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All Journal Jurnal Ilmiah Informatika Komputer KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer Jurnal ICT : Information Communication & Technology Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal) Jurnal Riset Sistem Informasi dan Teknologi Informasi (JURSISTEKNI) Jurnal Informatika Terpadu International Journal of Social Science Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Dimamu Jurnal Sistem Informasi dan Teknologi (SINTEK) AMMA : Jurnal Pengabdian Masyarakat Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal) Jurnal Kecerdasan Buatan dan Teknologi Informasi Sintek Kuwera
Nana Suarna
STMIK IKMI Cirebon
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Analisa Clustering untuk Mengelompokan Data Penayangan Film Bioskop Menggunakan Algoritma K-Means Moh Nurdayat Dayat; Nana Suarna; Yudhistira Arie Wijaya
INTERNAL (Information System Journal) Vol. 6 No. 1 (2023)
Publisher : Masoem University

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Abstract

The purpose of this study is one of the analyzes to obtain film screening data, the approach used in this study is the K-means algorithm using the parameter measure type Numerical Measure with Numerical Measure Euclidean Distance to get the best Davies Bouldin Index (DBI), with the intention of getting helps grouping datasets of film screenings at the Ramayana Cirebon XXI Cinema. Results from the evaluation of the Davies Bouldin Index (DBI) obtained is (K-2) with a Davies Bouldin Index (DBI) value of 0.864, because the value obtained is the smaller the Davies Bouldin Index (DBI) value, it shows the optimum performance of the resulting cluster.
Usability Testing pada Aplikasi Kas Berbasis Android dan Teknologi API menggunakan Metode System Usability Scale Nurul Ibnu Al Muharom; Nana Suarna; Raditya Danar Dana
Jurnal Informatika Terpadu Vol 10 No 1 (2024): Maret, 2024
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v10i1.1099

Abstract

Cash management applications are used to store transaction data and create cash in and cash out reports that are more effective than using books. However, currently no usability testing has been carried out so it is quite difficult to determine future application development steps. The aim of this research is to measure the level of usefulness of an Android-based cash management application using the System Usability Scale (SUS) method, namely a 10-question Likert scale questionnaire distributed to respondents with the final result being a score of 0-100. The number of respondents was 15 people who were CV employees. Jaya Mukti. This test was carried out to determine the level of user convenience and satisfaction. The results of the research obtained a score of 84.7, this score shows a percentile level of 96%, Grade Scale A, Acceptability Ranges are in the Acceptable category, meaning acceptable, and the Adejctive Rating is in the Excellent category. If correlated with NPS, it falls into the promoter category, meaning users will recommend the application. These results show that the application can be accepted by users and is very good and above the established usability value standards. This research also produced 4 recommendations for improvement based on the results of questionnaire answers so that they can be used as evaluation for future application development.
Prediksi Jumlah Sampah pada Sektor Informal di Provinsi Jawa Barat MenggunakanAlgoritma Regresi Linear Nursyifa Puspa Ar-rahmi Slamet; Nana Suarna; Willy Prihartono
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 1 (2024): Maret
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i1.10294

Abstract

Waste has become one of the most pressing global problems to be solved. Rapid population growth, urbanization, and consumerism have led to a significant increase in the volume of waste worldwide. This phenomenon not only affects the environment, but also touches the economic sector, health, and social life. West Java, as one of the provinces with the highest population density in Indonesia, faces great pressure regarding waste management. The province is experiencing a significant increase in the amount of waste that occurs due to population growth and high intensity of industrial activities. The method used in this research is linear regression algorithm. The application of linear regression algorithm can help the government to plan strategic measures in waste management. By using historical data on waste production, population growth, and other factors. This algorithm can provide an overview of future trends in waste generation. The purpose of this research is to implement a linear regression algorithm to predict the amount of waste data that goes to the informal sector, especially involving collectors or stalls in West Java province. The results of this study resulted in an increase in the accuracy level of the accuracy of the volume of waste in the informal sector in West Java Province can have a significant impact and make a major contribution to the understanding of the effectiveness of the application of linear regression algorithms. This increase in accuracy is expected to deepen the understanding of how the algorithm can be optimized for more efficient prediction and management of waste volume.
PENERAPAN ALGORITMA SUPPORT VECTOR MACHINE UNTUK ANALISIS SENTIMEN ULASAN PELANGGAN TOKO LIVIA CIREBON DI SHOPPE Syaeful Annas; Nana Suarna; Irfan Ali; Heliyanti Susana
Jurnal Ilmiah Informatika Komputer Vol 29, No 3 (2024)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/ik.2024.v29i3.13109

