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angreyani, jeny
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Computer Science & IT Economics, Econometrics & Finance Education Social Sciences

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ANALISIS SENTIMEN ULASAN E-COMMERCE SHOPEE DENGAN MENGGUNAKAN ALGORITMA NAIVE BAYES angreyani, jeny; Pernando, Yonky
J-Com (Journal of Computer) Vol 5, No 1 (2025): MARET 2025
Publisher : LPPM STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/j-com.v5i1.3570

Abstract

Abstract: In this study, an analysis of the use of the Naive Bayes algorithm for sentiment analysis of reviews from Shopee app users on the Google Play Store was conducted, with classification divided into three categories: positive, negative, and neutral. To improve data quality, a preprocessing process was carried out with stages of cleaning, case folding, normalization, stop word removal, stemming, and tokenizing. Next, the text is formatted using the TF-IDF method to facilitate classification. For this data, the Naive Bayes model is used, which has an accuracy rate of 87% in detecting sentiment. Positive and negative categories can be easily identified compared to neutral sentiments due to the smaller amount of neutral data. Overall, the Naive Bayes algorithm successfully analyzed user sentiments well. The research can be developed with other algorithm methods, such as SVM, K-NN, or Decision Tree, in order to compare the performance of various algorithms.Keywords: sentiment analysis; naive bayes; user reviews; e-commerce; shopee Abstrak: Dalam penelitian ini dilakukan analisis penggunaan algoritma Naive Bayes untuk analisis sentimen review dari pengguna aplikasi Shopee di Google Play Store, klasifikasi dibagai menjadi 3 kategori yaitu positif, negatif, dan netral. Untuk meningkatkan kualitas data, dilakukam proses preprocessing dengan tahap cleanimg, case folding, normalisasi, stopword removal, stemming, dan tekonezing. Selanjutnya, teks diformat menggunakan metode TF-IDF untuk memudahkan klasifikasi. Untuk data ini, model Naive Bayes digunakan, yang memiliki tingkat akurasi 87% dalam mendeteksi sentimen. Kategori positif dan negatif dapat dengan mudah diidentifikasi dibadingkan sentiemen netral karena jumlah data netral yang lebih sedikit. Secara keseluruhan, algoritma Naive Bayes berhasil menganalisis perasaan pengguna dengan baik. Penelitian dapat dikembangkan dengan algoritma metode lain, seperti SVM, K-NN, atau Decision Tree, guna membandingkan kinerja berbagai algoritma.Kata kunci: analisis sentiment; naive bayes; ulasan pengguna; e-commerce; shopee
SIMULASI TOPOLOGI JARINGAN BERBASIS IOT UNTUK PERANGKAT RUMAH TANGGA MENGGUNAKAN CISCO PACKET TRACER Meidianto, Meidianto; Anggeliani, Cynthia; Angreyani, Jeny; Pernando, Yonky
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 2 (2025): May 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i2.2994

