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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Transformatika WARTA Emitor: Jurnal Teknik Elektro Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Jurnal Sosial Ekonomi Perikanan Jurnal Ilmiah Dinamika Rekayasa (DINAREK) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial Li Falah: Jurnal Studi Ekonomi dan Bisnis Islam JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Informatika Universitas Pamulang Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Nasional Komputasi dan Teknologi Informasi JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Ilmiah Sinus Jurnal Teknik Elektro Uniba (JTE Uniba) Indonesian Journal of Electrical Engineering and Computer Science JIKA (Jurnal Informatika) Jurnal Sistem Komputer dan Informatika (JSON) JUKI : Jurnal Komputer dan Informatika GANDRUNG: Jurnal Pengabdian Kepada Masyarakat Journal Informatic, Education and Management (JIEM) Jurnal Teknik Informatika (JUTIF) Infotech: Jurnal Informatika & Teknologi Jurnal Pendidikan dan Teknologi Indonesia Arkus Journal of Technology and Informatics (JoTI) Jurnal Abdi Masyarakat Indonesia Waniambey: Journal of Islamic Education International Journal Software Engineering and Computer Science (IJSECS) Prosiding Konferensi Nasional PKM-CSR Jurnal Manajemen dan Teknologi Informasi Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi Jurnal Nasional Teknologi Komputer Duta.com : Jurnal Ilmiah Teknologi Informasi dan Komunikasi Proceeding ISETH (International Summit on Science, Technology, and Humanity) Abdi Teknoyasa Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia Jurnal Informatika: Jurnal Pengembangan IT Jurnal Pengabdian Masyarakat dan Riset Pendidikan Jurnal Indonesia : Manajemen Informatika dan Komunikasi Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) The Indonesian Journal of Computer Science International Journal of Applied Mathematics and Computing. International Journal of Computer Technology and Science International Journal of Information Engineering and Science Jurnal Al-Hikmah Way Kanan Journal of Islamic Economic Laws Jurnal Pengabdian Masyarakat Terapan Nusantara Journal of Artificial Intelligence and Information Systems Dirham: Journal of Sharia Finance and Economics Journal of Engineering, Electrical and Informatics ITEJ (Information Technology Engineering Journals) Jurnal Elektronika dan Telekomunikasi
Dedi Gunawan
Universitas Muhammadiyah Surakarta
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Sentiment Analysis of Emotional Intensity as a Continuous Driver of Engagement and Algorithmic Visibility Zia Ul Rehman Zafar; Dedi Gunawan; Muhammad Saif
Nusantara Journal of Artificial Intelligence and Information Systems Vol. 2 No. 1 (2026): June
Publisher : Faculty of Engineering and Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47776/nuai.v2i1.2006

Abstract

This study investigates how emotional intensity, rather than sentiment direction, shapes engagement and algorithmic visibility in digital political discourse. Using sentiment analysis, a dataset of about 15,000 posts from Twitter (X) and YouTube was collected over a 30-day period and scored with a hybrid TextBlob, VADER, and BERT pipeline. Emotional strength (the absolute sentiment value) correlated moderately with engagement (r = 0.58, p < 0.05), whereas the directional sentiment score did not (r ≈ 0.05). Emotionally intense posts attracted about 2.4 times more engagement than neutral posts, and positive posts were the most frequent (41%) while neutral posts drew the lowest mean engagement. These results indicate that engagement-based ranking amplifies emotional magnitude over neutral or analytical content, which can narrow the diversity of visible expression. The findings give platform designers and policymakers a reproducible basis for assessing how affective dynamics shape visibility in algorithmically mediated public discourse.
Implementasi Convolutional Neural Network dan Large Language Model untuk Klasifikasi dan Deskripsi Pengenalan Pola Crochet Hernanda Lilih Kusumaningtyas; Dedi Gunawan
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 4 (2026): Juni 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i4.9699