Abstract

Analisis sentimen adalah proses yang bertujuan untuk memahami opini pelanggan dengan mengklasifikasikan ulasan menjadi sentimen positif, netral, atau negatif. Penelitian ini bertujuan untuk mengembangkan model analisis sentimen berbasis algoritma Support Vector Machine (SVM) terhadap ulasan pelanggan Toko Livia Cirebon di platform Shopee. Pendekatan penelitian dilakukan secara kuantitatif, dengan tahapan meliputi pengumpulan data, pra-pemrosesan teks (cleansing, normalisasi slang, tokenisasi, penghapusan stopword, dan stemming), pelabelan menggunakan Inset Lexicon, transformasi data teks menjadi vektor numerik dengan metode TF-IDF, pelatihan model SVM, serta evaluasi performa menggunakan metrik akurasi, precision, recall, dan F1-score. Model yang dikembangkan mencapai akurasi sebesar 91% dengan performa terbaik pada sentimen positif (F1-score 95%), meskipun performa pada kategori netral dan negatif masih memerlukan peningkatan. Hasil penelitian ini menunjukkan bahwa algoritma SVM efektif untuk analisis sentimen dalam e-commerce, memberikan wawasan strategis bagi pemilik usaha untuk menyusun strategi pemasaran dan meningkatkan kualitas layanan.
Pelatihan Pola Dan Segmentasi Citra Bagi Dosen Kopertip Indonesia Untuk Mendukung Penelitian Multidisiplin Mulyawan; Nana Suarna; Gildan Jaya Muhammad Ramadhan; Muhammad Alfian Nur Rahmat
AMMA : Jurnal Pengabdian Masyarakat Vol. 3 No. 3 : April (2024): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Pattern recognition and image segmentation are visual data analysis techniques with broad applications in various research fields. This Community Service Program aims to provide training on pattern recognition and image segmentation for lecturers of Kopertip Indonesia. This training seeks to enhance lecturers' understanding and ability to apply these techniques as tools to support multidisciplinary research. The training material includes the fundamentals of image processing, various pattern recognition methods, image segmentation algorithms, and case studies of applications in cross-disciplinary research contexts. It is hoped that this activity can encourage the improvement of quality and interdisciplinary research collaboration within Kopertip Indonesia.
Optimalisasi Branding Dan Packaging Produk UMKM Untuk Peningkatan Daya Saing Di E-Commerce Nana Suarna; Nisa Dienwati Nuris; Mohamad Ibnu Abas; Muhammad Alfian Nur Rahmat
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) play a crucial role in the economy but often face obstacles in increasing product value, especially within the e-commerce ecosystem. This Community Partnership Program aims to optimize branding and packaging for partner MSME products to be more competitive and attractive in the digital market. The implementation methods include analyzing the condition of the MSMEs, providing intensive training on effective branding strategies and attractive as well as functional packaging design, followed by implementation assistance on e-commerce platforms. The expected outcomes of this activity are an enhanced brand image, improved visual appeal of products, as well as increased selling value and expanded online market reach for the partner MSMEs.
Pemanfaatan Aplikasi E-Learning Dalam Meningkatkan Proses Belajar Mengajar Guru Dan Siswa Nana Suarna; Nining Rahaning; Ade Awaludin; Adinda Aulia Putri
AMMA : Jurnal Pengabdian Masyarakat Vol. 2 No. 3 (2023): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

The Covid-19 pandemic has accelerated the adoption of technology in education, particularly the use of e-learning applications. However, a lack of digital skills and understanding among teachers and students remains a major challenge. This Community Service Program aimed to improve digital literacy through training in the use of e-learning platforms. Activities were carried out in several stages: needs assessment, socialization, training, mentoring, and evaluation. The training materials included the introduction to platforms such as Google Classroom and Moodle, digital class management, content development, and online assessment. The results showed a significant improvement in the skills of both teachers and students in utilizing e-learning tools. Teachers became more confident and capable of integrating technology into their teaching processes, while students became more independent and active in online learning. Additionally, the training modules and video tutorials developed during the program served as sustainable learning aids. Online discussion forums were also established to facilitate experience sharing and technical problem-solving collaboratively. This program not only had a positive impact on participants’ technical competencies but also changed their mindset regarding technology use in education. Sustainability is recommended through continued training, infrastructure improvement, and collaboration with various stakeholders. Thus, this initiative is expected to become a model for sustainable digital literacy development in educational settings, particularly in regions that are lagging behind in adopting educational technology.
Optimalisasi Media Sosial Sebagai Sarana Promosi Produk Pertanian Desa Nisa Dienwati; Nana Suarna; Achmad Fikri Ulumudin; Achmad Luthfi
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.
Pengembangan Aplikasi Informasi Posyandu dalam Meningkatkan Layanan Kesehatan Ibu dan Anak Nana Suarna; Nining Rahaningsih; Euis Fadilah; Farah Nur Farida
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 04 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

