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Application of deep neural network with stacked denoising autoencoder for ECG signal classification Gunawan, Gunawan; Aimar Akbar, Aminnur; Andriani, Wresti
Journal of Intelligent Decision Support System (IDSS) Vol 7 No 2 (2024): June: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v7i2.247

Abstract

Applying deep neural networks with stacked denoising autoencoders (SDAEs) for ECG signal classification presents a promising approach for improving the accuracy of arrhythmia diagnosis. This study aims to develop a robust model that enhances the classification of ECG signals by effectively denoising the input data and extracting rich feature representations. The research employs a method involving data preprocessing, feature extraction using SDAEs, and classification with a deep neural network (DNN) validated on the MIT-BIH Arrhythmia Database. The results demonstrate that the proposed model achieves an impressive accuracy of 98.91%, significantly outperforming traditional machine learning methods. The implications of this research are substantial, offering a reliable and automated tool for arrhythmia diagnosis that can be utilized in clinical settings to improve patient care. The study highlights the model's potential for real-time clinical application, although further validation on more extensive and diverse datasets is necessary to confirm its generalizability and robustness. This research contributes to the field by integrating advanced SDAEs with deep learning, paving the way for more accurate and efficient ECG signal classification systems
Penerapan Metode Dobel Exponential dan Smoothing Analytical Hierarchy Process untuk Prediksi Tingkat Kerawanan Tanah Longsor Di Kabupaten Brebes Putra, Alif Sya’Bani; Surorejo, Sarif; Andriani, Wresti; Gunawan, Gunawan
Innovative: Journal Of Social Science Research Vol. 4 No. 3 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i3.10505

Abstract

Pengembangan metode prediksi tingkat kerawanan tanah longsor di Kabupaten Brebes menggunakan kombinasi double exponential smoothing dan analytical hierarchy process (AHP). Tujuan penelitian ini adalah meningkatkan pemahaman dan prediksi terhadap fenomena tanah longsor dan memanfaatkan data historis dan analisis kriteria multi-faktor. Metodologi penelitian ini melibatkan analisis seri waktu menggunakan double exponential smoothing untuk memprediksi variabel-variabel penting seperti curah hujan, dan pergerakan tanah. Sementara AHP digunakan untuk menilai dan mengintegrasikan berbagai faktor risiko tanah longsor, termasuk kondisi geologi, kemiringan lereng, dan penggunaan lahan. Hasil penelitian ini adalah model yang diusulkan mampu memprediksi tingkat kerawanan tanah longsor dengan akurasi yang lebih tinggi dibandingkan metode yang ada. Penelitian ini memberikan kontribusi penting dalam upaya mitigasi bencana tanah longsor di Kabupaten Brebes, serta membuka peluang untuk aplikasi metode serupa di wilayah lain yang memiliki risiko tanah longsor.
Perbandingan Metode Fuzzy Mamdani dan Fuzzy Tsukamoto untuk Identifikasi Tingkat Serangan Penyakit pada Tanaman Bawang Merah Hidayatullah, Bryan Adam; Nugroho, Bangkit Indarmawan; Santoso, Nugroho Adhi; Gunawan, Gunawan
Innovative: Journal Of Social Science Research Vol. 4 No. 3 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i3.10506

Abstract

Penelitian ini membandingkan metode fuzzy Mamdani dan fuzzy Tsukamoto dalam mengidentifikasi tingkat serangan penyakit pada tanaman bawang merah untuk meningkatkan deteksi dini penyakit dan produktivitas pertanian. Menggunakan dataset parameter kesehatan tanaman, termasuk gejala penyakit dan kondisi lingkungan, penelitian mengaplikasikan kedua metode fuzzy tersebut untuk memperkirakan kerentanan tanaman terhadap penyakit. Hasil menunjukkan bahwa fuzzy Tsukamoto lebih akurat dan efisien, terutama dalam data kompleks. Penelitian ini memberikan pemahaman baru dalam aplikasi fuzzy logic pada penyakit tanaman bawang merah dan pengembangan model serupa di pertanian. Temuan ini penting untuk pengembangan sistem pendukung keputusan yang lebih efisien dalam pertanian, mengintegrasikan teknologi informasi dalam manajemen kesehatan tanaman.
Optimasi Search Engine Optimization (SEO) On Page Untuk Meningkatkan Peringkat Website Hondasukabumi.com Di Google Alim Murtopo, Aang; Nursidik, Maulia; Syefudin, Syefudin; Gunawan, Gunawan
Innovative: Journal Of Social Science Research Vol. 4 No. 3 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i3.10715

