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All Journal International Journal of Electrical and Computer Engineering Voteteknika (Vocational Teknik Elektronika dan Informatika) Jurnal Teknologi Informasi dan Ilmu Komputer JAIS (Journal of Applied Intelligent System) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Dinamisia: Jurnal Pengabdian Kepada Masyarakat INTEK: Informatika dan Teknologi Informasi Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Applied Technology and Computing Science Journal Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Infotekmesin Indonesian Journal of Electrical Engineering and Computer Science Journal of Innovation Information Technology and Application (JINITA) Journal of Community Development Jurnal Ekonomi dan Teknik Informatika Jurnal Abdi Panca Marga Damhil: Jurnal Pengabdian kepada Masyarakat Pengabdian: Jurnal Abdimas
Nur Wachid Adi Prasetya
Politeknik Negeri Cilacap
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Nursing Physics Public Health Social Sciences Other

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Perbandingan Kinerja Algoritma Random Forest, Support Vector Machine, dan Naive Bayes Pada Klasifikasi Judul Skripsi Menggunakan Variasi N-Gram Nur Wachid Adi Prasetya; Ike Yunia Pasa
Infotekmesin Vol 17 No 2 (2026): Infotekmesin: Juli 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/

Abstract

Choosing a thesis topic remains challenging because many students struggle to select an appropriate research title. Thesis title classification can support this process by helping identify suitable research areas. Although classification algorithms have been widely applied in sentiment analysis, comparative studies of Random Forest, Support Vector Machine (SVM), and Naive Bayes, for thesis title classification using N-Gram features remain limited. This study compares these algorithms through text preprocessing, TF-IDF-based N-Gram feature extraction, and evaluation using confusion matrices and processing time. The dataset consists of 96 thesis titles classified into four categories: Information Systems, Multimedia, Networks, and IoT & Artificial Intelligence. The results show that SVM achieved the best performance, with 80% accuracy, 89% precision, 80% recall, an F1-score of 81.46%, and a processing time of 0.003 seconds, indicating that SVM is the most effective algorithm for thesis title classification compared with Naive Bayes and Random Forest.
Improving Diagnostic Accuracy on Prescription Text Data Using SMOTE-Optimized SVM Linda Perdana Wanti; Nur Wachid Adi Prasetya; Riyadi Purwanto; Rahmat Mulyadi; Akmal Fauzan Ananta
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 2 (2026): April 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i2.7441

Abstract

Disease classification based on drug prescription data plays a crucial role in helping healthcare professionals understand patient health conditions and supporting clinical decision-making. Drug prescription data actually contains a wealth of information regarding disease indications, but is generally presented in unstructured, free-text form. Furthermore, the data distribution across disease classes is often imbalanced, with some diseases receiving less data than others. This can lead to inaccurate classification models that favor disease classes with more data. This study aims to enhance the performance of disease classification based on drug prescription data by combining text mining approaches, the Synthetic Minority Oversampling Technique (SMOTE), and the Support Vector Machine (SVM) algorithm. The research process begins with text preprocessing, which includes case folding, tokenization, stopword removal, and stemming, to clean and normalize the prescription data. Next, the text data is converted into numeric features using the Term Frequency–Inverse Document Frequency (TF-IDF) method to enable processing by machine learning algorithms. To address the class imbalance issue, the SMOTE method is applied to training data by generating synthetic data for a limited number of disease classes. A classification model was then built using the SVM algorithm, known to be effective in handling high-dimensional text data. Model performance was evaluated using accuracy, precision, recall, and F1-score metrics. The results showed that the application of SMOTE and parameter optimization in Support Vector Machine significantly improved classification performance, with an accuracy of 92.6%, a precision of 91.8%, a recall of 93.4%, and an F1-score of 92.6%. The increased recall value in the class of patients diagnosed with diabetes indicates that the model is able to correctly identify most diabetes cases based on medical prescription data.
Integrasi LBS dan WhatsApp pada Sistem Informasi Transaksi Multi-Cabang Zisue dengan Model RAD Andesita Prihantara; Erlangga Widhi Pramono; Nur Wachid Adi Prasetya
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 15, No 3 (2026): Juni 2026
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v15i3.3607

