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UPT Publikasi Ilmiah, Universitas Islam Bandung. Jl. Tamansari No. 20, Bandung 40116, Indonesia, Tlp +62 22 420 3368, +62 22 426 3895 ext. 6891
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Bandung Conference Series: Industrial Engineering Science
Published by Universitas Islam Bandung
ISSN : -     EISSN : 28282132     DOI : https://doi.org/10.29313/bcsies.v2i2
Core Subject : Science, Engineering,
Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering
Bandung Conference Series: Industrial Engineering Science (BCSIES) menerbitkan artikel penelitian akademik tentang kajian teoritis dan terapan serta berfokus pada Teknik Industri dengan ruang lingkup, NASA-TLX, Alat Kualitas, Analisis SWOT, Analytical Hierarchy Process, Arsitektur Sistem Informasi Layanan Administrasi, Basis Data, Cetak biru Pelayanan, Failure Mode And Effect (FMEA), Fault Tree Analysis (FTA), First Come First Served, Framework for the Application of Systems Thinking (FAST), Hay Method, Human Resource Scorecard, Kuesioner 7 waste, Model tingkat aspirasi Quality Function Deployment (QFD), Model-driven development Six sigma, Multichannel Single Phase, NASA-TLX, Notasi kendall, Pelayanan, Pergudangan, Persediaan Sistem informasi, PIECES, Proses antrian, QFD (Quality Function Deployment) Lean manufacturing, Quantitative Strategic Planning Matrix (QSPM), Root Cause Analysys, Seven Tools, Sistem Antrian, Sistem Informasi, Strategi Pengembangan Model Driven, Stripping Obat Kualitas, Take Home Pay, Traffic Light System, TRIZ Kualitas, Work Sampling. Prosiding ini diterbitkan oleh UPT Publikasi Ilmiah Unisba. Artikel yang dikirimkan ke prosiding ini akan diproses secara online dan menggunakan double blind review minimal oleh dua orang mitra bebestari.
Arjuna Subject : Teknik (semua kategori) - Tenik Industri dan Manufaktur
Articles 1 Documents
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Perancangan Strategi Pemasaran Berbasis Analisis Sentimen Naive Bayes Firman Aji Utama; Ahmad Arif Nurrahman; Dewi Shofi Mulyati; Suliadi
Bandung Conference Series: Industrial Engineering Science 561-568
Publisher : UNISBA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/bcsies.v6i2.25756

Abstract

Abstract. Aquila Knives is a micro, small, and medium enterprise (MSME) engaged in the production and sale of kitchen knives, butcher knives, outdoor knives, and traditional Indonesian blades. In recent periods, the company experienced a 37% decline in sales, indicating the need to evaluate its marketing strategy based on customer perceptions. This study aims to analyze customer sentiment and develop a marketing strategy based on the analysis results. The dataset consists of 896 YouTube comments collected through web scraping. The analysis process includes text preprocessing, Term Frequency–Inverse Document Frequency (TF-IDF) weighting, sentiment classification using the Naïve Bayes algorithm, and Rule-Based Aspect Extraction based on Kotler’s product quality dimensions: Price, Feature, Reliability, Durability, Performance, Service, and Aesthetic. The results show that the Naïve Bayes model achieved an accuracy of 71.67%. The Performance aspect received the highest positive sentiment, while the Service aspect was dominated by negative sentiment, making it the highest priority for improvement. Based on these findings, a marketing strategy was developed using the Marketing Mix (4Ps) and translated into the 7 StoryBrand framework to support content marketing. The proposed approach provides a more targeted, customer-oriented marketing strategy with the potential to improve marketing effectiveness and increase Aquila Knives' sales. Abstrak. Aquila Knives merupakan usaha mikro, kecil, dan menengah (UMKM) yang bergerak di bidang produksi dan penjualan pisau, seperti pisau dapur, pisau jagal, pisau outdoor, dan senjata tradisional Indonesia. Dalam beberapa periode terakhir, perusahaan mengalami penurunan penjualan sebesar 37%, yang mengindikasikan perlunya evaluasi strategi pemasaran berdasarkan kebutuhan pelanggan. Penelitian ini bertujuan menganalisis sentimen pelanggan serta merancang strategi pemasaran berbasis hasil analisis tersebut. Data penelitian berupa 894 komentar YouTube yang diperoleh melalui web scraping. Tahapan analisis meliputi preprocessing, pembobotan kata menggunakan TF-IDF, klasifikasi sentimen dengan algoritma Naïve Bayes, serta Rule-Based Aspect Extraction berdasarkan aspek kualitas produk Kotler, yaitu Price, Feature, Reliability, Durability, Performance, Service, dan Aesthetic. Hasil penelitian menunjukkan bahwa Naïve Bayes menghasilkan akurasi sebesar 71,67%. Aspek Performance memperoleh sentimen positif tertinggi, sedangkan aspek Service didominasi sentimen negatif sehingga menjadi prioritas perbaikan. Berdasarkan hasil tersebut, disusun strategi pemasaran menggunakan Marketing Mix (4P) yang diterjemahkan ke dalam kerangka 7 Story Brand sebagai dasar content marketing. Hasil penelitian menunjukkan bahwa pendekatan ini menghasilkan strategi pemasaran yang lebih terarah, berbasis kebutuhan pelanggan, dan berpotensi meningkatkan efektivitas pemasaran serta penjualan Aquila Knives.

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