Abstract

Abstract: This study aims to simulate the implementation of the Internet of Things (IoT) in household devices using Cisco Packet Tracer. In this simulation, various devices such as smart lights, fans, air conditioners, automatic doors, automated windows, and smoke detectors were successfully controlled via smartphone with the assistance of a Home Gateway. The research was conducted using a structured simulation method, starting from planning to network topology evaluation. The simulation results show that the integration of IoT devices can function efficiently and stably. Each testing scenario from unlocking doors and adjusting fan speed to smoke detection was executed successfully and demonstrated real-time responses. This success highlights that Cisco Packet Tracer is an effective and cost-efficient tool for designing and testing smart home systems before real-world implementation. Moreover, the ease of controlling devices through mobile gadgets adds an extra layer of convenience for users. This study provides practical and applicable insights into the benefits of IoT technology in household settings and opens further opportunities for future smart home development. Keyword: Internet of Things (IoT); Cisco Packet Tracer; Smart Home; Home Gateway; Network Simulation Abstrak: Penelitian ini bertujuan untuk mensimulasikan penerapan Internet of Things (IoT) dalam perangkat rumah tangga dengan menggunakan Cisco Packet Tracer. Dalam simulasi ini, berbagai perangkat seperti lampu pintar, kipas angin, AC, pintu otomatis, jendela otomatis, dan detektor asap berhasil dikendalikan melalui smartphone dengan bantuan Home Gateway. Proses penelitian ini dilakukan dengan metode simulasi yang terstruktur, mulai dari perencanaan hingga evaluasi topologi jaringan. Hasil simulasi menunjukkan bahwa integrasi perangkat IoT dapat berfungsi dengan efisien dan stabil. Setiap skenario pengujian, mulai dari membuka pintu, mengatur kecepatan kipas, hingga mendeteksi asap, berhasil dilaksanakan dengan baik dan menunjukkan respons secara real-time. Keberhasilan ini menggarisbawahi bahwa Cisco Packet Tracer adalah alat yang efektif dan ekonomis untuk merancang serta menguji sistem rumah pintar sebelum diterapkan dalam kenyataan. Selain itu, kemudahan dalam mengontrol perangkat melalui gadget mobile memberikan kenyamanan tambahan bagi pengguna. Penelitian ini memberikan wawasan praktis dan aplikatif tentang manfaat teknologi IoT dalam rumah tangga serta membuka peluang lebih lanjut untuk pengembangan smart home di masa mendatang. Kata kunci: Internet of Things (IoT); Cisco Packet Tracer; Smart Home; Home Gateway; Simulasi Jaringan
ANALISIS SENTIMEN ULASAN E-COMMERCE SHOPEE DENGAN MENGGUNAKAN ALGORITMA NAIVE BAYES angreyani, jeny; Pernando, Yonky
J-Com (Journal of Computer) Vol. 5 No. 1 (2025): MARET 2025
Publisher : STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/j-com.v5i1.3570

Abstract

Abstract: In this study, an analysis of the use of the Naive Bayes algorithm for sentiment analysis of reviews from Shopee app users on the Google Play Store was conducted, with classification divided into three categories: positive, negative, and neutral. To improve data quality, a preprocessing process was carried out with stages of cleaning, case folding, normalization, stop word removal, stemming, and tokenizing. Next, the text is formatted using the TF-IDF method to facilitate classification. For this data, the Naive Bayes model is used, which has an accuracy rate of 87% in detecting sentiment. Positive and negative categories can be easily identified compared to neutral sentiments due to the smaller amount of neutral data. Overall, the Naive Bayes algorithm successfully analyzed user sentiments well. The research can be developed with other algorithm methods, such as SVM, K-NN, or Decision Tree, in order to compare the performance of various algorithms.Keywords: sentiment analysis; naive bayes; user reviews; e-commerce; shopee Abstrak: Dalam penelitian ini dilakukan analisis penggunaan algoritma Naive Bayes untuk analisis sentimen review dari pengguna aplikasi Shopee di Google Play Store, klasifikasi dibagai menjadi 3 kategori yaitu positif, negatif, dan netral. Untuk meningkatkan kualitas data, dilakukam proses preprocessing dengan tahap cleanimg, case folding, normalisasi, stopword removal, stemming, dan tekonezing. Selanjutnya, teks diformat menggunakan metode TF-IDF untuk memudahkan klasifikasi. Untuk data ini, model Naive Bayes digunakan, yang memiliki tingkat akurasi 87% dalam mendeteksi sentimen. Kategori positif dan negatif dapat dengan mudah diidentifikasi dibadingkan sentiemen netral karena jumlah data netral yang lebih sedikit. Secara keseluruhan, algoritma Naive Bayes berhasil menganalisis perasaan pengguna dengan baik. Penelitian dapat dikembangkan dengan algoritma metode lain, seperti SVM, K-NN, atau Decision Tree, guna membandingkan kinerja berbagai algoritma.Kata kunci: analisis sentiment; naive bayes; ulasan pengguna; e-commerce; shopee
Co-Authors Anggeliani, Cynthia Meidianto, Meidianto Pernando, Yonky