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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Pengabdian UntukMu NegeRI RABIT: Jurnal Teknologi dan Sistem Informasi Univrab CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro Seminar Nasional Teknologi Informasi Komunikasi dan Industri JITK (Jurnal Ilmu Pengetahuan dan Komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA IJISTECH (International Journal Of Information System & Technology) EDUMATIC: Jurnal Pendidikan Informatika Jurnal Pengabdian Kepada Masyarakat MEMBANGUN NEGERI Journal of Electronics, Electromedical Engineering, and Medical Informatics Indonesian Journal of Electrical Engineering and Computer Science Computer Science and Information Technologies Journal of Education Informatic Technology and Science Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) IJISTECH Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Pendidikan dan Teknologi Indonesia SATIN - Sains dan Teknologi Informasi Jurnal Pendidikan Dirgantara
Edi Ismanto
Universitas Muhammadiyah Riau
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Pengembangan Media Pembelajaran Berbasis Game Edukasi Tema 4 Tentang Bangun Ruang Di Kelas 2 SD Bella, Bella Fitria Sari; Melly Novalia; Edi Ismanto
Computer Science and Information Technology Vol 5 No 2 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i2.7529

Abstract

Learning media at SD Negeri 164 Pekanbaru City refers to blackboards and books that are already available, but do not yet have effective learning strategies. Lack of student interest in learning in the teaching and learning process which is not in accordance with the current development and needs of students. With increasingly advanced and rapid technological developments, humans can create various tools to carry out activities that support productivity. Like making educational game learning media. This research aims to produce a learning media product for the snakes and ladders educational game theme 4 about building space and to determine the feasibility test, practicality and effectiveness of the educational game snakes and ladders theme 4 about building spaces in class 2 of SD Negeri 164 Pekanbaru City. The research method used is the Research and Development (R&D) research method with the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) development model. In the feasibility test, an assessment is carried out by two experts, namely a media expert and a material expert to determine the suitability of the product. Where the results of the feasibility test for media experts got a result of 82% in the "Very Good" category and for material experts a result of 93% in the "Very Good" category. In the practicality test, it was carried out by teachers and students, where the teacher got a practicality result of 93% in the "Very Practical" category and the students got a result of 80% in the "Practical" category. The effectiveness test was carried out by giving pretest and post-test questions, where the pretest got a result of 64% and the post-test got a result of 92.2%. So this learning media is feasible, practical and effective to use to support teaching and learning activities.
A Comparative Study of Improved Ensemble Learning Algorithms for Patient Severity Condition Classification Edi Ismanto; Abdul Fadlil; Anton Yudhana; Kitagawa, Kodai
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 6 No 3 (2024): July
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v6i3.452

Abstract

The evolution of Electronic Health Records (EHR) has facilitated comprehensive patient record-keeping, enhancing healthcare delivery and decision-making processes. Despite these advancements, analyzing EHR data using ensemble machine learning methods poses unique challenges. These challenges include data dimensionality, imbalanced class distributions, and the need for effective hyperparameter tuning to optimize model performance. The study conducted a thorough comparative analysis of various ensemble machine learning (EML) models using Electronic Health Record (EHR) datasets. After addressing data imbalance and reducing dimensionality, the accuracy of the EML models showed significant improvement. Notably, the Gradient Boosting Machine (GBM) and CatBoost models exhibited superior performance with an accuracy of 73%, achieved through experiments involving dimensionality reduction and handling of imbalanced data. Furthermore, optimization techniques such as Grid Search and Random Search were employed to enhance the EML models. The results of model optimization revealed that the GBM + Random Search model performed the best, achieving an accuracy of 74%, followed by the XGBoost + Grid Search model with an accuracy of 73%. The GBM model also excelled in distinguishing between positive and negative classes, boasting the highest Area under Curve (AUC) value of 0.78, indicative of its superior classification capabilities compared to other models. This study emphasizes the significance of incorporating cutting-edge EML techniques into clinical workflows and emphasizes the revolutionary potential of GBM in classification modeling for patient severity conditions. Future research should focus on deep learning (DL) applications and the integration of these models.
Pemanfaatan Digital Marketing untuk Memperluas Strategi Pemasaran Produk Furniture dari Bahan Kayu Rubber Ismanto, Edi; Januar Al Amien; Hammam Zaki; Eka Pandu Cynthia
Jurnal Pengabdian UntukMu NegeRI Vol 8 No 1 (2024): Pengabdian Untuk Mu negeRI
Publisher : LPPM UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jpumri.v8i1.5720

