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All Journal Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) Telematika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Sinkron : Jurnal dan Penelitian Teknik Informatika CogITo Smart Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Journal of Education Technology Jurnal Tekno Insentif JURTEKSI Building of Informatics, Technology and Science Infotekmesin Journal of Information Systems and Informatics Jurnal Sistem Komputer dan Informatika (JSON) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Journal of Applied Data Sciences Jurnal Pendidikan dan Teknologi Indonesia Jurnal Pengabdian Masyarakat Indonesia Jurnal Ilmu Komputer dan Teknologi (IKOMTI) Jurnal Pengabdian Mitra Masyarakat (JPMM) Electronic Journal of Education, Social Economics and Technology Bulletin of Social Informatics Theory and Application Jurnal Riset Teknik Komputer CSRID Southeast Asia Journal on Open and Distance Learning
Rujianto Eko Saputro
Universitas Amikom Purwokerto
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering 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 Nursing Public Health Social Sciences Veterinary Other

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Aplikasi Damai : Desain Persuasif Aplikasi Konsultasi Kesehatan Mental Berbasis Mobile Menggunakan User Centered Design Indriyani, Ria; Eko Saputro, Rujianto; Millatul Izza, Nia; Afriansyah, Fery; Salsa Dhia, Hasna; Aimah, Samsul; Munandar, Irwansyah; Tea Makdatuang, Radeta
Infotekmesin Vol 15 No 2 (2024): Infotekmesin, Juli 2024
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v15i2.2204

Abstract

Mental health is health related to a person's emotional, mental and psychological condition. Anxiety disorders are conditions in which individuals experience anxiety for short periods of time or intense episodes, where this anxiety can occur for no apparent reason. Damai is a mobile-based application designed to help overcome mental health problems, especially anxiety disorders among teenagers. This research focuses on designing a user interface that involves users directly at every stage of UCD, starting from user needs, concept design, to implementation of application prototypes. The success of this research was designing a mobile-based mental health consultation application to help teenagers who suffer from mental health. This application successfully provides several features such as mental health tests, online or offline counseling and pharmacy services. In trials conducted on 6 participants, the success of the trial can be concluded that the average direct success was 100%, the misclick rate was 25%, and the average duration was 38.1 seconds.
Comparative Analysis of Decision Tree, Random Forest, Svm, and Neural Network Models for Predicting Earthquake Magnitude Turino, Turino; Saputro, Rujianto Eko; Karyono, Giat
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 2 (2025): JUTIF Volume 6, Number 2, April 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.2.2378

Abstract

This study conducts a comparative analysis of four machine learning algorithms—Decision Tree, Random Forest, Support Vector Machine (SVM), and Neural Network—to predict earthquake magnitudes using the United States Geological Survey (USGS) earthquake dataset. The analysis evaluates each model's performance based on key metrics: Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and the coefficient of determination (R²). The Random Forest model demonstrated superior performance, achieving the lowest MAE (0.217051), lowest RMSE (0.322398), and highest R² (0.574261), indicating its robustness in capturing complex, non-linear relationships in seismic data. SVM also showed strong performance, with competitive accuracy and robustness. Decision Tree and Neural Network models, while useful, had comparatively higher error rates and lower R² values. The study highlights the potential of ensemble learning and kernel methods in enhancing earthquake magnitude prediction accuracy. Practical implications of the findings include the integration of these models into early warning systems, urban planning, and the insurance industry for better risk assessment and management. Despite the promising results, the study acknowledges limitations such as reliance on historical data and the computational intensity of certain models. Future research is suggested to explore additional data sources, advanced machine learning techniques, and more efficient algorithms to further improve predictive capabilities. By providing a comprehensive evaluation of these models, this research contributes valuable insights into the effectiveness of various machine learning techniques for earthquake prediction, guiding future efforts to develop more accurate and reliable predictive models.
DESIGNING UI/UX OF DOCTOR'S CONSULTATION APPLICATION USING DESIGN THINKING METHOD Damayanti, Wenti Risma; Kuncoro, Adam Prayogo; Subarkah, Pungkas; Saputro, Rujianto Eko
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 2 (2024): Maret 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i2.3053

