Article Per Year (5 Year)
p-Index From 2021 - 2026
4.2
P-Index
This Author published in this journals
All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Pengabdian UntukMu NegeRI Sinkron : Jurnal dan Penelitian Teknik Informatika JIKO (Jurnal Informatika dan Komputer) Jurnal Penelitian Pendidikan IPA (JPPIPA) Dinamisia: Jurnal Pengabdian Kepada Masyarakat INTEK: Informatika dan Teknologi Informasi Building of Informatics, Technology and Science Indonesian Journal of Electrical Engineering and Computer Science Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Computer Science and Information Technology (CoSciTech) Malcom: Indonesian Journal of Machine Learning and Computer Science Journal of Software Engineering and Information System (SEIS) Teknomatika: Jurnal Informatika dan Komputer
Soni
Universitas Muhammadiyah Riau
Religion Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Physics Social Sciences Other

Published : 40 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 40 Documents
Search

 1   2   3   4 
Improving imbalanced class intrusion detection in IoT with ensemble learning and ADASYN-MLP approach Soni, Soni; Remli, Muhammad Akmal; Mohd Daud, Kauthar; Al Amien, Januar
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 2: November 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i2.pp1209-1217

Abstract

The exponential growth of the internet of things (IoT) has revolutionized daily activities, but it also brings forth significant vulnerabilities. intrusion detection systems (IDS) are pivotal in efficiently detecting and identifying suspicious activities within IoT networks, safeguarding them from potential threats. It proposes a ensemble approach aimed at enhancing model performance in such scenarios. Recognizing the unique challenges posed by imbalanced class distribution, the research employs three sampling techniques LightGBM adaptive synthetic sampling (ADASYN) with multilayer perceptron (MLP), XGBoost ADASYN with MLP, and LightGBM ADASyn with XGBoost to address class imbalance effectively. Evaluation confusion matrix performance metrics underscores the efficacy of ensemble models, particularly LightGBM ADASYN with MLP, XGBoost ADASYN with MLP, and LightGBM ADASYN with XGBoost, in mitigating imbalanced class issues. The LightGBM ADASYN with MLP model stands out with 99.997% accuracy, showcasing exceptional precision and recall, demonstrating its proficiency in intrusion detection within minimal false positives negatives. Despite computational demands, integrating XGBoost within ensemble frameworks yields robust intrusion detection results, highlighting a balanced trade-off between accuracy, precision, and recall. This research offers valuable insights into the strengths with different ensemble models, significantly contributing to the advancement of accurate and reliable IDS in realm of IoT.
IMPLEMENTASI ALGORITMA A STAR DALAM PENCARIAN RUTE TERPENDEK (SHORTEST PATH PROBLEM) PADA SISTEM PENCARIAN KANTOR POS DI KOTA PEKANBARU Mukhtar, Harun; Hendri, Yusriadi; Soni
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 2 No. 1 (2022)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (716.156 KB) | DOI: 10.37859/seis.v2i1.3313

Abstract

With the advancement of information technology today, there are several solutions that can facilitate the search for the shortest path (Shortest Path Problem) by using various algorithms such as the djiktra algorithm, A star algorithm, floyd warshall algorithm, prim algorithm and others. Algorithm A* (A star) is one of the algorithms included in the category of search methods that have information (informed search method). This algorithm is very good as a solution to the path finding process where this algorithm looks for the distance of the fastest route that will be taken by an initial point (starting point) to the destination object. The search technique used in this simulation is using the A* Algorithm with the manhattan distance heuristic function. Path Finding is one of the most important materials in Artificial Intelligence. Path Finding is usually used to solve problems on a graph. This study aims to provide a solution in finding the shortest route, so as to reduce operational costs that must be incurred by the company and also with this new system, it can be known the distance from one point to another without using manual calculations.
Performance evaluation of multiclass classification models for ToN-IoT network device datasets Soni, Soni; Remli, Muhammad Akmal; Daud, Kauthar Mohd; Al Amien, Januar
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 1: July 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i1.pp485-493

