saikhu, Agus Budi Raharjo 2024 9th International Conference on Informatics and Computing Icic 2024, 2024 Accurate prediction of global temperature anomalies is crucial for understanding climate change and informing policy decisions. This paper presents a novel time series classification method based on shapelets for predicting global temperature anomalies. Shapelets are small, discriminative subsequences within time series data that capture important patterns. By leveraging shapelets, our method identifies and utilizes these patterns to improve classification accuracy. We propose a framework that extracts and selects relevant shapelets from historical temperature data, followed by a classification algorithm to predict future anomalies. Experimental results demonstrate that our shapelet-based approach significantly outperforms traditional time series classification methods in terms of predictive accuracy and robustness. This work provides a valuable tool for climate scientists and policymakers to better anticipate and respond to global temperature changes.
Response Time Prediction of M/M/1SRPT Queuing System Using Simulation Modeling and Artificial Intelligence Ahmad Saikhu, Rully Soelaiman, Sheinna Yendri, S Wahyuddin 2023 8th International Conference on Informatics and Computing Icic 2023, 2023 In queueing systems, users need to know the expected response time of their jobs for decision-making and proofing system reliability. Because of this reason, there is a need to predict the response time of given jobs when a specific discipline is implemented in the queuing system. In this paper, we proposed a novel method combining simulation modeling and artificial intelligence methods to predict job response time on the M/M/1/SRPT queue. Simulation modeling is used for generating data, which is then used by the artificial methods to do the response time prediction. In our proposed approach, three attributes are used to predict the response time: job processing time, total processing time in the system, and total processing time of the preceding jobs in the queue. These attributes are used in both artificial intelligence methods: linear and support vector regression (SVR). Based on the case study testing result, our proposed method resulted in an average variance score of 94.5% using linear regression, 99.7% using SVR polynomial, and 99.8% using SVR RBF, which proves the prediction accuracy.
Land suitability analysis using geographic information system (GIS): A case study in Soppeng district S Wahyuddin, H Buchari, I I Wahab, Z Rahmat, Z Fadli Journal of Physics Conference Series, 2021 The agricultural sector is a sector of the economy that is still the flagship in various regions in Indonesia, especially Soppeng regency. The area of Soppeng hills is approximately 800 km2 and is at an average altitude of 200 m above sea level, and has no coastal area. The utilization of Geographic Information Systems (GIS) promises resource management and modeling, especially quantitative models, to be more accessible and simpler. GIS is an efficient and effective way to know the characteristics of a region’s land and its development potential. Land suitability is the suitability of land for a particular purpose of use through the determination of land value (class) and land use patterns connected to the territory’s potential. It can be attempted more targeted land use along with its sustainability maintenance efforts. The spatial analysis involves modeling, testing, and interpreting model results to extract or form new information from a collection of geographic elements. This research will be carried out for 12 Months (1 year) through 4 stages. The research aims to identify land use’s suitability in the analysis of agricultural land suitability using geographical information systems in Soppeng regency area.
Gap Analysis of University Online Learning Website from Students' Perspectives: A Case from Telkom University, Indonesia M Pradana, M D Rahmawan, S Wahyuddin, R Imam Journal of Physics Conference Series, 2021 The purpose of this research is to observe the perceived quality of Telkom University online learning website from students’ perspectives. Students here act as the main users of the learning platform and we would like to see whether the perceived quality and the ideal quality already fulfil users’ expectation. The data used are the primary and secondary data with a set of sample taken from 100 students. We use the question items from website quality method and analyse the data with importance performance analysis (gap analysis). The research shows that the usability and service interaction aspects of the website have quite significant gaps between perceived and ideal qualities.