Abstract

Abstract: For all people in the world, the application of information and communication technology has become something that is used in everyday life. All information can be accessed easily using current developments in various technologies. The process of searching for various information on the internet has become a habit of today's society. One of the information that people often seek is about health. Several available online health consultation service applications provide considerable benefits for all users. One method used for the UI and UX design process is design thinking. The average user of the application is 18-35 years old. The user interface provided in this application is not yet user friendly, especially for the elderly. User interface (UI) and user experience (UX) are important so that users feel comfortable when using an application.            Keywords: information technology; consulting application; UI/UX; design thinking  Abstract: Bagi seluruh masyarakat di dunia, penerapan teknologi informasi dan komunikasi menjadi hal yang sudah digunakan dalam kehidupan sehari-hari. Seluruh informasi dapat diakses dengan mudah menggunakan perkembangan berbagai macam teknologi saat ini. Proses mencari berbagai informasi di internet sudah menjadi kebiasaan masyarakat saat ini. Salah satu informasi yang sering dicari oleh masyarakat yaitu tentang kesehatan. Beberapa aplikasi layanan konsultasi kesehatan online yang tersedia memberikan manfaat yang cukup besar bagi seluruh pengguna. Salah satu metode yang digunakan untuk proses desain UI dan UX adalah design thinking. Pengguna aplikasi tersebut rata-rata berusia 18-35 tahun. Tampilan user interface yang disediakan pada aplikasi tersebut belum bersifat user friendly, terutama bagi kalanagn lansia. User interface (UI) dan user experience (UX) menjadi hal penting supaya pengguna merasakan kenyamanan pada saat menggunakan sebuah aplikasi.            Keywords: teknologi informasi; aplikasi konsultasi; UI/UX; design thinking
Optimalisasi UX Aplikasi Penyewaan Peralatan Bayi dengan Design Thinking dan Evaluasi SUS Ismail, Dimas Shafa Malik; Saputro, Rujianto Eko
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 6 No. 4 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v6i4.8657

Abstract

Penyewaan perlengkapan bayi menjadi solusi praktis bagi orang tua yang membutuhkan alat dalam jangka waktu terbatas. Namun, dalam praktiknya, masih banyak layanan penyewaan yang berjalan secara manual dan belum efisien, sehingga menimbulkan kendala seperti keterbatasan informasi, proses pemesanan yang rumit, serta waktu layanan yang tidak fleksibel. Penelitian ini bertujuan untuk merancang dan meningkatkan kualitas antarmuka pengguna (UI) serta pengalaman pengguna (UX) melalui pengembangan aplikasi mobile berbasis metode Design Thinking, guna meningkatkan efisiensi layanan dan kepuasan pengguna. Proses perancangan mengikuti lima tahap, yaitu Empathize, Define, Ideate, Prototype, dan Test, dengan diawali wawancara serta observasi untuk memahami kebutuhan pengguna, kemudian dilanjutkan dengan perancangan wireframe, alur navigasi, hingga pengujian prototipe low-fidelity dan high-fidelity. Evaluasi dilakukan dengan metode System Usability Scale (SUS) terhadap 15 responden yang merepresentasikan target pengguna. Hasil pengujian menunjukkan skor rata-rata SUS sebesar 77,17, yang menandakan aplikasi memiliki tingkat kegunaan tinggi dan respons positif dari pengguna. Temuan ini membuktikan bahwa pendekatan Design Thinking efektif dalam menghasilkan desain aplikasi penyewaan yang intuitif, ramah pengguna, dan mampu meningkatkan pengalaman digital pelanggan secara signifikan.
PROGRAM PENDAMPINGAN PENULISAN ILMIAH UNTUK MENINGKATKAN JUMLAH PUBLIKASI ILMIAH MAHASISWA Sarmini, Sarmini; Saputro, Rujianto Eko; Utomo, Fandy Setyo; Hidayatulloh, Hanif; Indriyani, Ria; Ramadhan, Rio Fadly
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 7, No 4 (2023): December
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v7i4.17570