Abstract

Artikel penelitian ini berjudul "Optimasi Search Engine Optimization (SEO) On Page Untuk Meningkatkan Peringkat Website Hondasukabumi.com Di Google", bertujuan untuk mengidentifikasi dan menerapkan strategi optimasi SEO On Page yang efektif dalam meningkatkan peringkat website bisnis lokal di mesin pencari Google. Menggunakan metode studi literatur dan observasi, penelitian ini fokus pada analisis kata kunci tertentu dari tahun 2020 hingga 2024 dan optimasi elemen-elemen SEO On Page seperti title tag, meta deskripsi, dan struktur heading. Hasil penelitian menunjukkan bahwa penerapan strategi SEO On Page yang ditargetkan berdasarkan analisis kata kunci dan optimasi konten relevan berhasil meningkatkan visibilitas dan peringkat website Hondasukabumi.com di hasil pencarian Google. Implikasi dari penelitian ini menekankan pentingnya SEO On Page dalam strategi pemasaran digital untuk bisnis lokal, memberikan wawasan penting bagi pemilik bisnis dan praktisi SEO dalam meningkatkan performa website di era digital.
Penerapan Metode Naïve Bayes Classifier dan Selectin Sort untuk Menentukan Peringkat Cafe Di Kota Tegal Arifiyah, Nur Latifatul; Gunawan, Gunawan; Anandianska, Sawaviyya
Innovative: Journal Of Social Science Research Vol. 4 No. 3 (2024): Innovative: Journal Of Social Science Research (Special Issue)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i3.11408

Abstract

Penelitian ini mengembangkan sistem penilaian dan peringkat untuk cafe di Kota Tegal dengan mengintegrasikan metode Naïve Bayes Classifier dan Selection Sort, bertujuan untuk menyediakan panduan objektif bagi pelanggan dalam memilih cafe berdasarkan ulasan. Tujuan utama dari penelitian ini adalah untuk meningkatkan akurasi dalam penentuan peringkat cafe, sekaligus memberikan wawasan bagi pemilik cafe untuk meningkatkan kualitas layanan dan produk mereka. Metode yang digunakan meliputi pengumpulan data ulasan pelanggan, analisis sentimen menggunakan Naïve Bayes Classifier, dan perankingan menggunakan Selection Sort. Hasil penelitian menunjukkan efektivitas kombinasi kedua metode ini dalam menghasilkan peringkat cafe yang konsisten dengan penilaian pelanggan sebenarnya. Implikasinya, sistem ini menawarkan metode yang dapat diandalkan untuk evaluasi dan perbandingan cafe, serta mendukung pemilik cafe dalam strategi peningkatan kualitas berdasarkan umpan balik pelanggan. Penelitian ini memberikan kontribusi pada penerapan metode klasifikasi dan pengurutan dalam konteks baru, membuka peluang untuk penelitian selanjutnya dalam pengembangan sistem rekomendasi di sektor lain.
Penerapan Metode Fuzzy K-Means Clustering untuk Pengelompokan Konten Halaman Web secara Otomatis Budiono, Wahyu; Nugroho, Bangkit Indarmawan; Santoso, Nugroho Adhi; Gunawan, Gunawan
Innovative: Journal Of Social Science Research Vol. 4 No. 3 (2024): Innovative: Journal Of Social Science Research (Special Issue)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i3.12022

