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All Journal KREDO : Jurnal Ilmiah Bahasa dan Sastra KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer Jurnal ICT : Information Communication & Technology JALL (Journal of Applied Linguistics and Literacy) Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Edukasi (Ekonomi, Pendidikan dan Akuntansi) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Teknologi Informasi dan Komunikasi SOSIOLOGI: Jurnal Ilmiah Kajian Ilmu Sosial dan Budaya Instal : Jurnal Komputer Journal of Artificial Intelligence and Engineering Applications (JAIEA) BULLET : Jurnal Multidisiplin Ilmu AMMA : Jurnal Pengabdian Masyarakat
Narasati, Riri Narasati
STMIK IKMI Cirebon
Arts Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Nursing Social Sciences Other

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KONSTRUKSI SOSIAL TEKNOLOGI CHATGPT DALAM PENDIDIKAN Dienwati Nuris, Nisa; Anam, Khaerul; Narasati, Riri
SOSIOLOGI: Jurnal Ilmiah Kajian Ilmu Sosial dan Budaya Vol. 26 No. 2 (2024): SOSIOLOGI: Jurnal Ilmiah Kajian Ilmu Sosial dan Budaya
Publisher : Jurusan Sosiologi Fakultas Ilmu Sosial dan Ilmu Politik Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/sosiologi.v26i2.1399

Abstract

The technology that is currently developing in the field of education is the use of ChatGPT media. ChatGPT can be applied in campus learning. The flow of ChatGPT technology development poses a challenge to human perspectives on learning methods and information acquisition. The purpose of the research is to analyze the relationship between ChatGPT technology in shaping social constructs among students and institutions. This research uses the concept of the Social Construction of Technology (SCOT) to analyze the use of ChatGPT in the educational environment. This research method uses a descriptive qualitative approach to explore the meaning and experiences of students in using ChatGPT. To strengthen this qualitative research method, data collection techniques include in-depth interviews, direct observation, documentation, and literature review. The data analysis process follows systematic stages, namely data collection, data reduction through filtering relevant information, structured data presentation, and drawing conclusions based on the understanding of participants' experiences. The research results show that ChatGPT is designed to facilitate users in performing activities, with features tailored to users' activities. The implications of ChatGPT technology in education have both positive and negative impacts in its usage. The positive impact can assist in tasks, while the negative impact lies in aspects of privacy andand ethical limitations.
Strategi Pelatihan Digital Marketing Untuk Peningkatan Daya Saing UMKM Di Media Sosial Dan Marketplace Dienwati Nuris, Nisa; Narasati, Riri; Nuryadi; Yati Ningrum, Riska
AMMA : Jurnal Pengabdian Masyarakat Vol. 3 No. 3 : April (2024): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Micro, small, and medium enterprises (MSMEs) make a significant contribution to the economy, but often face obstacles in developing their business potential in the digital era. This Community Partnership Program aims to empower MSME entrepreneurs through the design of an integrated business ecosystem based on digital platforms. The implementation methods include analyzing the conditions of partner MSMEs, developing a relevant business ecosystem model design, intensive training on the utilization of digital platforms in various aspects of business operations (marketing, sales, inventory management, and customer interaction), and assistance in implementing the designed digital ecosystem. The expected outcomes of this program are improved operational efficiency, expanded market reach, strengthened customer relationships, and the promotion of sustainable business growth for partner MSMEs through the adoption of an effective digital ecosystem.
Peningkatan Daya Saing Siswa SMK Melalui Pelatihan Bahasa Inggris Untuk Dunia Kerja Narasati, Riri; Hamonangan, Ryan; Fajar, Achmad; Aulia Putri, Adinda
AMMA : Jurnal Pengabdian Masyarakat Vol. 3 No. 3 : April (2024): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

English language skills are a key factor in improving the competitiveness of Vocational High School (SMK) graduates in an increasingly competitive and globalized world of work. This article discusses various strategies that can be applied to improve the English language competence of SMK students to be better prepared to face industry challenges. The approaches used include communication-based learning, utilization of technology in the learning process, and integration of English materials with the needs of the industrial world. In addition, intensive training programs and English language certification are strategic steps to improve students' abilities. This research shows that interactive and contextual learning methods are able to increase student motivation and understanding. project-based, workplace simulation, and the use of digital platforms have proven effective in improving students' communication skills. In addition, industry involvement in the learning process through internship programs and cooperation with educational institutions also has a positive impact on the job readiness of graduates. With an increase in English competency, SMK graduates are not only more confident in facing the world of work, but also have a greater chance of getting a job in a multinational company or working abroad. Therefore, improving the quality of English learning in SMK should be a major concern in order to create competitive human resources who are ready to compete in the era of globalization.
Clustering Data on Participants’ Reactions to Online Shop Posts on Facebook Using K-Means Algorithm With Elbow Method Technique Arifin, Imam; Rahaningsih, Nining; Suprapti, Tati; Narasati, Riri
Bahasa Indonesia Vol 15 No 02 (2023): Instal : Jurnal Komputer Periode (Juli-Desember)
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalkomputer.v15i02.132