Abstract

ABSTRAKKurangnya pengetahuan dan keterampilan mahasiswa Fakultas Ilmu Komputer untuk menulis artikel ilmiah menyebabkan rendahnya jumlah luaran jurnal ilmiah yang dihasilkan oleh mahasiswa sebagai luaran program Merdeka Belajar Kampus Merdeka (MBKM) di semester gasal tahun akademik 2022/2023. Berdasarkan permasalahan tersebut, kami mengusulkan pelaksanaan kegiatan webinar pendampingan penulisan jurnal ilmiah bagi mahasiswa Fakultas Ilmu Komputer yang bertujuan untuk meningkatkan kemampuan menulis artikel ilmiah dan meningkatkan jumlah publikasi ilmiah mahasiswa sebagai luaran program Merdeka Belajar Kampus Merdeka. Ada tiga tahapan dalam pelaksanaan kegiatan yaitu tahap persiapan, implementasi dan evaluasi. Kegiatan pendampingan dilakukan secara daring dengan menghadirkan narasumber dari Universiti Teknikal Malaysia (UTeM) dan diikuti oleh 117 mahasiswa yang mengikuti program MBKM di semester genap 2022/2023. Dampak dari kegiatan webinar yang telah dilaksanakan yakni meningkatnya jumlah publikasi artikel ilmiah mahasiswa Fakultas Ilmu Komputer sebagai luaran program MBKM di semester genap tahun akademik 2022/2023. Berdasarkan data yang diperoleh dari Fakultas Ilmu Komputer Universitas AMIKOM Purwokerto terdapat sejumlah 192 tulisan artikel ilmiah mahasiswa yang telah dikirimkan ke beberapa jurnal nasional. Kata kunci: assistance; merdeka belajar kampus merdeka; scientific writing; collaboration; research ABSTRACTComputer Science Faculty students' lack of knowledge and skills to write scientific articles has resulted in the low number of scientific journals produced by students as outputs of the Merdeka Belajar Kampus Merdeka (MBKM) Program in the odd semester of the 2022/2023 academic year. Based on these problems, we propose implementing a webinar to assist scientific journal writing for students of the Faculty of Computer Science, which aims to improve the ability to write scientific articles and increase the number of students' scientific publications as an output of the Merdeka Belajar Kampus Merdeka program. There are three stages in implementing activities: preparation, implementation, and evaluation. Mentoring activities were carried out online by presenting resource persons from Universiti Teknikal Malaysia (UTeM) and were attended by 117 students taking part in the MBKM program in the even semester 2022/2023. The impact of the webinar activities that have been carried out is the increase in the number of publications of scientific articles by Faculty of Computer Science students as an output of the MBKM program in the even semester of the 2022/2023 academic year. Based on data from the Faculty of Computer Science, Universitas AMIKOM Purwokerto, 192 student scientific articles have been submitted to several national journals. Keywords: accompaniment; study center; games; collaboration; research
PELATIHAN PENGISIAN BEBAN KERJA DOSEN (BKD) MELALUI SISTER PADA DOSEN FAKULTAS ILMU KOMPUTER UNIVERSITAS AMIKOM PURWOKERTO Saputro, Rujianto Eko; Febrianti, Diah Ratna; Saputri, Inka; Sarmini, Sarmini
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 7, No 4 (2023): December
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v7i4.17792