Abstract

Internet of things (IoT) technology has empowered tangible objects to establish internet connections, facilitating data exchange with computational capabilities. With significant potential across sectors like healthcare, environmental monitoring, and industrial control, IoT represents a promising technological advancement. This study explores datasets from ToN-IoT’s IoT devices, focusing on multi-class classification, including normal and attack classes, with an additional aim of identifying potential attack sub-classes. Datasets comprise various IoT devices, such as refrigerators, garage doors, global positioning systems (GPS) sensors, motion lights, modbus devices, thermostats, and weather sensors. Comparative analysis is conducted between two prominent multiclass classification models, extreme gradient boosting (XGBoost) and light gradient boosting machine (LightGBM), utilizing accuracy and computational time metrics as evaluation criteria. Research findings highlight that the LightGBM model achieves superior accuracy at 78%, surpassing XGBoost 74.31%. However, XGBoost demonstrates an advantage with a shorter computational time of 1.23 seconds, compared to LightGBM 6.79 seconds. This study not only provides insights into multiclass classification model selection but also underscores the crucial consideration of the trade-off between accuracy and computational efficiency in decision-making. Research contributes to advancing our understanding of IoT security through effective classification methodologies. The findings offer valuable information for researchers and practitioners, emphasizing the nuanced decisions needed when selecting models based on specific priorities like accuracy and computational efficiency.
Enhancing attack detection in IoT through integration of weighted emphasis formula with XGBoost Al Amien, Januar; Ab Ghani, Hadhrami; Md Saleh, Nurul Izrin; Soni, Soni
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i1.pp641-648

Abstract

This research addresses the challenge of detecting attacks in the internet of things (IoT) environment, where minority classes often go unnoticed due to the dominance of majority classes. The primary objective is to introduce and integrate the imbalance ratio formula (IRF) into the XGBoost algorithm, aiming to provide greater emphasis on minority classes and ensure the model's focus on attack detection, particularly in binary and multiclass scenarios. Experimental validation using the IoTID20 dataset demonstrates the significant enhancement in attack detection accuracy achieved by integrating IRF into XGBoost. This enhancement contributes to the consistent improvement in distinguishing attacks from normal traffic, thereby resulting in a more reliable attack detection system in complex IoT environments. Moreover, the implementation of IRF enhances the robustness of the XGBoost model, enabling effective handling of imbalanced datasets commonly encountered in IoT security applications. This approach advances intrusion detection systems by addressing the challenge of class imbalance, leading to more accurate and efficient detection of malicious activities in IoT networks. The practical implications of these findings include the enhancement of cybersecurity measures in IoT deployments, potentially mitigating the risks associated with cyber threats in interconnected smart environments.
Advanced tourist arrival forecasting: a synergistic approach using LSTM, Hilbert-Huang transform, and random forest Mukhtar, Harun; Remli, Muhammad Akmal; Mohamad, Mohd Saberi; Wan Salihin Wong, Khairul Nizar Syazwan; Ridhollah, Farhan; Deprizon, Deprizon; Soni, Soni; Lisman, Muhammad; Amran, Hasanatul Fu'adah; Sunanto, Sunanto; Ismanto, Edi
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i1.pp517-526

Abstract

An advanced synergistic approach for forecasting tourist arrivals is presented, integrating long short-term memory (LSTM), Hilbert-Huang transform (HHT), and random forest (RF). LSTM is leveraged for its capability to capture long-term dependencies in sequential data. Additional data from Google Trends (GT) is processed with HHT for feature extraction, followed by feature selection using the RF algorithm. The combined HHT-RF-LSTM model delivers highly accurate forecasts. Evaluation employs regression analysis with metrics such as root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and mean square error (MSE), highlighting the effectiveness of this innovative approach in predicting tourist arrivals. This methodology provides a robust framework for handling limited datasets and improving forecast reliability. By incorporating diverse data sources and advanced preprocessing techniques, the model enhances prediction performance, demonstrating the strong performance of RF in feature selection.
Optimalisasi Peran Pendidikan Mahasiswa KKN Kelompok 55 Universitas Muhammadiyah Riau Dalam Membangun Generasi Masa Depan Eka Putra; Soni, Soni; Hul Hasanah, Sifa; Rinaldi, Rinaldi; Ramadhanti, Nurul
Jurnal Pengabdian UntukMu NegeRI Vol. 7 No. 2 (2023): Pengabdian Untuk Mu negeRI
Publisher : LPPM UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jpumri.v7i2.6035