Abstract

Crochet merupakan kerajinan tekstil dengan beragam pola yang sulit diidentifikasi secara manual karena memerlukan pengalaman dan waktu. Penelitian ini bertujuan mengembangkan sistem klasifikasi pola crochet berbasis Convolutional Neural Network (CNN) serta mengintegrasikannya dengan Large Language Model (LLM) untuk menghasilkan deskripsi pola secara otomatis dalam bahasa Indonesia. Dataset yang digunakan terdiri dari 830 citra yang dibagi ke dalam delapan kelas. Model CNN digunakan untuk ekstraksi fitur dan klasifikasi citra, kemudian hasil prediksi diteruskan ke LLM untuk menghasilkan deskripsi tekstual. Evaluasi dilakukan menggunakan metrik accuracy, precision, recall, F1-score, dan confusion matrix. Hasil pengujian menunjukkan bahwa model mencapai akurasi sebesar 93% dengan nilai macro average dan weighted average sebesar 0,93, yang mengindikasikan performa yang seimbang pada seluruh kelas, meskipun masih terdapat kesalahan pada pola dengan kemiripan tekstur. Kontribusi utama penelitian ini terletak pada integrasi CNN dan LLM dalam satu sistem multimodal yang tidak hanya menghasilkan klasifikasi, tetapi juga deskripsi pola secara otomatis. Sistem diimplementasikan dalam aplikasi berbasis web yang memungkinkan pengguna memperoleh hasil klasifikasi, confidence score, dan deskripsi secara langsung. Pendekatan ini diharapkan dapat meningkatkan efisiensi proses identifikasi pola crochet serta mendukung pengembangan sistem multimodal pada domain tekstil.
DETEKSI DINI KANKER KULIT MENGGUNAKAN CNN, DNN, DAN EFFICIENTNET: PENDEKATAN DEEP LEARNING BERBASIS WEB Shindy Maheswari; Dedi Gunawan
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6417

Abstract

Skin cancer is one of the most commonly diagnosed types of cancer globally. Early detection is crucial for improving the chances of recovery and preventing further complications. This study implements and compares three deep learning models—Convolutional Neural Network (CNN), Deep Neural Network (DNN), and EfficientNet—to detect skin cancer using the HAM10000 dataset. The research process includes preprocessing, model training, performance evaluation, and integration into an interactive web application based on Flask. Evaluation was conducted using accuracy, precision, recall, F1-score, and AUC metrics. The test results show that EfficientNet provides the best performance with a test accuracy of 78.44%, followed by CNN at 69.76%, while DNN only reaches 40.52% due to loss of spatial information. To improve interpretability, the system is also equipped with Grad-CAM visualization that highlights important areas in the lesion image that influence the model's decision. This study demonstrates that the EfficientNet architecture can provide more accurate and stable classification of skin lesions compared to the other two models. The practical implications of these results are the potential use of EfficientNet in clinical decision support systems to assist in the early detection of skin cancer in an automated, efficient, and accurate manner, particularly in healthcare facilities with limited resources.  
PERBANDINGAN CNN, RESNET50, DAN VISION TRANSFORMER UNTUK KLASIFIKASI KANKER PAYUDARA BERBASIS WEB Stella Juventia Grace; Dedi Gunawan
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6420

Abstract

This research aims to compare three deep learning algorithm-based image processing models, namely CNN, ResNet50, and Vision Transformer (ViT), in classifying breast cancer based on mammography images. The CBIS-DDSM dataset from Kaggle was used and processed through pre-processing steps such as data cleaning, image resizing, normalization, augmentation, and data splitting into training and testing sets. The models were evaluated using a 5-Fold Cross Validation scheme to ensure performance stability. The results show that ResNet50 achieved the highest accuracy of 97%, followed by CNN at 92%, and Vision Transformer at 71%. All three models were implemented into a web application using Flask to support the automatic diagnosis process. These findings are expected to help develop a faster and more accurate breast cancer detection system for medical professionals.
IMPLEMENTASI ALGORITMA FHSAR DALAM MENYEMBUNYIKAN ATURAN ASOSIASI SENSITIF PADA DATASET TRANSAKSI Cintana Rendra Salsabila; Dedi Gunawan
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7115