This Community Partnership Program aims to develop a Posyandu information system application to improve the efficiency and effectiveness of maternal and child health services. This application is designed to facilitate Posyandu officers in managing patient data, recording health histories, monitoring child development, and providing relevant health information. The application development includes needs analysis, user interface (UI) design, implementation of key features, and application usage training for Posyandu officers. It is expected that with this application, the quality of health services at Posyandu can be improved, and health information access for mothers and children can be facilitated.
Analisa Penggunaan Metode Lexicon Based Dan Algoritma Naive Bayes Pada Sentimen Ulasan Aplikasi Duolingo Muhammad Abib Allesdio; Ade Irma Purnamasari; Irfan Ali; Nana Suarna; Agus Bahtiar
Jurnal Sistem Informasi dan Teknologi Vol 6 No 2 (2026): Jurnal Sistem Informasi dan Teknologi (SINTEK)
Publisher : LPPM STMIK KUWERA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56995/sintek.v6i2.261

Abstract

Peningkatan jumlah ulasan pengguna pada aplikasi mobile membuka peluang untuk memahami persepsi dan pengalaman pengguna melalui analisis sentimen. Penelitian ini bertujuan untuk menganalisis sentimen ulasan pengguna aplikasi Duolingo yang diambil dari Google Play Store menggunakan dua pendekatan, yaitu metode lexicon-based dan algoritma Naive Bayes berbasis Python. Metode lexicon-based digunakan untuk memberikan skor polaritas berdasarkan leksikon sentimen, sedangkan Naïve Bayes diterapkan sebagai model klasifikasi dengan dukungan fitur TF-IDF. Proses penelitian meliputi tahapan pengumpulan data, preprocessing teks (cleaning, case folding, tokenisasi, stopword removal, dan stemming), pembobotan sentimen, pelatihan model, serta evaluasi performa menggunakan accuracy, precision, recall, dan F1-score. Hasil penelitian menunjukkan bahwa metode lexicon-based mampu memberikan gambaran umum polaritas ulasan, namun performanya sangat dipengaruhi oleh kelengkapan leksikon dan variasi bahasa informal pengguna. Sementara itu, algoritma Naive Bayes menunjukkan performa yang lebih stabil dan akurasi lebih tinggi dalam mengklasifikasikan sentimen dibandingkan pendekatan leksikon. Perbandingan kedua metode memperlihatkan bahwa Naive Bayes lebih efektif dalam menangani data teks pendek, tidak terstruktur, serta mengakomodasi variasi kata dan ejaan. Temuan penelitian ini memberikan pemahaman yang lebih dalam mengenai persepsi pengguna terhadap Duolingo serta menjadi referensi metodologis bagi penelitian sentiment analysis selanjutnya, khususnya yang melibatkan kombinasi metode leksikon dan klasifikasi probabilistik.
Co-Authors Abdul Ajiz Abdul Rasyid Faiq Hadinata Achmad Baihaqi Achmad Fikri Ulumudin Achmad Luthfi Ade Awaludin Ade Irma Purnamasari Adinda Aulia Putri Akhyanto Akhyanto Annisa Annastia Suarna Arye Fandia Kusuma Basysyar, Fadhil Muhammad Cep Lukman Rohmat Danya Rizki Chaerunisa Dion Nugraha Dita Amalia Rizki Dita Rizki Amalia Dodi Solahudin Dodi Solihudin Dwi Atmoko Elisa Sriyulia Ervina Mahara Euis Fadilah Fadhil Muhammad Basysyar Fadrin Helmi Farah Nur Farida Fathurrohman Febriyana Lorenza Gildan Jaya Muhammad Ramadhan Heliyanti Susana Herman Iin Irfan Ali Kuju Susilawati Lin Lin Martanto . Melisa Hikari Melva Regina Arpratika Moh Nurdayat Dayat Mohamad Ibnu Abas Muhammad Abib Allesdio Muhammad Alfian Nur Rahmat Mulyawan Mulyawan Mulyawan Nana Mulyanasari Nanda Septian Nining Rahaning Nining Rahaningsih Nining Rahaningsih Nisa Dieanwati Nuris Nisa Dienwati Nur Kholidin Nursyifa Puspa Ar-rahmi Slamet Nurul Ibnu Al Muharom Odi Nurdiawan Opiana . Raditya Danar Dana Rini Astuti Rini Astuti Ryan Hamonangan Saeful Anwar Sayudin Sayudin Shandy Alfian Sri Muflikah Kurniarti Sulaeman Syaeful Annas Usup Supendi Willy Prihartono Yudhistira Arie Wijaya