Abstract

The COVID-19 pandemic, which has affected Indonesia for the past three years, has had a significant negative impact on a number of industries, including the Micro, Medium, and Small Enterprises (MSME) sector, which has been particularly hard hit. Pekanbaru City has 105,445 MSMEs, with data indicating that there are as many as 1,034 MSMEs, which produce a range of goods used by the community, including furniture products and various wood-based office and home furnishings. Of course, if development is carried out for MSME wood craftsmen, this is a potential aspect for the City of Pekanbaru. UMKM Furniqa Woodcraft as a raw material to create furniture items like chairs, tables, cabinets, and various other handicraft products uses rubber wood. However, there has been a significant drop in sales since the Covid-19 pandemic, so a solution must be found. In an effort to increase product marketing, service activities performed include training and assisting with managing Digital Marketing. This activity is implemented using a variety of approaches, including the Interview and Discussion Method, the Training Method, and the Evaluation Method. The evaluation of the implementation of digital marketing training and mentoring showed that employees at Furniqa Woodcraft had increased knowledge competence by 75.875%.
Analisis Perbandingan Model Fully Connected Neural Networks (FCNN) dan TabNet Untuk Klasifikasi Perawatan Pasien Pada Data Tabular Ismanto, Edi; Abdul Fadlil; Anton Yudhana
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Electronic Health Records (EHR) store tabular data that is rich in information and play a critical role in supporting decision-making within the healthcare field, particularly for patient care classification. This study evaluates the performance of two artificial intelligence models, Fully Connected Neural Networks (FCNN) and TabNet, in processing tabular data for patient care classification tasks. The findings reveal that both models demonstrate strong performance, with TabNet showing a slight advantage. TabNet achieves an accuracy of 0.74, marginally surpassing FCNN's 0.73. Furthermore, TabNet excels in precision (0.74 vs. 0.72), recall (0.72 vs. 0.71), and F1-Score (0.73 vs. 0.71), highlighting its greater reliability in minimizing false positives and accurately detecting positive cases with a better balance between precision and recall. With its architecture specifically tailored for tabular data and its capacity for direct interpretability, TabNet offers enhanced efficiency and ease of implementation compared to FCNN, which demands more complex data preprocessing. For future research, it is suggested to employ larger and more diverse datasets, explore data with higher feature complexity, and conduct comprehensive hyperparameter tuning to further improve the performance of both models.
Efektivitas Sosialisasi Listrik Aman dan Hemat pada Mahasiswa melalui Pretest dan Posttest Menggunakan Google Form Tri Wahono; Ismanto, Edi; Nuraeni, Eneng; Yudhana, Anton; Herman
Jurnal Pengabdian Kepada Masyarakat MEMBANGUN NEGERI Vol. 8 No. 2 (2024): Jurnal Pengabdian Kepada Masyarakat MEMBANGUN NEGERI
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35326/pkm.v8i2.6394

Abstract

Sosialisasi mengenai penggunaan listrik yang aman dan hemat menjadi semakin penting dalam konteks modern, mengingat berbagai tantangan dan kebutuhan yang dihadapi masyarakat saat ini. Beberapa faktor utama yang melatarbelakangi upaya sosialisasi ini meliputi kebutuhan akan keselamatan, efisiensi energi, penghematan biaya. Kurangnya pengetahuan tentang pengetahuan mengenai penggunaan listrik yang benar mengakibatkan insiden kecelakaan listrik. Sosialisasi ini bertujuan untuk menganalisis efektivitas sosialisasi tentang listrik yang aman dan hemat pada mahasiswa pendidikan Universitas Muhammadiyah Riau. Sosialisasi dilakukan untuk meningkatkan pemahaman dan kesadaran mahasiswa terhadap penggunaan listrik yang lebih bijaksana dan aman. Metode penelitian yang digunakan adalah pemberian materi secara langsung kemudian untuk mengukur pemahaman mahasiswa menggunakan pre-test dan post-test. Alat pengumpulan data berupa kuesioner yang disebarkan melalui Google form, yang mencakup pertanyaan terkait pengetahuan dan perilaku dalam penggunaan listrik sebelum dan sesudah sosialisasi. Hasil dari 49 responden yang mengisi kuesioner dengan 15 pertanyaan, analisis statistik mengungkapkan bahwa intervensi yang diberikan memiliki efek positif yang signifikan terhadap pengetahuan atau keterampilan responden. Hal ini dibuktikan dengan nilai p yang lebih kecil dari 0,05. Dapat disimpulksn bahwa kegiataan sosialisasi terbukti efektif dalam meningkatkan pemahaman atau kemampuan responden secara cepat.
Sosialisasi & Edukasi: Optimalisasi Bakat dan Minat Siswa Berbasis Sistem Pakar Dengan Pendekatan Artificial Intelligence Ismanto, Edi; Vitriani; Ajeng Safitri
Jurnal Pengabdian UntukMu NegeRI Vol 8 No 3 (2024): Pengabdian Untuk Mu negeRI
Publisher : LPPM UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jpumri.v8i3.7947