Gap analysis of Indonesian state-owned bank internet banking website Proceedings of the International Conference on Industrial Engineering and Operations Management, 2019
RECENT SCHOLAR PUBLICATIONS
TEKNOLOGI MASA DEPAN APLIKASI DAN INOVASI AR/VR DALAM BERBAGAI BIDANG AA Ir, MT Jabbar, S Marlina, S Wahyuddin Penamuda Media , 2026 2026
Shapelet Transformation of Multivariate Time Series for IoT Anomaly Detection S Wahyuddin, A Saikhu, AB Raharjo Engineering, Technology & Applied Science Research 16 (2), 33549-33556 , 2026 2026
Institutional Capacity and Public Vocational Training Service Quality in Responding to Digital Labor Market Challenges Z Fadli, W Wahyuddin PUBLICUS: Jurnal Administrasi Publik 4 (1), 110-121 , 2026 2026
Time Series Modeling for Unemployment Prediction in Indonesia Using ARIMA (Autoregressive Integrated Moving Average) Approach S Wahyuddin, Z Rachmat Proceeding of Research and Civil Society Desemination 3 (1), 229-236 , 2025 2025
Cloud Computing: Referensi Lengkap S Wahyuddin, IP Sari, SH Tampubolon, A Zulherry, B Butsiarah, T Taufik, ... Yayasan Kita Menulis , 2025 2025 Citations: 2
Penerapan Artificial Intelligence dalam TI S Wahyuddin, P Wahyuningsih, H Mubarak, S Jura, D Sofia, H Haeriani, ... Yayasan Kita Menulis , 2025 2025 Citations: 1
Integrasi Teknologi Informasi Dalam Desain Pembelajaran Modern A Impron, AY Salim, E Haerani, N Kholisatul‘Ulya, H Purnata, AA Rafiq, ... Penerbit Widina , 2025 2025 Citations: 13
Keamanan Data dalam Revolusi Teknologi NRDP Astuti, F Natsir, MS Haris, Y Ramdhani, E Aribowo, N Anwar, ... Qriset Indonesia , 2025 2025 Citations: 8
Applying text mining for case analysis and vaccination status level in Ontario S Wahyuddin, Z Rachmat, Amriadi, R Fahrudin, GAN Pongdatu, Z Fadli AIP Conference Proceedings 3200 (1), 040034 , 2025 2025
Optimizing Shapelet Lengths for Effective Time Series Classification S Wahyuddin, A Saikhu, AB Raharjo 2025 International Conference on Advancement in Data Science, E-learning and … , 2025 2025
e-Government dan Inovasi Pemerintahan S Wahyuddin, S Abdullah, SH Tampubolon, B Waseso, C Susanto, ... Yayasan Kita Menulis , 2025 2025 Citations: 3
Penerapan Software Cisco Packet Tracer Sebagai Media Pembelajaran Praktikum Pada Mata Kuliah Jaringan Komputer H Hendrawansyah, Z Rachmat, S Wahyuddin Martabe: Jurnal Pengabdian Kepada Masyarakat 7 (10), 4159-4168 , 2025 2025
Metodologi penelitian teknologi informasi SN Wahyuddin S, Ahmad Jurnaidi Wahidin, Yuliana Mose, Yoseph Pius Kurniawan ... ISBN: 978-623-125-689-8 Penerbit: Get Press Indonesia , 2025 2025
Dasar-dasar dan aplikasi internet of things (IoT) AI Wahyuddin S, Dwi Feriyanto, Dwi Sasmita Aji Pambudi, Muhammad Nuzan Rizki ISBN 978-623-125-732-1 Penerbit Get Press Indonesia , 2025 2025
E-business : inovasi dan strategi untuk era digital ZHNK Zul Rachmat, Wahyuddin S, Amriadi, Ihsanulfu’ad Suwandi, ... ISBN 978-623-473-792-9 Penerbit CV. Madani Berkah Abadi , 2025 2025
TEKNOLOGI INFORMASI S Wahyuddin, AJ Wahidin, Y Mose, YPK Kelen, S Nasiroh, M Syahputra, ... 2025
Time Series Shapelets Classification Method for Predicting Global Temperature Anomalies S Wahyuddin, A Saikhu, AB Raharjo 2024 Ninth International Conference on Informatics and Computing (ICIC), 1-5 , 2024 2024
UI/UX development using design thinking method R Fahrudin, GAN Pongdatu, A Rahman, CF Palembang, S Wahyuddin AIP Conference Proceedings 2867 (1), 030003 , 2024 2024 Citations: 2
Basis Data: Desain, Implementasi, dan Manajemen M Maemunah, Y Yuswardi, S Wahyuddin, K Kamaruddin, T Tommy, ... Yayasan Kita Menulis , 2024 2024 Citations: 9
