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All Journal Jurnal Informasi dan Teknologi BALQIS: Journal of Business Innovation and Digital Marketing BALQIS: Journal of Business Innovation and Digital Marketing
Memet Sanjaya
Politeknik Takumi
Computer Science & IT Economics, Econometrics & Finance

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Optimizing Website Ranking Using Long-Tail Keywords and Internal Linking: A Case Study Memet Sanjaya; Rizaldi Putra; Deni Utama; Arif Prayoga
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.645

Abstract

This study proposes a structured and cost-effective Search Engine Optimization (SEO) strategy through the application of long-tail keyword targeting and internal linking. Conducted across three websites within the same corporate group, this research investigates how internal links and keyword mapping can collectively improve organic rankings. Each high-volume keyword was developed into long-tail variations and implemented into topic-specific articles, supported by contextual internal and cross-site linking. Website A, as the parent site, was used strategically to distribute link authority to other sites. In a two-month observation, keyword rankings showed significant improvements, particularly for underperforming domains. The results confirm that collaborative SEO using content relevance and internal link equity distribution can enhance visibility without relying on paid backlinks.
Pelatihan Pembuatan Konten Media Sosial Menggunakan Teknologi Ai Untuk Mendapatkan Passive Income Bagi Siswa Smk di Cikarang Memet Sanjaya
BALQIS : Journal of Business Innovation and Digital Marketing Vol. 1 No. 2 (2025): December 2025
Publisher : Program Studi Bisnis Digital - Fakultas Ekonomi dan Bisnis Islam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/balqis.v1i2.10484

Abstract

This study aims to analyze the improvement of digital literacy and AI-based content production skills among vocational high school (SMK) students through structured training. The research employed a quantitative approach using a one-group pretest–posttest design. A total of 33 students participated in the training, while 22 paired responses met the criteria for statistical analysis. The research instrument consisted of Likert-scale questionnaires and open-ended questions measuring content creation skills, AI knowledge, perceptions of the economic potential of digital content, and experience using AI tools. Data were analyzed using the Wilcoxon Signed Rank Test due to non-normal data distribution. The results indicate a statistically significant improvement across all measured indicators, with p-values < 0.001. These findings demonstrate that structured AI-based training is effective in enhancing digital literacy and preparing vocational students to produce economically valuable digital content. This study contributes empirical evidence to the development of AI-based digital literacy learning models in vocational education.
Pelatihan Pembuatan Konten Media Sosial Menggunakan Teknologi Ai Untuk Mendapatkan Passive Income Bagi Siswa Smk di Cikarang Memet Sanjaya
BALQIS : Journal of Business Innovation and Digital Marketing Vol. 1 No. 2 (2025): December 2025
Publisher : Program Studi Bisnis Digital - Fakultas Ekonomi dan Bisnis Islam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30983/balqis.v1i2.10484

Abstract

This study aims to analyze the improvement of digital literacy and AI-based content production skills among vocational high school (SMK) students through structured training. The research employed a quantitative approach using a one-group pretest–posttest design. A total of 33 students participated in the training, while 22 paired responses met the criteria for statistical analysis. The research instrument consisted of Likert-scale questionnaires and open-ended questions measuring content creation skills, AI knowledge, perceptions of the economic potential of digital content, and experience using AI tools. Data were analyzed using the Wilcoxon Signed Rank Test due to non-normal data distribution. The results indicate a statistically significant improvement across all measured indicators, with p-values < 0.001. These findings demonstrate that structured AI-based training is effective in enhancing digital literacy and preparing vocational students to produce economically valuable digital content. This study contributes empirical evidence to the development of AI-based digital literacy learning models in vocational education.
Co-Authors Arif Prayoga Deni Utama Rizaldi Putra