Abstract

Penerapan Metode Fuzzy K-Means Clustering untuk Pengelompokan Konten Halaman Web Secara Otomatis adalah penelitian yang bertujuan untuk mengotomatisasi proses pengelompokan konten halaman web menggunakan pendekatan clustering fuzzy. Dalam konteks ini, algoritma Fuzzy K-Means digunakan untuk mengelompokkan konten halaman web menjadi beberapa kategori berdasarkan kesamaan karakteristik tertentu. Metode ini memanfaatkan kelebihan pendekatan clustering fuzzy dalam menangani ketidakpastian dalam data dan kemampuan K-Means dalam mengelompokkan data menjadi beberapa cluster. Penelitian ini mencakup tahapan pra-pemrosesan data, ekstraksi fitur, dan implementasi algoritma Fuzzy K-Means Clustering. Eksperimen dilakukan menggunakan dataset yang berisi konten halaman web dari berbagai domain. Hasil evaluasi menunjukkan bahwa metode ini dapat menghasilkan pengelompokan konten halaman web yang sesuai dengan karakteristiknya secara otomatis, dengan tingkat akurasi dan interpretabilitas yang baik. Implementasi metode ini dapat memberikan kontribusi signifikan dalam pengelolaan dan penyaringan konten web secara efisien.
ANALISIS PENERAPAN SMART LIVING DALAM PEMBANGUNAN SMART CITY DI KOTA TEGAL Arrohman, Zidni Dlia; Andriani, Wresti; Gunawan, Gunawan
Jurnal Cahaya Mandalika ISSN 2721-4796 (online) Vol. 4 No. 2 (2023)
Publisher : Institut Penelitian Dan Pengambangan Mandalika Indonesia (IP2MI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/jcm.v4i2.1448

Abstract

Smart City is a city that can monitor and combine the situation of all infrastructure, both physical, social and business fields. The purpose of making a Smart City design is to make the city more efficient, prolonged, balanced and appropriate to live in. This design can also be applied to programming the rules of space, area or city, not only to the handling of cases in large cities. Each programming that uses the Smart City design intends to make the city sustainable. Regarding this is synergy with the programming of the landscape of prolonged natural tourism in Tegal City. The programming of the landscape to be raised is the realization of integrity and production power as well as the base of natural energy and multifunctional creation. To create programming purposes, Smart City designs that advance the use of IT can be applied to landscape programming zones and activities to be raised. IT systems used include intelligent inspection equipment installed in landscapes, features or equipment that can associate one network with another, computerization, social tools and GIS. The markers of success are measured by smart city design applications, including better management and organization, more advanced technology, the creation of good government, stakeholders understand and can use the technology applied, the economy increases, infrastructure development is better and the presence of areas is prolonged.
Application of association rule for prediction of menu ordered at café minapadi Zain Hidayatullah, Fikri; Surorejo, Sarif; Andriani, Wresty; Gunawan, Gunawan
Jurnal Mandiri IT Vol. 12 No. 4 (2024): April: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v12i4.279

Abstract

This research aims to develop a predictive model that helps prepare menus based on customer preferences at Café Minapadi, hoping to improve operational efficiency and customer satisfaction. Using rule-association data mining techniques, the study uncovered hidden patterns in extensive transaction data, applying a priori algorithms in datasets to explore menu ordering frequencies and trends. Data analysis includes cleansing, transforming, and selecting features to generate relevant insights. The results found that items such as coffee and chocolate cake were often purchased together, providing an opportunity for menu optimization and special promotions. Evaluation of predictive models shows the possibility of increased accuracy in stock preparation and adjustment of menu offerings, providing significant benefits in business decision-making in the culinary sector.
Application of expert system using certainty factor method to identify diseases in rice plants Azmi, Isni; Gunawan, Gunawan; Anandianskha, Sawaviyya
Jurnal Mandiri IT Vol. 12 No. 4 (2024): April: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v12i4.280

Abstract

This article explores the application of expert systems using certainty factor methods for disease identification in rice crops, highlighting the importance of information technology integration in agriculture. The study aims to develop a system that allows quick and accurate identification of rice disease, using certainty factor methods that are effective in dealing with data uncertainty. This study used a quantitative approach with a quasi-experimental design. The results indicate an effective system for identifying diseases, with significant implications for supporting farmers and improving food security. Suggestions for future research include system integration with mobile applications and real-time data analysis to improve system accessibility and applicability in modern agricultural practices.
Application of apriori algorithm to find relationships between courses based on student grades STMIK YMI Tegal Hassan, Muhamad Nur; Gunawan, Gunawan; Arif, Zaenul
Jurnal Mandiri IT Vol. 12 No. 4 (2024): April: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v12i4.281