Abstract

Tujuan utama pelaksanaan program Kuliah Kerja Nyata (KKN) Kelompok 55 Universitas Muhammadiyah Riau adalah memberikan pengalaman berharga kepada mahasiswa dalam menggali potensi desa dan memberikan kontribusi kepada masyarakat setempat. Pelaksanaannya melibatkan survei dan perencanaan program kerja. Beberapa lembaga pendidikan di di Desa Kuala Gading, Kecamatan Batang Cenaku, Kabupaten Indragiri Hulu, Provinsi Riau, pada 24 Juli hingga 31 Agustus 2023 menjadi sasaran Program Kerja mahasiswa KKN yang dilakukan rutin setiap harinya. Seluruh mahasiswa KKN berperan dalam membantu penyelenggaraan pendidikan di desa. Tidak hanya di sekolah, mahasiswa KKN juga mengadakan les gratis dan mengajar mengaji bagi anak-anak demi memaksimalkan kegiatan pendidikan di desa. Respons positif dari pihak desa diperoleh selama mengajar di berbagai lembaga pendidikan lokal, mulai dari tingkat Taman Kanak-Kanak (TK), Sekolah Dasar (SD), hingga Pondok Pesantren Tebu Ireng 4. Kolaborasi mahasiswa KKN tersebut diharapkan dapat memberikan dampak yang signifikan dalam keikutsertaan membangun generasi masa depan.
Pemanfaatan Dan Pengembangan Tanaman Obat Keluarga (Toga) Oleh Masyarakat Desa Bukit Lingkar Mukhtar, Harun; Soni, Soni; Prastiwi, Adila Pramudiah; Mas’yuri, Dhina Nurriska; Kultum, Fi Ardhi; Vanama, Melsa; Nengsih, Rafni Yulia; Arkan, M Alif; Muzahaffar, Fatih Al; Aini, Fitria
Jurnal Pengabdian UntukMu NegeRI Vol. 7 No. 2 (2023): Pengabdian Untuk Mu negeRI
Publisher : LPPM UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jpumri.v7i2.6037

Abstract

TOGA (Tanaman Obat Keluarga ) merupakan kumpulan berbagai jenis tanaman obat yang memiliki khasiat untuk menyembuhkan berbagai penyakit, dengan ada nya tumbuhan TOGA di sekitaran lingkungan rumah masyarakat dapat memudahkan masyarakat dalam mengobati berbagai penyakit ringan yang biasa di derita masyarakat contoh nya seperti batuk,demam,gangguan pencernaan, sakit perut, flu , sakit gigi, dan masih banyak yang lainya. Sehingga keberadaan TOGA di lingkungan masyarakat bukit lingkar menjadi sangat penting karena menjadi sebuah alternatif pengobatan alamai secara mandiri oleh karena itu tujuan dari pengabdian ini yaitu untuk memberikan penyuluhan pemanfaatandan pengembangan tanaman TOGA . metode yang di gunakan dalam pengabdian kali ini yaitu memberikan penyuluhan, pelatihan, dan memberikan berbagai resep bagaimana cara mengelolah tanaman obat menjadi obat yang siap pakai.
Penerapan Model Technology Readiness Index untuk Mengukur Tingkat Kesiapan Mahasiswa dalam Penerimaan Sistem E-Polvot Anam, M Khairul; Zoromi, Fransiskus; Soni; Nasution, Torkis; Andesa, Khusaeri
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 6: Desember 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2023107368