Abstract

ABSTRAKMasih kurangnya pemahaman dosen terkait pengisian BKD melalui SISTER menyebabkan beberapa dosen merasa kesulitan dalam melakukan pengisian BKD, hal ini berdampak pada ketepatan waktu dosen dalam mengirimkan laporan BKD kepada asesor. Keterlambatan tersebut juga mengakibatkan asesor terlambat dalam memeriksa dan memberikan penilaian, yang pada akhirnya dosen menjadi terlambat untuk melaporkan laporan BKD kepada lembaga terkait. Maka dari itu perlu adanya kegiatan pelatihan untuk menyamakan persepsi dosen dalam pengisian BKD, dengan pelatihan ini diharapkan mampu meningkatkan pengetahuan, kemampuan dan ketelitian dosen pada saat mengisi BKD. Kegiatan pelatihan ini bertujuan untuk membantu mempermudah dosen dalam melakukan pengisian BKD melalui SISTER dan juga meningkatkan ketepatan waktu dosen dalam pengumpulan laporan BKD. Metode pelaksanaan kegiatan terdiri dari tahap perencanaan, tahap pelaksanaan dan tahap evaluasi. Kegiatan pelatihan diberikan kepada dosen dengan memberikan pemaparan materi, tes setelah pelatihan dan tanya jawab kepada dosen sebelum kegiatan pelatihan diakhiri. Berdasarkan hasil evaluasi kegiatan menunjukkan bahwa kegiatan pelatihan dapat diikuti dan dipahami dengan baik oleh peserta dan sebanyak 80% peserta setelah mengiktui kegiatan pelatihan dapat menyelesaikan pengisian BKD dan menyimpan permanen laporan BKD. Kata kunci: pelatihan; pengisian; BKD; SISTER; dosen. ABSTRACTThere is still a lack of understanding regarding filling in the BKD through SISTER, causing some lecturers to find it difficult to fill in the BKD, this has an impact on the tighter time for lecturers in sending BKD reports to assessors. This delay also results in an assessor being late in examining and providing an assessment, which ultimately results in the lecturer being late in reporting the BKD report to the relevant institution. Therefore, there is a need for training activities to equalize lecturers' perceptions in filling out the BKD. With this training, it is hoped that it will be able to increase the knowledge, ability and accuracy of lecturers when filling out the BKD. This training activity aims to help make it easier for lecturers to fill in BKD through SISTER and also increase lecturers' timeliness in collecting BKD reports. The activity implementation method consists of the planning stage, implementation stage and evaluation stage. Training activities provided to lecturers include presentation of material, tests after training and questions and answers to lecturers before the training activities end. Based on the results of the activity evaluation, it shows that the training activities can be followed and understood well by the participants and as many as 80% of participants after participating in the training activities can complete filling in the BKD and keep a permanent BKD report. Keywords: training; filling; BKD; SISTER; lecturer.
Labeling Optimization and Hybrid CNN Model in Sentiment Analysis of Movie Reviews with Slang Handling Saputra, Alfin Nur Aziz; Saputro, Rujianto Eko; Saputra, Dhanar Intan Surya
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 6 (2025): JUTIF Volume 6, Number 6, Desember 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.6.4465

Abstract

This research focuses on the development of a hybrid Convolutional Neural Network (CNN) model for sentiment analysis of movie comments, specifically designed to overcome the challenges of handling nonstandard language and slang. Slang is often an obstacle in sentiment analysis due to its non-standard nature and is difficult to recognize by traditional algorithms. By utilizing an kamusalay as a data preprocessing step, this research successfully converts slang words into standardized forms, thus improving the quality of data used in modeling. The data was collected through YouTube Data API on the comments of the movie “Pengabdi Setan 2: Communion” and processed using tokenization, stemming, stopwords removal, and TF-IDF feature extraction techniques. The hybrid model combines machine learning algorithms such as Naive Bayes, Logistic Regression, and Random Forest with CNN's ability to extract complex spatial patterns from text data. The evaluation results show that this model is able to achieve up to 95% accuracy, with consistently high precision, recall, and F1-score. This approach not only improves the accuracy of sentiment analysis, but also provides an effective solution for handling non-standard language variations, making it relevant for application in digital opinion analysis on social media.
Pengaruh Prediksi Kredit bermasalah Terhadap Keputusan Bank Dengan Komparasi Metode ANN, CNN, dan Random Forest Nurmalitasari, Gupita; Eko Saputro, Rujianto; Karyono, Giat
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 12 (2025): JPTI - Desember 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.1276