Abstract

This research explores the application of the Apriori algorithm to investigate the relationship between courses based on student grades at STMIK YMI Tegal. This research focuses on analyzing the relationship between courses to support curriculum development that is responsive and relevant to industry needs and improves the quality of learning. The main objective of this research is to identify and understand relationship patterns between various courses based on student analysis scores using the Apriori algorithm, an effective data mining methodology for uncovering association rules between items in large datasets. By using a quantitative approach and quasi-experimental design, this research succeeded in analyzing grade data from various semesters, identifying combinations of courses that often appear together with high grades, indicating a positive correlation between related courses. The results of the analysis reveal that several basic courses play a significant role in forming a strong foundation for advanced courses, highlighting the importance of a capable curriculum structure. Although the lift scores show a neutral relationship, these findings provide important initial insights for further understanding of interactions between courses. The implication for curriculum development is the need to emphasize the integration of courses that have positive relationships to support a coherent learning process and increase student success.
Co-Authors Aang Alim Murtopo Aditdya, Maulana Ahmad Zulfikri Aimar Akbar, Aminnur Aisyach Aminarti Santoso Al Fattah, Muhammad Raikhan Alan Eka Prayoga Albana, Muhammad Syifa Ali Murtopo, Aang Amalani, Mukhamad Zulfa Bakhtiar Ananda, Pingky Septiana Anandaianskha, Sawaviyya Anandianshka, Sawaviyya Anandianska, Sawaviyya Anandianskha, Sawaviyya Andriani, Wresti Andriani, Wresty Anshori, Abu Hasan Al Arif, Zaenul Arifiyah, Nur Latifatul Arrohman, Zidni Dlia Aslam, Muhammad Nur Aziz, Taufiq Azmi, Isni Azmi, Muchamad Nauval Bangkit Indarmawan Nugroho Budiono, Wahyu Cahyo, Septian Dwi Catur Supriyanto Dari, Mayang Melan Dewi, Errika Mutiara Didiek Trisatya Dodi Setiawan Dodi Setiawan Dwi Fina Fahirah Dwi Kurniawan, Rifki Fadila, Nurul Fahirah, Dwi Fina Fanti, Azizah Permata Farkhan, Muhammad Fatkhurrohman Fatkhurrohman, Fatkhurrohman Firmansyah, Akhmad Lutfi Firmansyah, Hasbi Firmansyah, Muchamad Aries Gunawan Gunawan Hafid Subechi, Fadlan Handayani, Sri Harefa, Reyvan Sinatria Haris Fadillah Hassan, Muhamad Nur Hidayatullah, Bryan Adam Intan Mayla Faiza Intan Mayla Faiza Januarto, Sigit Khadziqul Humam Munfi Khasanah, Apriliani Maulidya Khusni, Muhammad Wazid Kurniawan, Rifki Dwi Limaknun, Lulu Lutfayza, Rezi Maulana, M Taufik Fajar Miftakhuddin, Ahmad Miftakhudin, Muhammad Mohamad Rifki Septiadi Mohammad Amin Triwinanto Triwinanto Moonap, Dinar Auranisa Muchamad Nauval Azmi Muh Ridwan Muhammad Sulthon Mutaqin, Ahadan Fauzan Muttaqin, Anik Naja, Naella Nabila Putri Wahyuning Ningrum, Isna Lidia Nughroho, Bangkit Indarmawan Nugroho Adhi Santoso Nur Tulus Ujianto Nurokhman, Akhmad Nursahid, Wahyu Nursidik, Maulia Nurul Fadhilah Nurul Fadilah, Nurul Prayoga, Alan Eka Priyo Haryoko Purwanto Purwanto Putra, Alif Sya’Bani Qurrotu Aini, Atikah Rafhina, Ana Ramadhan, Ilham Gema Rifki Dwi Kurniawan Rivaldiansyah, Rafik Riyadi, Fajar Sugeng Santoso, Aisyach Aminarti Santoso, Bayu Aji Santoso, Nughroho Adhi Santoso, Nugroho Adh Santoso, Nugroho Adhi Santoso, Nugroho Adi Saputra, Aryan Dandi Sarif Surorejo Sawaviyya Anandianskha Sawaviyya Anandianskha Sawaviyya Anandianskha Sawavyya Anandianskha Septian Ari Wibowo Septiana Ananda, Pingky Septiana, Pingky Surur, Misbahu Sya’bani, Adhita Zulfa Syefudin, Syefudin Ubaidillah, Muhamad Rizal Ujianto, Nur Tulus W.N, Naella Nabila Putri Wahyu Pratama, Raka Wahyuning Naja, Naella Nabila Putri Wilda Shabrina Windi Setiawati Wresti Andriani Wresti Andriani Wresti Andriani Yan Kurniawan Yan Kurniawan, Yan Yulison Herry Chrisnanto Zaenul Arif Zain Hidayatullah, Fikri Zain, Ahmad Muzakky