Abstract

BEM (Badan Eksekutif Mahasiswa) merupakan ujung tombak dalam menjalankan tata pemerintahan di kalangan mahasiswa dan media untuk menyampaikan aspirasi baik berupa kesejahteraan, keamanan baik secara lisan maupun dalam tulisan kepada perguruan tinggi. Pemilihan BEM di perguruan tinggi rutin dilaksanakan setiap setahun. Namun dalam pemilihan BEM, beberapa mahasiswa tidak dapat menggunakan hak memilih karena keterbatasan waktu yang disediakan oleh panitia pemilihan. Dalam pelaksanaan pemilihan, disediakan 3 jenis waktu perkuliahan, yaitu regular siang jam 08.00 – 17.00, malam jam 17.45 – 09.30, dan non-reguler diadakan perkuliahan jarak jauh atau online setiap akhir pekan. Untuk pemilihan biasanya mahasiswa reguler malam dan non reguler tidak melakukan voting atau pemilihan dikarenakan waktunya diadakan siang hari. Untuk mengatasi permasalahan tersebut perlunya sebuah sistem bisa digunakan dimana saja tanpa harus datang ke kampus. Salah satu sistem yang dapat digunakan adalah e-polvot atau elektronik polling dan voting. Namun untuk menghadirkan sistem tersebut perlu kesiapan baik dari infrastruktur maupun pengguna. Penelitian ini melakukan analisis terhadap kesiapan mahasiswa STMIK Amik Riau dalam penerimaan sistem e-polvot. Tujuan penelitian adalah menganalisis kesiapan mahasiswa menggunakan sistem e-polvot. Analisis kesiapan mahasiswa menggunakan model Technology Readiness Index (TRI). Model ini memiliki 4 variabel yaitu Optimism, Innovativeness, Discomfort dan Insecurity. Populasi yang digunakan dalam penelitian ini adalah seluruh mahasiswa STMIK Amik Riau dengan teknik total sampling. Hasil yang didapatkan pada penelitian ini yaitu mahasiswa STMIK Amik Riau siap untuk menerima sistem e-polvot. Hal ini dilihat dari nilai yang didapatkan dari pengukuran ini adalah 3,93 yang dikategorikan HIGH.   Abstract The Student Executive Board (BEM) plays a pivotal role in governing students and serves as a platform to express aspirations, both in terms of welfare and security, through both oral and written means to the university. BEM elections at the university are regularly conducted annually. However, in the BEM elections, some students are unable to exercise their voting rights due to time constraints set by the election committee. The election process offers three types of lecture schedules: regular daytime from 08:00 to 17:00, evening lectures from 17:45 to 09:30, and non-regular lectures held during weekends for distance or online learning. Consequently, regular evening and non-regular students often abstain from voting or participating in the election due to the daytime scheduling. To address this issue, a system is needed that can be accessed from anywhere without physically coming to the campus. One such system that can be used is the e-polvot or electronic polling and voting system. However, implementing such a system requires readiness in terms of infrastructure and user acceptance. This research aims to analyze the readiness of STMIK Amik Riau students in accepting the e-polvot system. The research objective is to assess the readiness of students in using the e-polvot system. The analysis of students' readiness utilizes the Technology Readiness Index (TRI) model, which consists of four variables: Optimism, Innovativeness, Discomfort, and Insecurity. The population used for this study comprises all students of STMIK Amik Riau, and the total sampling technique is employed. The findings of this research indicate that the students of STMIK Amik Riau are ready to accept the e-polvot system, as evidenced by a TRI score of 3.93, which falls into the "HIGH" category.
What Can Spatial Assessment Reveal About Flash Flood Risk and Ecosystem Carrying Capacity in Tropical Highland Environments? Juita, Erna; Dasrizal; Ibrahim, Mohd Hairy; Yuniarti, Elsa; Ulni, Arie Zella Putra; Soni
Jurnal Penelitian Pendidikan IPA Vol 11 No 11 (2025): November: In Progress
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i11.11889

Abstract

Flash floods are among the most destructive hydrometeorological hazards in tropical highland regions, yet their spatial risks remain poorly quantified in data-scarce environments. This study assessed flash flood risk in Solok Selatan Regency, West Sumatra (Indonesia), by integrating landform and slope classification with the Topographic Wetness Index (TWI) derived from a 30 m DEM. Historical records of 11 flood events between 2010 and 2020 were used for model validation. The analysis revealed that most of the regency is characterized by moderate flash flood risk, while high-risk zones are concentrated in steep fluvial landscapes. Validation against observed flood locations demonstrated a spatial match of 95.2%, confirming the reliability of the model. In addition, the evaluation of hydrological ecosystem service capacity indicated that over 80% of the landscape has only moderate regulatory function, limiting its ability to buffer runoff. These findings highlight the importance of integrating DEM-based hydrological indices with ecosystem assessments to support more effective disaster risk reduction and spatial planning in tropical highland environments.
Edukasi Antibiotik Untuk Keluarga Sebagai Upaya Preventif Terhadap Risiko Stunting Pada Anak Desa Sungai Kayu Ara Anugerah Putra, Bayu; Dian Utami; Rico Apriandika; Hanum Salsabila; Fakhira Frisya Ramadhani; Alris Gusnanda; Septiana Srinandini; Jihan Aulia; Soni, Soni; Firdaus, Rahmad; Mukhtar, Harun; Br Bangun, Elsi Titasari; Handayani, Fitri; Amran, Hasanatul Fu'adah
Jurnal Pengabdian UntukMu NegeRI Vol. 9 No. 3 (2025): Pengabdian Untuk Mu negeRI
Publisher : LPPM UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jpumri.v9i3.10669

