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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Teknologi Informasi dan Ilmu Komputer Panrita Abdi - Jurnal Pengabdian pada Masyarakat Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization International Journal of Artificial Intelligence Research Journal of Information Technology and Computer Science (JOINTECS) Jurnal Ilmiah FIFO PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Conference on Innovation and Application of Science and Technology (CIASTECH) JURTEKSI Jurnal Abdimas Mahakam METIK JURNAL Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jusikom: Jurnal Sistem Informasi Ilmu Komputer Systematics Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Informasi dan Teknologi Buana Information Technology and Computer Sciences (BIT and CS) JATI (Jurnal Mahasiswa Teknik Informatika) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Indonesian Journal of Electrical Engineering and Computer Science Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat JIKA (Jurnal Informatika) Jurnal Sistem Komputer dan Informatika (JSON) Infotek : Jurnal Informatika dan Teknologi Journal of Applied Data Sciences Jurnal Cahaya Mandalika Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Djtechno: Jurnal Teknologi Informasi Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Mechanical Engineering for Society and Industry Dirgamaya: Jurnal Manajemen dan Sistem Informasi J-Intech (Journal of Information and Technology) Automotive Experiences Journal of Informatics and Communication Technology (JICT) Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Informatika Teknologi dan Sains (Jinteks) Abdimas Journal International of Lingua and Technology Jurnal Komtekinfo Jurnal Buana Pengabdian Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Innovative: Journal Of Social Science Research JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal) Jurnal Polimesin Journal of Informatics and Communication Technology (JICT) CSRID Jurnal SINTA: Sistem Informasi dan Teknologi Komputasi Journal of Information Technology
April Lia Hananto
Universitas Buana Perjuangan Karawang, Indonesia
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Journal : METIK JURNAL

 1 
Perbandingan Metode Klasifikasi Sentimen Analisis Penggunaan E-Wallet Menggunakan Algoritma Naïve Bayes dan K-Nearest Neighbor Fatmanisa Mumpuni Delta Maharani; April Lia Hananto; Shofa Shofia Hilabi; Fitria Nur Apriani; Agustia Hananto; Baenil Huda
METIK JURNAL Vol 6 No 2 (2022): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v6i2.372

Abstract

Dompet digital atau yang sering disebut dengan e-wallet dalam kurun waktu belakangan ini semakin meningkat dalam penggunaannya. Hasil survei Jakpat, dalam melakukan pembayaran digital sebanyak 94% responden menggunakan dompet digital (e-wallet). Banyak sekali masyarakat yang mulai merasakan manfaat dari e-wallet sendiri. Didalamnya, e-wallet menawarkan berbagai fitur yang salah satunya kepraktisan dan efisiensi dalam bertransaksi dan keamanan dalam transaksi. Tujuan dari penelitian ini untuk mencari algoritma terbaik dalam menentukan klasifikasi sentimen analisis penggunaan e-wallet dengan membandingkan dua algoritma yaitu Naïve Bayes (NB) dan K-Nearest Neighbor (k-NN). Sebanyak 1292 data menggunakan kata kunci yang sesuai dengan e-wallet yang akan digunakan, diambil pada tanggal 17 Oktober – 11 November 2022 melalui proses crawling data twitter. Proses tersebut dimulai pada tahap pengumpulan dataset twitter, pelabelan data, Text Processing, Cross Validation model klasifikasi, evaluasi accuracy hingga didapatkan hasil akhir yaitu dibandingkan dengan model klasifikasi Naïve Bayes, hasil akurasi algoritma k-NN lebih tinggi. Hasil accuracy dari masing-masing model klasifikasi yaitu NB sebesar 73.03% dan k-NN sebesar 89.44%, precision NB sebesar 21.40% dan k-NN sebesar 65.45%, dan recall NB sebesar 48.32% dan k-NN sebesar 22.25%. Dari hasil perbandingan metode membuktikan bahwa algoritma k-NN dengan accuracy terbaik yaitu sebesar 89.44%.
Klasifikasi Sentimen Komentar Pengguna pada Aplikasi Ruangguru Menggunakan Algoritma Naive Bayes Yovika Aprianti; Tukino; Hananto, April Lia; Hilabi, Shofa Shofiah
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 1 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v9i1.1023