Abstract

Di tengah era digital, pentingnya pendidikan yang dapat mempersiapkan generasi muda untuk tantangan global sangat nyata, terutama dalam konteks pengembangan potensi individu. Banyak siswa yang kurang mendapatkan bimbingan yang tepat, sehingga kemampuan mereka tidak termanfaatkan secara maksimal. Optimalisasi bakat dan minat siswa berbasis sistem pakar di SMPN 16 Pekanbaru bertujuan untuk mengatasi kesenjangan dalam identifikasi dan pengembangan bakat siswa. Dengan menerapkan sistem pakar berbasis Artificial Intelligence (AI), kegiatan ini menawarkan solusi inovatif untuk mendeteksi dan mengarahkan bakat serta minat siswa secara lebih objektif. Kegiatan mencakup seminar edukasi yang mengenalkan konsep bakat dan minat, serta pelatihan praktis dalam penggunaan sistem pakar. Evaluasi efektivitas program menunjukkan peningkatan pemahaman peserta sebesar 77.5%, dengan analisis t-test yang mengindikasikan dampak positif yang signifikan. Temuan ini mempertegas bahwa integrasi teknologi dalam pendidikan sangat penting untuk mendukung pengembangan bakat siswa, sehingga mereka dapat menjadi individu yang lebih percaya diri dan berdaya saing tinggi di masyarakat global.
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.
Penguatan Pendidikan Karakter Siswa Melalui Tujuh Kebiasaan Anak Indonesia Hebat di SMK Negeri 3 Pekanbaru Amelia Agustina; Edi Ismanto
Jurnal Pendidikan Dirgantara Vol. 2 No. 1 (2025): Jurnal Pendidikan Dirgantara
Publisher : Asosiasi Riset Ilmu Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/jupendir.v2i1.196

Abstract

Character education is one of the important aspects in forming a good personality in each individual. Good character will have a positive impact on the social, emotional, and academic life of students. The 7 Habits of Great Indonesian Children Movement Program is designed as a strategic step to form individuals who are not only academically intelligent, but also have strong characters that are the foundation of the nation's success in the future. The main objective of this movement is to create a golden generation of Indonesia in 2045. By instilling positive habits from an early age, it is hoped that Indonesian children can grow into healthy, intelligent, characterful individuals who contribute positively to the nation and state. One of the State Vocational Schools in Pekanbaru has implemented the 7 habits of great Indonesian children movement, namely at State Vocational School 3 Pekanbaru.
A Comparison of Enhanced Ensemble Learning Techniques for Internet of Things Network Attack Detection Edi Ismanto; Januar Al Amien; Vitriani Vitriani
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 3 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i3.3885

Abstract

Over the past few decades, the Internet of Things (IoT) has become increasingly significant due to its capacity to enable low-cost device and sensor communication. Implementation has opened up many new opportunities in terms of efficiency, productivity, convenience, and security. However, it has also brought about new privacy and data security challenges, interoperability, and network reliability. The research issue is that IoT devices are frequently open to attacks. Certain machine learning (ML) algorithms still struggle to handle imbalanced data and have weak generalization skills when compared to ensemble learning. The research aims to develop security for IoT networks based on enhanced ensemble learning by using Grid Search and Random Search techniques. The method used is the ensemble learning approach, which consists of Random Forest (RF), Adaptive Boosting (AdaBoost), Gradient Boosting Machine (GBM), and Extreme Gradient Boosting (XGBoost). This study uses the UNSW-NB15 IoT dataset. The study's findings demonstrate that XGBoost performs better than other methods at identifying IoT network attacks. By employing Grid Search and Random Search optimization, XGBoost achieves an accuracy rate of 98.56% in binary model measurements and 97.47% on multi-class data. The findings underscore the efficacy of XGBoost in bolstering security within IoT networks.
Pengembangan Game Edukasi Interaktif Berbasis Android Untuk Mendukung Proses Pembelajaran Siswa Sekolah Menengah An Nikmah Al Islamiyah Kamboja Herdani, Inka Friska; Ismanto, Edi; Novalia, Melly; Syahfutra, Wandi
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 4 (2025): JPTI - April 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.818