Abstract

Stunting masih menjadi salah satu masalah kesehatan masyarakat di Indonesia dengan prevalensi yang cukup tinggi. Salah satu faktor risiko penting terjadinya stunting adalah infeksi berulang pada anak, yang sering kali ditangani dengan pemberian antibiotik. Penggunaan antibiotik yang tepat dapat membantu mencegah stunting dengan cara menekan beban penyakit, namun penggunaan yang tidak rasional berisiko menimbulkan resistensi serta gangguan keseimbangan mikrobiota usus yang berdampak pada penyerapan gizi. Rendahnya literasi penggunaan antibiotik di masyarakat, khususnya di kalangan ibu rumah tangga dan lansia sebagai pengasuh utama dalam keluarga, menjadi tantangan tersendiri. Kegiatan sosialisasi ini bertujuan untuk meningkatkan pemahaman masyarakat mengenai penggunaan antibiotik rasional serta mengingatkannya terhadap pencegahan stunting. Metode yang digunakan adalah ceramah interaktif, diskusi, dan pembagian media edukasi. Hasil kegiatan menunjukkan adanya peningkatan pemahaman peserta mengenai pentingnya penggunaan antibiotik sesuai anjuran tenaga medis. Oleh karena itu, sosialisasi antibiotik kepada ibu dan lansia memiliki peran penting sebagai upaya preventif yang secara tidak langsung dapat mendukung pencegahan stunting pada anak.
Co-Authors Ab Ghani, Hadhrami Agusriadi, - Al Amien, Januar Alris Gusnanda Aminullah, Rabiah Aminuyati Amran, Hasanatul Fu'adah Anam, M Khairul Ananda Fitria Andesa, Khusaeri ANDRIANSYAH Arie Zella Putra Ulni Arkan, M Alif Baidarus Bambang Sugiantoro Bayu Anugerah Putra Br Bangun, Elsi Titasari Dasrizal Daud, Kauthar Mohd Deprizon, Deprizon Desti Mualfah Deyola Shifana Diah Angraina Fitri Diah Angraini Putri Dian Utami Didik Sudyana Edi Ismanto Eka Putra Eka Ramadhan Elsa Yuniarti Erna M.Si Juita S.Pd Evans Fuad Fakhira Frisya Ramadhani Falda Dimantara Fatma, Yulia Febby Apri Wenando Fitri Handayani Fitria Aini, Fitria Fransiskus Zoromi, Fransiskus Gunawan, Rahmad Hadi Nasbey Hafid, Afdhil Hanum Salsabila Hari Sepdian Harun Mukhtar Hasanuddin Hasanuddin Hayami, Regiolina Hendri, Yusriadi Herianto Herianto Hul Hasanah, Sifa Ibrahim, Mohd Hairy Ilham Firdaus Irzi Gunawan Januar Al Amien Januar Al Amien Jihan Aulia Kultum, Fi Ardhi Laksono Trisnantoro Lisman, Muhammad Mas’yuri, Dhina Nurriska Md Saleh, Nurul Izrin Miftakhul Jannah Mikdad Amseno Mohamad, Mohd Saberi Mohd Daud, Kauthar Muhammad Fajri Jamil Muhammad Hamadi Muzahaffar, Fatih Al Nengsih, Rafni Yulia Prastiwi, Adila Pramudiah Putra, Reza Tanujiwa Rahmad Firdaus Rahmad Firdaus Rahmaddeni Rahmaddeni Ramadhanti, Nurul Randra Aguslan Pratama Remli, Muhammad Akmal Reny Medikawati Taufik Ricinur Ricinur Rico Apriandika Ridhollah, Farhan Rinaldi Rinaldi Rizki Anwar Rizki, Yoze Rizky Rahman Salam Septiana Srinandini Sofhia Mohnica Sunanto Sunanto Sy, Yandiko Saputra Torkis Nasution Unik, Mitra Vanama, Melsa Wan Salihin Wong, Khairul Nizar Syazwan Yogi Alfinaldo Yoze Rizki Yudi Prayudi Yulia Fatma Yulia Fatma Yusril Ibrahim