MOST CITED SCHOLAR PUBLICATIONS
Teknologi Digital di Era Modern SH Wibowo, S Wahyuddin, AA Permana, S Sembiring Teknologi Digital Di Era Modern , 2023 2023 Citations: 118
Technology, Law And Society W Andriyani, R Sacipto, D Susanto, C Vidiati, R Kurniawan, ... Tohar Media , 2023 2023 Citations: 61
Indonesia’s fight against COVID-19: the roles of local government units and community organisations M Pradana, N Rubiyanti, I Hasbi, DG Utami, W S Local Environment 25 (9), 741-743 , 2020 2020 Citations: 60
Machine learning AA Permana, S Wahyuddin, LW Santoso, GWN Wibowo, AK Wardhani, ... Machine learning , 2023 2023 Citations: 34
Perancangan Aplikasi E-Learning Berbasis Website Pada SMP Negeri 3 Watansoppeng R Handayani, Z Rachmat, S Wahyuddin JUMISTIK 1 (1), 43-54 , 2022 2022 Citations: 34
Cloud Computing: Konsep dan Implementasi M Muttaqin, J Simarmata, AM AKP, N Nurzaenab, IF Ashari, S Wahyuddin Cloud Computing: Konsep dan Implementasi , 2023 2023 Citations: 31
Rekayasa Perangkat Lunak Panduan Praktis Untuk Pengembangan Aplikasi Berkualitas AM Dawis, YWS Putra, F Fitria, D Hamidin, SN Yutia, M Maniah, NR Feta, ... Penerbit Widina , 2023 2023 Citations: 28
Indonesian University Students' Entrepreneurial Intention: A Conceptual Study M Pradana, A Wardhana, C Wijayangka, BR Kartawinata, W S Journal of Critical Reviews 7 (7), 571-573 , 2020 2020 Citations: 27
Metodologi penelitian kuantitatif: dengan Aplikasi IBM SPSS S Wahyuddin, PW Santosa, N Heryana, L Lokollo, R Ristiyana, KA Roni, ... Get Press Indonesia , 2023 2023 Citations: 26
Peramalan Transaksi Penjualan dengan Metode Holt-Winter Exponential Smoothing GAN Pongdatu, E Abinowi, S Wahyuddin Jurnal Ilmiah Teknologi Infomasi Terapan 6 (3), 228-233 , 2020 2020 Citations: 26
Multimedia dan Sains Penerapan Teknologi Untuk Penelitian dan Penyampaian Informasi S Setiyanto, IC Utomo, AM Dawis, T Yuliati, NB Nugraha, M Maniah, ... Penerbit Widina , 2023 2023 Citations: 24
Artificial Intelligence: Konsep Dasar Dan Kajian Praktis AM Dawis, IS Himawan, D Meidelfi, F Ikhram, I Intan, R Harun, MS Haris, ... Tohar Media , 2022 2022 Citations: 24
Data Science dan Pembelajaran Mesin M Muttaqin, AK Jaya, S Harlina, S Wahyuddin, L Hakim, M Anshori Data Science dan Pembelajaran Mesin , 2023 2023 Citations: 23
Gap Analysis of Indonesian State-Owned Bank Internet Banking Website M Pradana, S Wahyuddin, S Syarifuddin, A Putra Proceedings of the International Conference on Industrial Engineering and … , 2019 2019 Citations: 21
Layanan Digital Di Era 5.0 S Wahyuddin, JS Pasaribu, R Bau, Z Munawar, A Hermila, B Harto, ... Global Eksekutif Teknologi , 2023 2023 Citations: 19
Rancang Bangun Sistem Informasi Pengelolaan Data Penduduk Berbasis Web Pada Desa Palangiseng Kabupaten Soppeng Z Rachmat, S Wahyuddin Jurnal Minfo Polgan 12 (1), 1022-31 , 2023 2023 Citations: 19
REKAYASA PERANGKAT LUNAK RM Romindo, T Yusnanto, N Heryana, APA Jamaludin, AA Permana, ... 2023 Citations: 17
Analysis of Indonesia’s Inflation Using ARIMA and Artificial Neural Network FI Estiko, W S Economics Development Analysis Journal 8 (2), 151-162 , 2019 2019 Citations: 15
Sistem Informasi Pelayanan Administrasi pada Desa Abbanuangnge Kabupaten Soppeng Z Rachmat, A Irfan, A Ardi REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer 8 (1), 56-65 , 2024 2024 Citations: 14
Perancangan Sistem Informasi Investaris Barang di SMP Negeri 1 Tanasitolo Kabupaten Wajo I Suwandi, Z Rachmat Jurnal Bisnis Digital dan Enterpreneur (BISENTER) 1 (1), 8-16 , 2023 2023 Citations: 14