Abstract

Transaction data is one of the assets in the digital era that can be used to analyze consumer behavior through the application of data mining algorithms, such as association rules. Not all association rules are safe to publish because some contain sensitive information that can impact customer privacy or a company's business strategy. This study aims to implement the Fast Hiding Sensitive Association Rule (FHSAR) algorithm with an item suppression approach that removes certain items with high frequency and supports sensitive rules so that these rules no longer meet the minimum support and confidence values. Sensitive association rules are explicitly determined by the user based on a combination of items considered confidential and predetermined support and confidence values. The dataset used is a public dataset from SPMF. The algorithm implementation is carried out in the form of a Python and Flask-based web application to upload datasets, set threshold values, view suppression results, and display item support visualizations using Charts.js. Evaluation of the algorithm's effectiveness is carried out using four metrics: Misses Cost (MC), Artificial Rules (AR), Item Loss (IL), and Data Dissimilarity (DD). The test results show that the FHSAR algorithm is able to effectively hide sensitive rules with MC values ​​of 1.4%, AR of 0%, IL of 0.9%, and DD of 0.04%. The data sanitization process has minimal impact on the structure and quality of the data, so that the resulting dataset is still suitable for further analysis.
Education on Making Dishwashing Liquid Soap and Ecoprint Pounding for the Empowerment of PCM and PCNA Cadres in Kebakkramat Siti Fatimah; Ahmad M. Fuadi; Akida Mulyaningtyas; Kun Harismah; Dedi Gunawan
GANDRUNG: Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 1 (2026): GANDRUNG: Jurnal Pengabdian Kepada Masyarakat
Publisher : Fakultas Olahraga dan Kesehatan, Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/gandrung.v7i1.7318

Abstract

The Muhammadiyah Branch Management (PCM) and Nasyiatul 'Aisyiyah Branch Management (PCNA) of Kebakkramat are organizations that are active in social, religious, and cadre development activities in Karanganyar. The challenges of regeneration and strengthening cadre activities have driven the need for practical and relevant empowerment programs. These community service activities are carried out through creative economy training in the form of making liquid dish soap and ecoprinting as an effort to improve the skills and capacity of cadres. Liquid soap was chosen because it is a household necessity with broad business opportunities, while ecoprinting was chosen as an environmentally friendly craft skill that can be developed into products of artistic and economic value. The implementation methods included introduction, education, implementation, evaluation, and monitoring. The results of the activities showed an increase in the creativity and understanding of cadres in utilizing business opportunities based on practical skills. This activity also contributed to strengthening the association's independence and competitiveness and produced outputs in the form of scientific publications, documentation products, and potential intellectual property rights (IPR). This program is expected to be a strategic step in strengthening cadre capacity and supporting sustainable community empowerment.
Implementation of The Topsis Algorithm In A Car Purchase Decision-Making System Viki Julian Avinda Nur Ependi; Dedi Gunawan
Journal of Technology and Informatics (JoTI) Vol. 8 No. 1 (2026): Vol. 8 N. 1 (2026)
Publisher : Universitas Dinamika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37802/joti.v8i1.1272

Abstract

Private vehicles such as cars and motorcycles are crucial modes of transportation for the movement of goods and people. With technological advancements, car manufacturers offer a wide range of vehicles. Therefore, prospective buyers face challenges in selecting a vehicle that best suits their preferences and criteria. To tackle the issue, this study develops a practical decision support system (DSS) as a user-friendly tool for buyers, with theoretical contributions in the form of a more adaptive TOPSIS application and systematic analysis in car selection. This study focuses on collecting car-related data using 12 criteria, such as price, fuel consumption, safety, and design. The TOPSIS method is then normalized to ensure a fair and objective comparison between criteria. The results show the top alternative ranking, Suzuki 2002 (closeness score of 0.7089 in position 1), and the SUS test result of 85.6, indicating that the system is easy to use and capable of providing recommendations that align with user preferences. Therefore, this study highlights that the TOPSIS method can be an effective tool in supporting car purchase decision-making and making it easier for prospective buyers to choose the car that best suits their needs.
Pengembangan Media Sosial sebagai Sistem Informasi di MI Muhammadiyah Taraman, Sragen Yudi Wahyu W; Cahyaningtyas S W; Dedi Gunawan; Arif Surya Kusuma
ABDIKAN: Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi Vol. 5 No. 2 (2026): Mei 2026
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/abdikan.v5i2.7900

Abstract

Madrasah Ibtidaiyah Muhammadiyah (MIM) Taraman in Sragen Regency has faced challenges regarding a decline in new student enrollment due to suboptimal digital promotion strategies. Despite utilizing social media platforms, the lack of strategic management has failed to effectively attract prospective parents. This community service program aims to enhance the school's visibility through the development of a modern and interactive school information system. The implementation method employed three primary strategies: lectures, discussions, and practical simulations. The implemented solutions included the development of a school profile website integrated with AI Chatbot technology for 24/7 information services and an analytics dashboard to monitor publication effectiveness. Beyond technical aspects, the program focused on human resource capacity building through training in content management, digital branding, and technical assistance for teachers and staff. The results indicate a significant impact on the partners' digital literacy. Based on post-test data, all participants (19 individuals) expressed a clear understanding and agreement regarding the utilization of information systems and social media as effective promotional tools. The implementation of this technology is expected to expand MIM Taraman's promotional reach and increase student enrollment in the upcoming academic year.
Development of an IoT-Based Smart Health Monitoring System with Heart Attack Prediction Using the SVM (Support Vector Machine) Algorithm Untung Surapati; Dadang Iskandar Mulyana; Dedi Gunawan; Anggit Purnama
International Journal of Applied Mathematics and Computing Vol. 2 No. 3 (2025): July : International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v2i3.128