Abstract

Zisue Restaurant confronts operational hurdles owing to human ordering via WhatsApp, which can result in recording errors, difficulties managing several branches, and the lack of an autonomous delivery cost calculation system. The goal of this study is to include Location-Based Service (LBS) features and WhatsApp notifications into a website-based transaction information system. This system was created utilising the Rapid Application Development (RAD) paradigm, with stages including requirements planning, user interface design, incremental construction, and implementation. Google Maps API is utilised to calculate delivery costs automatically depending on distance, and WhatsApp Gateway is used to provide real-time order status messages. Testing findings demonstrate that the system can reliably compute shipping prices, provide order confirmation notifications in less than 5 seconds, and centrally handle transaction data across all branches. The findings of this study suggest that combining LBS and WhatsApp with the RAD strategy improved operational efficiency and service transparency at Zisue Restaurant.Keywords: LBS; WhatsApp Notification; Transaction System; Multi-branch; Rapid Application Development AbstrakRestoran Zisue menghadapi kendala operasional karena pemesanan dilakukan secara manual melalui WhatsApp, yang dapat mengakibatkan kesalahan pencatatan, kesulitan mengelola beberapa cabang, dan kurangnya sistem perhitungan biaya pengiriman otomatis. Tujuan penelitian ini adalah untuk memasukkan fitur Layanan Berbasis Lokasi dan notifikasi WhatsApp ke dalam sistem informasi transaksi berbasis situs web. Sistem ini dibuat dengan menggunakan paradigma Pengembangan Aplikasi Cepat, dengan tahapan termasuk perencanaan kebutuhan, desain antarmuka pengguna, konstruksi bertahap, dan implementasi. Google Maps API digunakan untuk menghitung biaya pengiriman secara otomatis berdasarkan jarak, dan WhatsApp Gateway digunakan untuk memberikan pesan status pesanan secara real-time. Hasil pengujian menunjukkan bahwa sistem dapat menghitung harga pengiriman dengan andal, memberikan notifikasi konfirmasi pesanan dalam waktu kurang dari 5 detik, dan menangani data transaksi secara terpusat di semua cabang. Temuan penelitian ini menunjukkan bahwa penggabungan LBS dan WhatsApp dengan strategi RAD meningkatkan efisiensi operasional dan transparansi layanan di Restoran Zisue. 
English Learning Assistance Using Interactive Media for Children with Special Needs to Improve Growth and Development Linda Perdana Wanti; Annisa Romadloni; Oman Somantri; Laura Sari; Nur Wachid Adi Prasetya; Anne Johanna
Pengabdian: Jurnal Abdimas Vol. 1 No. 2 (2023)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/abdimas.v1i2.155

Abstract

Background. Children with special needs (ABK) are children who are in several ways different from other children in general. Among the crew members are Special Children (ALB), which consists of children who are blind, deaf, mentally retarded, quadriplegic, mentally disabled and double disabled. Some of the main things that need to be considered in the learning process for ALB are teachers, learning methods, learning approaches, infrastructure and learning support media (teaching aids). Purpose. The purpose of this community service activity is to solve the problems faced by partners in the English learning process, namely when a disorder results in disruption in daily functioning, especially in learning, the student requires special services (children with special educational needs) and requires specific learning methods in addition to appropriate and interactive learning media. Method. The solution offered to overcome this problem is the optimization of teaching methods. The recommended approach in the English language assistance activities for the Cilacap State Polytechnic PkM Team is in the form of prompts and demonstrations. Meanwhile, teaching English can use total physical response (TPR) by maximizing lip reading technique in addition to maximizing the use of flash cards to attract students' interest and focus. Results. The results obtained from this community service activity are increasing the ability of children with special needs to say a few simple words in English. The growth and development of children with special needs increase after the community service activities are completed. This is shown from the evaluation results carried out by the service team by conducting a post-test on ABK. Conclusion. To get significant results, namely increasing the growth and development of ABK, especially in the pronunciation of words in English, it is better if this activity is carried out regularly in the future.
Wood Waste Crushing Machine Training at BUMDes Banjarwaru Sejahtera Linda Perdana Wanti; Nur Akhlis Sarihidaya Laksana; Unggul Satria Jati; Roy Aries Permana Tarigan; Bayu Aji Girawan; Radhi Ariawan; Nur Wachid Adi Prasetya; Ganjar Ndaru Ikhtiagung
Pengabdian: Jurnal Abdimas Vol. 2 No. 3 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/abdimas.v2i3.847

