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J-Com (Journal of Computer)
Published by STMIK Royal Kisaran
ISSN : -     EISSN : 2775801X     DOI : 10.33330
Core Subject : Science,
Computer Science & IT
J-Com (Journal of Computer) is a scientific journals that contains research results conducted by collaborating students with lecturers. J-Com published third a year on March, July, November.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 11 Documents
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Search results for , issue "Vol. 5 No. 1 (2025): MARET 2025" : 11 Documents clear
ANALISIS DATA SAINS: GENDER, PERTUMBUHAN INSTAGRAM DAN STRATEGI PEMASARAN GLOBAL DIGITAL turnandes, Yogo; Afrilli, Rezka; Andeskom, Gogon
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.v5i1.3894

Abstract

Abstract: This study aims to analyze the influence of gender on user responses to social media strategies on the Instagram platform by utilizing data science techniques. The methodology includes collecting user interaction data based on gender, statistical analysis, and applying machine learning algorithms to identify response patterns. The results reveal significant differences in how male and female users respond to social media content and campaigns, affecting marketing strategy effectiveness. Data science analysis showed that the K-Means Clustering method segmented users into three groups based on interaction patterns, with female users showing the highest engagement rate (18%) compared to male users (12%). The Decision Tree model identified gender as the most dominant predictor of engagement (40%), followed by user growth (25%) and content type (20%). The Random Forest model validated that gender-targeted strategies increased marketing effectiveness by up to 22%. Multivariate regression revealed a positive effect of female user proportion (+0.45) and a negative effect of male user proportion (−0.12) on engagement. In conclusion, a deeper understanding of gender-based response differences can assist companies in designing more targeted social media strategies and enhancing engagement.            Keywords: gender; social media response; instagram; data science; marketing strategy Abstrak: Penelitian ini bertujuan untuk menganalisis bagaimana pengaruh gender memengaruhi respons pengguna terhadap strategi media sosial di platform Instagram dengan memanfaatkan teknik data sains. Metode yang digunakan meliputi pengumpulan data interaksi pengguna berdasarkan gender, analisis statistik, dan penerapan algoritma machine learning untuk mengidentifikasi pola respons. Hasil penelitian menunjukkan adanya perbedaan signifikan dalam cara pengguna laki-laki dan perempuan merespons konten dan kampanye media sosial, yang berdampak pada efektivitas strategi pemasaran. Analisis data sains menunjukkan bahwa metode K-Means Clustering berhasil mengelompokkan pengguna ke dalam tiga segmen berdasarkan pola interaksi, dengan segmen perempuan menunjukkan tingkat engagement tertinggi (18%) dibandingkan laki-laki (12%). Model Decision Tree mengidentifikasi gender sebagai faktor paling dominan terhadap engagement dengan kontribusi sebesar 40%, disusul oleh pertumbuhan pengguna (25%) dan jenis konten (20%). Random Forest memvalidasi bahwa strategi yang disesuaikan berdasarkan gender meningkatkan efektivitas pemasaran hingga 22%. Regresi multivariat menunjukkan bahwa proporsi pengguna perempuan berkontribusi positif sebesar 0,45 poin terhadap engagement, sedangkan pengguna laki-laki berkontribusi negatif sebesar -0,12. Kesimpulannya, pemahaman mendalam tentang perbedaan respons berdasarkan gender dapat membantu perusahaan dalam merancang strategi media sosial yang lebih tepat sasaran dan meningkatkan engagement.Kata kunci: gender; respons media sosial; instagram; data sains; strategi pemasaran

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