Abstract

Kredit bermasalah menjadi salah satu tantangan utama sektor perbankan karena dapat mengganggu stabilitas keuangan dan mempengaruhi keputusan strategis. Oleh karena itu, kemampuan memprediksi potensi kredit bermasalah secara akurat sangat penting dalam pengelolaan risiko. Penelitian ini membandingkan kinerja tiga algoritma kecerdasan buatan ANN (Artificial Neural Network) dengan arsitektur MLP (Multilayer Perceptron), CNN  (Convolutional Neural Network), dan RF (Random Forest) untuk klasifikasi risiko kredit berdasarkan data nominatif kredit.Dataset mencakup fitur-fitur utama seperti plafon pinjaman, jangka waktu, penghasilan, baki debet, kolektibilitas dan total tunggakan. Data diklasifikasikan dalam lima kategori risiko berdasarkan status pembayaran antara lain L (Lancar), DP (Dalam Perhatian), KL (Kurang Lancar), D (Diragukan), dan M (Macet). Setiap model dievaluasi berdasarkan akurasi keseluruhan dan kemampuannya mengidentifikasi kelas minoritas dan mayoritas.Hasil menunjukkan bahwa Random Forest unggul dengan akurasi 91,42%, efektif dalam mengklasifikasikan kategori “Lancar” dan “Macet”. Model ANN MLP mencapai akurasi 89,90%, namun kurang optimal untuk kelas minoritas. Sementara CNN hanya mencatat akurasi 58,58% dan mengalami overfitting terhadap kelas mayoritas.Studi ini menyimpulkan bahwa Random Forest adalah metode paling tepat untuk data tabular yang seimbang, sementara CNN memiliki potensi dalam konteks data spasial atau sekuensial. Dan hasil yang akurat dari prediksi Random forest diharapkan dapat menjadi pertimbangan bagi lembaga keuangan dalam pengambilan keputusan terkait kebijakan di bank Pemerintah di Purbalingga.
Penerapan Algoritma Kalman Filter Dan Yolo Mengukur Efektifitas Aruco Marker Bagi Tunanetra YULIANTO, KOKO EDY; SAPUTRO, RUJIANTO EKO; UTOMO, FANDY SETYO
Jurnal Tekno Insentif Vol 19 No 2 (2025): Jurnal Tekno Insentif
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah IV