Abstract

Background. BUMDes Banjarwaru Sejahtera is a business owned and managed by the people of Banjarwaru Village, Cilacap Regency. Some of the businesses that have been managed by BUMDes Banjarwaru Sejahtera include renting molen machines and making handicrafts such as broom handles and woven bamboo household crafts which produce an abundance of wood waste left over from the production process. So far, this wood waste has been sold to tofu craftsmen as fuel for the tofu production process. Purpose. People can use wood waste as added value by processing wood waste into handicrafts that have high economic value so that they can improve the welfare of the people of Banjarwaru village. Through this community service activity, training will be held on the use of wood waste chopping machines so that processed wood waste can be made into handicrafts such as particle boards or other handicrafts. Method. The method used is a lecture method where the community service team who are lecturers at the Cilacap State Polytechnic provide training on the use of wood waste chopping machines to members of BUMDes Banjarwaru Sejahtera and several wood craftsmen in Banjarwaru village. Results. The results of this community service activity have had a positive impact on business development at BUMDes Banjarwaru Sejahtera. Conclusion. Through this community service activity, it can be concluded that this activity has had a positive impact on the business development of BUMDes Banjarwaru Sejahtera. Apart from this, training in the use of wood waste chopping machines can also increase the competence of wood craftsmen in Banjarwaru village so they can produce more varied crafts made from wood waste.
Co-Authors Aditya Saputra, Muhammad Bintang Agus Susanto Akmal Fauzan Ananta Alif Iftitah Alif Iftitah Andesita Prihantara Andriansyah Zakaria Andriansyah Zakaria Annas Setiawan Prabowo Anne Johanna Annisa Romadloni Awaludin, Ihza Bayu Aji Girawan Dwi Krisbiantoro, Dwi Dwi Kumara, Dimas Maulana Dwi Novia Prasetyanti Dwi Novia Prasetyanti Eka Tripustikasari Erlangga Widhi Pramono Fadillah Fadillah Furi, Syamaidzar Nadifa Ganjar Ndaru Ikhtiagung Girawan, Bayu Aji Hastuti, Hety Dwi Hijriah Fajar Muhammad Insan Ike Yunia Pasa Ikhtiagung, Ganjar Ndaru Ilham Aditya Pangestu Indonesia Isa Bahroni, Isa Jati, Unggul Satria Johanna, Anne Kristiningsih, Ari Laura Sari Lina Puspitasari Linda Perdana Wanti Linda Perdana Wanti Muhammad Nur Faiz Muhammad Ramadani Nafisa, Zahrun Nur Akhlis Sarihidaya Laksana Nur Akhlis Sarihidaya Laksana, Nur Akhlis Sarihidaya Nur Wahyu Rahadi Oman Somantri Perdana Wanti, Linda Prih Diantono Abda`u Purwaningrum, Santi Puspitasari, Lina Radhi Ariawan Rahmat Hidayat Rahmat Mulyadi Ramadani, Muhammad Ratih Hafsarah Maharrani Riyadi Purwanto Rostika Listyaningrum Roy Aries Permana Tarigan Santi Purwaningrum Sari, Laura Sarihidaya Laksana, Nur Akhlis Sarihidaya, Nur Akhlis Sri Kusumadewi Unggul Satria Jati Wanti, Linda Perdana Wittriansyah, Khoeruddin Wittriansyah, Khoerudin Zahrun Nafisa