Abstract

The advancement of digital technology has encouraged the increasing use of online learning applications such as Ruangguru, while simultaneously fostering various innovations in the field of education. Ruangguru, as one of the most popular educational applications in Indonesia, receives thousands of user comments that can be analyzed to reflect user satisfaction and perception. This study aims to automatically classify user comments based on the sentiments they contain using the Naïve Bayes Classifier algorithm. This approach is expected to help Ruangguru developers better understand user needs and preferences, thereby improving service quality. The dataset was obtained from the Google Play Store platform, consisting of approximately 5,000 comments collected during the period from October 28 to December 31, using the google-play-scraper tool. The application of the Multinomial Naïve Bayes algorithm with TF-IDF weighting was employed to analyze the data, resulting in four sentiment categories: Baik Sekali, Baik, Cukup Baik, and Kurang Baik. Evaluation of the model was conducted using accuracy, precision, recall, and F1-score metrics. With an accuracy rate of 84.83%, the model correctly predicted the actual labels in approximately 85% of the test data. The model also achieved an F1-score of 85%, a precision of 86%, and a recall of 85%. The classification results revealed that the “Baik” category dominated with a proportion of 28.3%, followed by “Baik Sekali” at 24.3%, “Cukup Baik” at 24.0%, and “Kurang Baik” at 23.4%. These findings indicate that the model maintains a reasonable balance between sensitivity and accuracy in sentiment classification. Therefore, the Naïve Bayes Classifier method is capable of automatically identifying user opinions and has the potential to serve as a valuable tool in sentiment analysis for online learning services.
Co-Authors - Faqih AA Sudharmawan, AA Abdullah Abdullah Abdullahi Tanko Mohammed Abdullahi Tanko Mohammed Adittia Agustian Afra, Alfina Fadhilah Agneresa Agneresa Ahmed Sule Ahnaf, Naufal Zubdi Ajie, Prasetyo Alparizi, Muhamad Iqbal Alpian, Yayan alzahra, alika aziza Anthony Chukwunonso Opia Aprilia Putri Nardilasari Arkan Hilman Hakim Asep Haris Atmaja, Rashelin Zahra Aulia, Aldi Aviv Yuniar Rahman Aviv Yuniar Rahman Aviv Yuniar Rahman Aviv Yuniar Rahman Baenil Huda Baenil Huda Baenil Huda Baenil Huda Bagus Setyawan Baihaqi, Kiki Ahmad Bayu Priyatna Bayu Priyatna Bayu Priyatna Berkah*, Kamila Candra Zonyfar Catur Nugroho Danny Manongga Dean Ariesta Aziz Deddy Prihadi Detrie Noviani Dhany Hermansyah Dien Noviany Rahmatika Edrina Christine, Natalie Eichler, Luiz Eko Pramono Eko Sediyono Esam Abu Baker Ali Fadli, Muhammad Abil Fatlun, Aulia Fatmanisa Mumpuni Delta Maharani Fauzi Ahmad Muda Firdaus, Mohamad Ricky Firman Nurdiansyah Firman Nurdiyansyah Fitri Nur Masruriyah, Anis Fitri Nurapriani Fitria Nur Apriani Fitria Nurapriani Fuad anwar yuwono Guntur, Muhamad Hananto, Agustia Hanny Hikmayanti Handayani Hayati, Cucu Hendry Henry Adam Hibatullah, Muhammad Hafizh Hilabi, Shofa Shofia Hilabi, Shofa Shofiah Hilabi, Shofa Shofiah Hindriyanto Dwi Purnomo Huda Huda Huda, Baenil Ihsan, Mohammad Maftuh Ihwan Ghazali Ilman Kadori Indra Kurniawan Indri Oktapiani Irawan, Bei Harira Irwan Sembiring Istiadi Isyanto, H. Puji Iwan Setiawan Iwan Setyawan Joko Purwanto Kamila Berkah* Kurnia, Nisa Lutfiah, Siti Mega Tri Kurnia Melisa Miswadi Miswadi Moh Hasan Basri Mohamad Ricky Firdaus Mubarok, Piky Muhamad Djaka Permana Muhammad Idris Muhammad Idris Muhammad Idris Muhammad Nova Muhammad Zacky Asy'ari Muthia Nur Rizky Fitriani Nisa Kurnia Novalia, Elfina Novia Cahya Utami Nur ‘Azah Nurapriani, Fitria Nurapriani, Nurapriani Nurfajria, Dera Paryono, Tukino Permana Andi Paristiawan Permana Andi Paristiawan Pradana Rizki Maulana Prasetya, Rafli Pratama, Daffa Agung Priatna, Bayu Priyatna , Bayu Priyatna, Bayu Purnomo, Hendryanto Dwi Putri Indraswari Reformasi, Era Rieke Retnosary Rosalina, Elsa Rukmanta Jayawiguna Ruliansyah Ruliansyah Ruliansyah Ruliansyah, Ruliansyah Saepul Aripiyanto Safarudin Gazali Herawan Sari, Nurnilam Sarina Sulaiman Sarina Sulaiman Setiawan, Feddy Wanditya Setiawan, Pratama Wahyu Shofa Shofia Hilabi Shofa Shofia Hilabi Shofa Shofia Hilabi Shofa Shofiah Hilabi Shofa Shofiah Hilabi Shofa Shofiah Hilabi Shofa Sofiah Hilabi Shofiah Hilabi, Shofa Shuaibu Alani Balogun Sigit Widiyanto Silva, Tiago Siti Masruroh Soleman, Soleman Sopian, Jajang Sri Mumpuni Ngesti Rahaju Sudrajat, Deden Renhad Suhada, Karya Surala, Lyvia Susilawati, Agnes Dwita Syah Alam Tita Puspita Sari Tukino Tukino Tukino Tukino Tukino Tukino, Tukino Tukino, Tukino Wahiddin, Deden Yazid, Muhammad Abi Yovika Aprianti Yoviyardi, Rama