Abstract

Early detection of a potential heart attack is a crucial step in preventing sudden death from heart disease. This research aims to develop an Internet of Things (IoT)-based health monitoring system capable of measuring vital body data in real time and predicting the likelihood of a heart attack from CSV data obtained from sensors, integrated through RapidMiner as learning data using a machine learning algorithm, the Support Vector Machine (SVM). The system was built using an ESP32 microcontroller connected to a MAX30102 sensor to measure heart rate and finger oxygen levels (SpO₂), as well as a DHT22 sensor to measure temperature and humidity. The resulting data is sent to the Blynk application to display real-time data according to its parameters. The initial prediction logic was developed using a rule-based method based on medical thresholds for four vital parameters. The data was then used to train an SVM model as a classification system to detect potential heart attacks. Test results showed that the system can identify abnormal conditions with a good level of accuracy and provide early warnings based on changes in vital parameters in real time. This system is expected to be an initial solution for personal health monitoring, especially for individuals at risk of heart disease. It can be further developed with cloud integration and automatic notifications to users' devices.
IMPLEMENTASI DAN PELATIHAN SISTEM PENDAFTARAN ONLINE KARTU TANDA ANGGOTA MUHAMMADIYAH RANTING KEBAKKRAMAT Dedi Gunawan; Yunus Aris Wibowo; Sukirman; Nabil Aziz Bima Anggita; Faishal Nur Haidar Afif
Abdi Teknoyasa INPRESS Volume 7, Nomor 1, Juli 2026
Publisher : Universitas Muhammadiyah Surakarta