Abstract

One of the social media platforms that not only serves as a place to share stories and statuses but also as a place to sell is Facebook. The data used is a dataset from Kaggle totaling 6666 data with 10 attributes and then sampled with the Slovin technique and obtained 377 sample data which will be processed using RapidMiner software with K-Means Algorithm and then optimized with Elbow Method technique, evaluation using (Cluster Distance Performance) to find the average within centroid distance value and the Davies-Bouldin Index (DBI) value. The results obtained are, the average within centroid distance value of the 3rd clustering is proven in the cluster distance performance operator obtained ???? = 3: 200237.353, ????=5: 118343.557, ????=7: 75339.476, then the ideal of clusters in this study proven by the Elbow Method is when ???? = 5, and Davies-Bouldin Index (DBI) value which is close to zero is when ???? = 3 with a value of k = 3: 0.394. In addition, clustering based on the number of likes and comments can help sellers identify the most active group of participants and potentially become loyal customers.
Penerapan Naïve Bayes Dan Visualisasi Wordcloud Dalam Analisis Sentimen Pengguna E-Learning Narasati, Riri; Solehudin, Dodi
BULLET : Jurnal Multidisiplin Ilmu Vol. 2 No. 2 (2023): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

This study aims to analyze the sentiment of e-learning users using the Naïve Bayes method and WordCloud visualization. In today's digital era, e-learning has become an increasingly popular learning platform, making sentiment analysis of users on this platform crucial to understand their experiences. The Naïve Bayes method was chosen for classifying user sentiment, while WordCloud visualization is used to display the frequency of words appearing in user reviews. The data used in this research were collected from user comments and reviews on e-learning platforms. The results indicate that the Naïve Bayes method is effective in classifying user sentiment, while WordCloud provides a clear representation of the most frequent words in the reviews, revealing the sentiment patterns present.
Peningkatan Kemampuan Bahasa Inggris Siswa SMK Melalui Pendekatan Komunikatif Dan Praktis Narasati, Riri; Kurniawan, Rudi; Aditia; Haekal Susanto, Ahmad
AMMA : Jurnal Pengabdian Masyarakat Vol. 2 No. 4 (2023): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

The agricultural sector in villages has great potential to produce high-quality products but still faces challenges in marketing. One major issue is the limited knowledge and skills of farmers in utilizing social media as a promotional tool. Through this community service program, training and mentoring were provided to farmers and agricultural entrepreneurs to enhance their understanding of digital marketing. Activities included the creation and management of business social media accounts, training in creating engaging promotional content (photos, videos, and copywriting), and branding and packaging strategies. The program showed significant improvements in farmers' abilities to market their products independently through platforms such as Instagram, Facebook, and WhatsApp Business. Farmers who previously relied solely on middlemen have now started to sell directly to consumers online. Some partners also reported increased sales and social media engagement. Additionally, the formation of a digital farmer community strengthened promotional networks and experience sharing among agricultural players. This program not only encouraged independent marketing but also enhanced the competitiveness of local agricultural products in broader markets. The program's sustainability is strongly recommended through follow-up mentoring, paid advertising training, and improved digital infrastructure in rural areas. Thus, using social media as a promotional tool becomes not just a short-term solution but a sustainable strategy to drive rural digital economic growth.
Pelatihan Digital Marketing Untuk Peningkatan Kapasitas Perempuan Dalam Pemasaran Produk Hamonangan, Ryan; Narasati, Riri; Sri Nurmala, Ai; Ayu Febriaan Lesmana, Alfira
AMMA : Jurnal Pengabdian Masyarakat Vol. 2 No. 4 (2023): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

The development of digital technology has brought significant changes in the world of education, especially in online learning methods. Digital literacy is an essential skill for educators in navigating technology-based learning. This research aims to improve digital literacy for elementary school teachers in facing online learning challenges. The training program developed includes a basic understanding of digital technology, the use of learning software, and effective teaching strategies in an online environment. The research method used was a qualitative approach with observation, interviews and case studies in several primary schools in Cirebon district. The results showed that digital literacy training significantly improved teachers' competence in using technology and improved the effectiveness of online teaching. Teachers who participated in this training program were able to optimize the use of various digital platforms, improve interaction with students, and adapt the curriculum to better fit the online learning model. In addition, the main challenges faced include limited access to technology infrastructure and lack of adequate technical support. Therefore, more supportive policies in the provision of technology resources and continuous training programs for teachers are needed. The findings of this study confirm that improving digital literacy is a key factor in the successful implementation of online learning at primary school level. By improving teachers' competence in technology utilization, it is expected that the learning process can be more interactive, effective and adaptive to the times. This study also recommends the need to integrate digital-based curriculum so that teachers are better prepared to teach online materials.
Comparative Analysis of Durian Leaf Disease Classification Using Transfer Learning VGG16, InceptionV3, and U-Net Nafisa Maysa Salma; Kurniawan, Rudi; Nurhakim, Bani; Bahtiar, Agus; Narasati, Riri
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1864