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36787/jti.v19i2.1948

Abstract

Abstrak Mobilitas dan aksesibilitas merupakan tantangan utama bagi individu dengan disabilitas visual. Penelitian ini mengevaluasi efektivitas sistem navigasi berbasis multi-sensor untuk tunanetra dengan menggabungkan Algoritma Kalman Filter dan YOLO dalam mendeteksi Aruco Marker. Fokus penelitian adalah meningkatkan akurasi dan efisiensi navigasi melalui integrasi teknik deteksi deep learning dan prediksi matematis secara real-time. Hasil eksperimen menunjukkan bahwa Kalman Filter memiliki waktu deteksi lebih cepat, dengan rata-rata 0,1090 detik untuk objek Botol Plastik dan 0,1069 detik untuk objek Kombinasi. YOLO mencatat waktu sedikit lebih cepat namun dengan komputasi lebih berat. Kalman Filter mencatat efisiensi waktu 12,5%–13,3% lebih baik pada objek tertentu dan akurasi sebesar 94,50% (Botol Plastik) serta 96,00% (objek Kombinasi), lebih tinggi dibandingkan YOLO. Kombinasi kedua algoritma ini memberikan solusi navigasi yang akurat dan efisien untuk tunanetra, serta berpotensi dikembangkan lebih lanjut sebagai sistem navigasi real-time yang andal. Kata kunci: Kalman Filter, YOLO, Aruco Marker, Navigasi Tunanetra, Efektivitas Deteksi Abstract Mobility and accessibility remain major challenges for individuals with visual impairments. This study evaluates the effectiveness of a multi-sensor navigation system for the visually impaired by integrating the Kalman Filter algorithm and YOLO for Aruco Marker detection. The research focuses on improving the accuracy and efficiency of navigation by combining deep learning-based detection with real-time mathematical prediction. Experimental results show that the Kalman Filter achieves faster detection times, averaging 0.1090 seconds for Plastic Bottle objects and 0.1069 seconds for Combination objects. While YOLO recorded slightly faster raw detection times, Kalman Filter demonstrated 12.5%–13.3% better computational efficiency for certain objects. In terms of accuracy, Kalman Filter achieved 94.50% for Plastic Bottle objects and 96.00% for Combination objects, outperforming YOLO’s 92.00% and 93.50%, respectively. The integration of both algorithms offers a promising and optimal solution for the development of reliable real-time navigation systems for the visually impaired. Keywords: Kalman Filter, YOLO, Aruco Marker, Blind Navigation, Detection Effectiveness
Optimalisasi kemampuan menulis akademik melalui teknologi AI: kolaborasi Universiti Teknikal Malaysia Melaka dan Universitas Amikom Purwokerto Sarmini Sarmini; Rujianto Eko Saputro; Fandy Setyo Utomo; R. Vitto Mahendra Putranto; Shendy Filanzi; Febriansyah Husni Adiatma
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 8, No 4 (2024): December
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v8i4.26335