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

Abstract

Muhammadiyah merupakan salah satu organisasi islam terbesar yang ada di Indonesia. Organisasi ini memiliki banyak cabang dan ranting disetiap kota dan kecamatan di seluruh Indonesia. Kecamatan Kebakkramat yang terletak di kabupaten Karanganyar, Jawa Tengah memiliki pimpinan cabang Muhammadiyah (PCM) dan pimpinan ranting muhammadiyah (PRM) yang aktif melakukan berbagai kegiatan kemuhammadiyahan. Anggota Muhammadiyah di wilayah tersebut tersebar diberbagai PRM dengan total anggota hampir seribu orang. Akan tetapi, masih banyak warga Muhammadiyah di lingkungan tersebut belum memiliki kartu anggota Muhammadiyah (KTAM). Persoalan lainnya adalah proses pendaftaran KTAM masih sangat manual dimana berkas persyaratan harus dicetak dan dikumpulkan di PCM Kebakkramat. Sebagai salah satu upaya untuk mengatasi persoalan tersebut maka implementasi teknologi website dapat diterapkan untuk proses pendaftaran KTAM online yang lebih terorganisir. Sistem yang sudah dikembangkan selanjutnya disosialisasikan dengan melakukan pelatihan penggunaan sistem kepada pengurus PCM Kebakkramat dan PRM di kecamatan Kebakkramat. Proses pelatihan penggunakan aplikasi KTAM online diikuti oleh 25 peserta dan hasil pelatihan menunjukkan bahwa 100% peserta memiliki pandangan yang positif terhadap sistem yang diterapkan. Selain itu seluruh peserta berpandangan bahwa sistem mudah digunakan dan dapat membantu dalam proses pendaftaran KTAM.
Co-Authors Afrizal Putra Pratama Ahimsa Prana Aditya Ahmad Muhammad Fuadi Ahmad Rozin Ahmad. M Fuadi Ahmada Aulia Rahman Ahsanul Amal, Muhammad Ahyana Ilham Wibisono Aisyah Mutia Dawis Aji Ari Adam Akbar, Yuma Akida Mulyaningtyas Al Farisi, Mu'taz Aldafi Prana Tantri Alfian Yulianto Ali Zainal Abidin Almira Putri Wibowo Alvino Raditya Putra amal, Muhammad ahsanul Amri Zadi Hudaya Anas Faridrahman Anfaisa, Anfaisa Ibnu Danar Dana Anggit Purnama Annisa Kusumastuti Apriliana, Cindi Dila Ardhani, Rahmad Ariefin Nur Hidayat Arif Surya Kusuma Arini Nur Rohmah Arrijal Amar Ma'ruf ASRORI, M ACHMAD Avifah Hasna Nur Fadila Avisa Putri Rosyida Ayu Putri Wardhani Badrus Zaman, Akhmad Roja Bambang Sukoco Basuki, Sucipto Bimantyoso Hamdikatama Budi Santoso Cahyaningtyas S W Cintana Rendra Salsabila Dadang Iskandar Mulyana` Dandi Katerpilarifai Dandung Rahmatdhan Dasim, Dasim Devi Afriyantari Puspa Putri Dewi Sasika Rani Diah Priyawati Dimas Fajar Saputro Dinda Ghebrina Putri Dita Pratama Eka Firmansyah Ekasakti, Ganza Wajendra Fadila Aulia Kusumaningrum Fahira, Dea Fahlevi, Rezza Faishal Nur Haidar Afif Fatah Yasin Al Irsyadi fatah yasin irsyadi, fatah yasin Feri Riski Dinata Fiktor Kurnia Tafonao Fitri Kurniawan Galardhia Zain Azzahra Gilang Sri Nayaka Goestjahjanti, Francisca Sestri Hanafi, Syafiq Mahmadah Handhika, Alfian Nova Hanggaraxsha, Irwan Harisnur, Alvian Hasyim Asyari Helmi Imaduddin Hernanda Lilih Kusumaningtyas Hernanda Lilih Kusumaningtyas Hernanda, Rizka Hudzaifah, Salim Maula Husein Ihsan Cahyo Utomo Ilham Adhi Septanto Islam, Syful Ismail Setiawan Istajib Kulla Himmy’azz Ita Permatahati Ivan Pradana Ivanovick Abdurrakhman Ar Raniri Jumiana Jumiana Junizal Kaukaban Syarqi Nur Budiono Kumoro, Dwi Ferdiyatmoko Cahya Kun Harismah Kurniawan, Yogiek Indra Kusrini Kusumastuti, Annisa Lukman Hakim Luthfiana Azzalea Afifah Machsunah, Yayuk Chayatun Mahendra, Galuh Raka Meilani, Reza Miftakhul Choiri Mila Faila Sufa Minallah, Aldin Nasrun Muhammad Furqan, Muhammad Muhammad Iqbal Hafidz Muhammad Saif Muslimawati, Dinny Patria Nabil Aziz Bima Anggita Nadia, La Ode Abdul Rajab Naila Khairunnisa Nailurrachman, M. Tariq Nasor, M. Nasor Nurasiah Nurasiah Pratomo Budi Santosa Prilya Shanty Adrianie Rahman, Ahmada Auliya Rahmatika, Hamni Kamal Raka Mahendra, Galuh Ramadhan, Muhammad Rivai Putra Reza Rendian Septiawan Rifa’I , Ahmad Ritonga, Hotman Sugeng Robby Nugroho Setyawan Rohmah, Alifah Alfiatur Rosmawati Rusnilawati Sadid, Muhammad Arib Umar safridha Audi Apriliasunfity Salsabil Nuuril Awwal Salsabila Putri Wibowo Salsabilla Nuraini, Arwinda Sania Citra Palupi Saputra, Masud Adhi Sarimole, Frencis Matheos Septanto, Ilham Adhi Shindy Maheswari Sigit Setiyanto Siti Fatimah SOPAN ADRIANTO Stella Juventia Grace Sugiyono Sugiyono Sukirman Sulthon Kaffaah Al Farizzi Sutisna Sutisna Suwanto Suwanto Syamsuri Tasya Indriani Titis Sri Wulan Tri Agus Setiawan Tri Wahyudi Umar Ali Ahmad Untung Surapati Verania Nur Andika Viki Julian Avinda Nur Ependi Waqiah Wibowo, Rama Aziz Widi Widayat WINANTI, WINANTI Yasir Sidiq Yogatama Dwi Prasetya Yudi Wahyu W Yunus Aris Wibowo Yusuf Sulistyo Nugroho Zia Ul Rehman Zafar Zudana , Kirana Maharani