Abstract

Image-based durian leaf disease detection presents challenges due to high visual similarity among symptoms and the limited, imbalanced dataset. This study compares three deep learning architectures VGG16, InceptionV3, and U-Net encoder-based—using transfer learning for classifying five durian leaf conditions. The dataset of 4,437 images underwent preprocessing, augmentation, and preliminary segmentation using U-Net to enhance focus on leaf regions. Fine-tuning was applied to the upper layers of each model to adapt feature representations to tropical leaf characteristics. The results indicate that InceptionV3 achieved the most stable and accurate performance with an accuracy of approximately 0.66, while VGG16 showed balanced results but was more prone to overfitting. U-Net proved effective for segmentation but less optimal as a classifier due to loss of small-scale lesion details. Overall, the findings demonstrate that combining U-Net segmentation with CNN-based transfer learning improves disease identification performance, particularly under limited data conditions.
PERBANDINGAN KINERJA SUPPORT VECTOR MACHINE ORIGINAL DAN SUPPORT VECTOR MACHINE BERBASIS SMOTE UNTUK ANALISIS SENTIMEN APLIKASI JKN MOBILE APIPAH, KUSNATUL; Martanto, Martanto; Dikananda, Fatihanursari; Bahtiar, Agus; Narasati, Riri
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI Vol. 17 No. 1 (2026): Maret
Publisher : UNIVERSITAS STEKOM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtikp.v17i1.1403

Abstract

Analisis sentimen terhadap ulasan pengguna aplikasi JKN Mobile digunakan untuk mengevaluasi kualitas layanan digital BPJS Kesehatan. Penelitian ini membandingkan kinerja algoritma Support Vector Machine (SVM) pada data asli dan SVM berbasis Synthetic Minority Oversampling Technique (SMOTE) dalam mengatasi permasalahan ketidakseimbangan kelas. Dataset diperoleh melalui proses scraping ulasan pengguna aplikasi JKN Mobile. Tahapan pra-pemrosesan meliputi case folding, tokenizing, stopword removal, dan stemming. Representasi fitur menggunakan metode Term Frequency–Inverse Document Frequency (TF-IDF). Evaluasi kinerja model dilakukan menggunakan metrik accuracy, precision, recall, dan F1-score. Hasil penelitian menunjukkan bahwa penerapan SMOTE mampu meningkatkan kinerja klasifikasi, khususnya pada kelas minoritas, dibandingkan dengan SVM tanpa penyeimbangan data. Dengan demikian, SMOTE terbukti efektif untuk meningkatkan performa analisis sentimen pada data tidak seimbang.
Co-Authors Ade Rizki Rinaldi Aditia Adniana, Royana Ahmad Faqih Amalia, Dita Rizki Anawar, Saeful Antika, Rindi APIPAH, KUSNATUL Aulia Putri, Adinda Ayu Febriaan Lesmana, Alfira Chaidir Ali Dienwati Nuris, Nisa Dikananda, Fatihanursari Edi Tohidi Eka Permana, Sandy Fajar, Achmad Fazrian, Vivi Febiyanto, Anggi Gifthera Dwilestari Haekal Susanto, Ahmad Hajaroh, Hajaroh Hamonangan, Ryan Herdiana, Ruli Herdiyana, Ruli Hery Widijanto Imam Arifin Indriya Efendi, Dendy Lestari, Ratih Liawati, Ayu Lukman Rohmat, Cep Martanto . Muhamad Sulaiman Mulyawan Nafisa Maysa Salma Nining Rahaningsih Nur alamsyah, Deri Nuraini, Asyifa Nurhakim, Bani Nurwahidah, Dalilah Nuryadi Raditya Danar Dana Riandy Yudistira Rifa’I, Ahmad Rizky Maulana, Rizky Rudi Kurniawan Ruli Herdiana Saeful Anwar Saeful Anwar, Saeful Sandy Eka Permana Solehudin, Dodi Solihudin, Dodi Sri Nurmala, Ai Syarif Maulana Yaasin Tati Suprapti Yati Ningrum, Riska