Abstract

Abstrak Kebutuhan untuk meningkatkan kemampuan mahasiswa dalam memanfaatkan teknologi terbaru, khususnya AI, dalam proses penulisan ilmiah semakin penting di era digital. Kegiatan pendampingan penulisan artikel ilmiah menggunakan kecerdasan buatan (AI) diselenggarakan oleh Pusat Studi Media, Game, dan Mobile Universitas Amikom Purwokerto, dengan narasumber Assoc. Prof. Ahmad Naim Che Pee dari Human-Centered Computing and Information Systems Lab (HCC-ISL), UteM dilaksanakan pada tanggal 1 Agustus 2024. Tujuan dari kegiatan ini untuk memberikan pemahaman serta keterampilan praktis bagi mahasiswa dalam penggunaan AI, khususnya Chat GPT, dalam menyusun artikel ilmiah, mulai dari penyusunan struktur, pengecekan tata bahasa, hingga pengelolaan referensi. Metode pelaksanaan kegiatan meliputi pre-test untuk mengukur pemahaman awal mahasiswa, pelatihan yang mencakup teori dan praktik penggunaan AI, post-test untuk menilai peningkatan pemahaman, serta sesi tanya jawab dan evaluasi. Hasil evaluasi menunjukkan peningkatan signifikan dalam pemahaman mahasiswa, yang tercermin dari data hasil post-test yang lebih baik dibandingkan pre-test. Selain itu, mahasiswa menyatakan bahwa pelatihan ini memberikan wawasan baru yang relevan untuk mendukung tugas akademik mereka. Kata kunci: pendampingan; kecerdasan buatan; chat GPT; mahasiswa; penulisan artikel. Abstract Enhancing students' abilities to utilize the latest technology, particularly AI, in scientific writing is becoming increasingly important in the digital era. A scientific article writing mentorship program using Artificial Intelligence (AI) was organized by the Media, Game, and Mobile Research Center at Universitas Amikom Purwokerto, with the guest speaker Assoc. Prof. Ahmad Naim Che Pee from the Human-Centered Computing and Information Systems Lab (HCC-ISL), UTeM, held on August 1, 2024. This activity aimed to provide students with practical understanding and skills in using AI, specifically Chat GPT, in composing scientific articles, from structuring the paper and grammar checking to managing references. The implementation method included a pre-test to measure students' initial understanding, training sessions covering theory and practical use of AI, a post-test to assess improvements, and a Q&A session and evaluation. The evaluation results showed a significant improvement in students' understanding, as reflected in the post-test data, which were better than the pre-test results. Students reported that this training provided new and relevant insights to support their academic tasks. Keywords: mentoring; artificial intelligence; chat GPT; students; article writing.
Co-Authors Adam Prayogo Kuncoro Adam Prayogo Kuncoro Adiya, Az Zahra Dwi Nur Afriansyah, Fery Aimah, Samsul Akhmad Fauzan Arif Mu'amar Wahid Aulia Hamdi Azhari Shouni Barkah Bagaskoro, Galih Berlilana Berlilana Cahyo, Samsul Dwi Chyntia Raras Ajeng Widiawati Damaito, Aditya Hanif Hadian Damayanti, Wenti Risma Dani Arifudin Darmono Darso, Darso Deasy Komarasary Dhanar Intan Surya Saputra Dhanar Intan Surya Saputra Ely Purnawati Ely Purnawati, Ely Embong Octavianto Fandy Setyo Utomo Fatudin, Arif Faturama, Rafi Febriansyah Husni Adiatma Febrianti, Diah Ratna Fery Afriansyah Giat Karyono Hariyanti, Anies Indah Hasna Salsa Dhia hidayatulloh, hanif Ikmah Ikmah Ikmah, Ikmah Ilham, Rifqi Arifin Indriyani, Ria Irwansyah Munandar Ismail, Dimas Shafa Malik Junianto, Haris Kusuma, Bagus Adhi Latif, Imam Sofarudin Lughri Wijaya Pamungkas Maharani, Revalyna Octavia Maulana Baihaqi, Wiga Millatul Izza, Nia Mohd. Hafiz Zakaria Mukti, Gilang Deli Munandar, Irwansyah Nanjar, Agi Ndari, Arum Vika Nia Millatul Izza Novita Eka Ramadhani Nugroho, Lustiyono Prasetyo Nurfaizi, Maulana Nurmalitasari, Gupita Octavianto, Embong Pandu W, Muhammad Arfianto Prasetyo, Agung Prianto, Slamet Endro Pungkas Subarkah Purwadi Purwadi Purwadi Purwadi Putri, Qeisha Amaliya Qolbu, Aufiatu Risqiyah Nur Ainun R. Vitto Mahendra Putranto Radeta Tea Makdatuang Ramadhan, Rio Fadly Ria Indriyani Rizqi Aulia Widianto Rohmah, Umdah Aulia Rosana Fadila Sari safitri feriawan, Titi Salam, Sazilah Salsa Dhia, Hasna Salsabila, Sabita Samsul Aimah Saputra , Dhanar Intan Surya Saputra, Alfin Nur Aziz Saputri, Inka Sari, Rida Purnama Sarmini Sarmini - Sarmini Sarmini Sarmini Sazilah Salam Serli, Serli Shendy Filanzi Sofa, Nur Sri Hartini Suliswaningsih, Suliswaningsih Syahputra, Akhmal Angga Tanzilla, Armeyta Putri Tarwoto, T Tea Makdatuang, Radeta Titi Safitri Maharani Toni Anwar Turino, Turino Wahyuni, Irmawati Tri Wanti, Linda Perdana Wenti Risma Damayanti Wiga Maulana Baihaqi Wijaya, Anugerah Bagus Yuli Purwati Yulianto, Koko Edy