Abstract

Penelitian ini bertujuan untuk mengembangkan game edukasi berbasis Android sebagai media pembelajaran jaringan komputer dasar di sekolah menengah An-Nikmah Al-Islamiyah Phnom Penh. Pengembangan dilakukan menggunakan model 4D yang terdiri dari tahapan Define, Design, Develop, dan Disseminate. Metode pengujian melibatkan validasi oleh ahli media, ahli materi, dan ahli bahasa serta uji coba kepada siswa dan guru untuk menilai aspek kelayakan dan praktikalitas. Data dikumpulkan melalui observasi, wawancara, dan angket, kemudian dianalisis secara kuantitatif menggunakan skala Likert untuk mengukur tingkat validitas dan efektivitas media pembelajaran.Hasil penelitian menunjukkan bahwa game edukasi yang dikembangkan memiliki tingkat kelayakan sangat tinggi dengan skor validasi ahli media sebesar 87%, ahli materi 79%, dan ahli bahasa 84%. Evaluasi praktikalitas oleh guru dan siswa juga memberikan hasil positif dengan persentase masing-masing 90% dan 81%. Penggunaan game edukasi ini meningkatkan keterlibatan siswa dalam pembelajaran serta memberikan pengalaman belajar yang lebih interaktif dan mandiri. Selain itu, game edukasi ini berkontribusi terhadap pengembangan pendidikan berbasis teknologi dengan menyediakan alternatif pembelajaran digital yang menarik dan mudah diakses.Penelitian ini memberikan dasar bagi pengembangan lebih lanjut dalam integrasi teknologi dalam pembelajaran, terutama dalam meningkatkan pemahaman siswa terhadap konsep jaringan komputer dasar. Pengujian lebih luas dan jangka panjang direkomendasikan untuk mengoptimalkan efektivitas media ini dalam berbagai konteks pendidikan.
Co-Authors Abdul Fadlil Adam Ramadhan Agus Satria Ajeng Safitri Al Rian, Rahmad Ambiyar, Ambiyar Amelia Agustina Amran, Hasanatul Fu'adah Anton Yudhana Bella, Bella Fitria Sari Deprizon, Deprizon Diah Eka Ratna Diva Arifal Adha Dwi Sanggar Wati, Anisa Effendi, Noverta Eka Pandu Cynthia Eka Pandu Cynthia Eka Pandu Cynthia Erik Suanda Handika Gunawan, Rahmad Habil Maulana Hadhrami Ab Ghani Hadhrami Ab. Ghani Hammam Zaki Harun Mukhtar Herdani, Inka friska Herlandy, Pratama Benny Herman Januar Al Amien Januar Al Amien Januar Al Amien Khairul Anshari Kitagawa, Kodai Lisman, Muhammad Melly Novalia Melly Novalia Melly Novalia, Melly Mohamad, Mohd Saberi Nuraeni, Eneng Nurul Izrin Binti Md Saleh Nurul Izrin Md Saleh Nurul Safira, Natasya Oriana, Larisa Patlan Putra Humala Harahap Pratama Benny Herlandi Pratama Benny Herlandy Putri Ramahdani, Anggi Rahmad Al Rian Rahmad Al Rian Rahmad Alrian Rahmad Gunawan Gunawan Remli, Muhammad Akmal Renita Rahmadani Resmi Darni Ridhollah, Farhan Septian Alza Siti Niah Soni Sri Fitria Retnawaty Sunanto Sunanto Suryadila, Lusi Tri Wahono Vitriani Vitriani Vitriani Vitrian Wan Salihin Wong, Khairul Nizar Syazwan Wandi Syahfutra Yeeri Badrun