Article Per Year (5 Year)
p-Index From 2021 - 2026
0.562
P-Index
This Author published in this journals
All Journal JPM: JURNAL PENGABDIAN MASYARAKAT Bulletin of Information Technology (BIT) Jurnal Nasional Teknologi Komputer
Rama Prameswara Ritonga
Unknown Affiliation
Aerospace Engineering Humanities Astronomy Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Medicine & Pharmacology Public Health Social Sciences Transportation Other

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Dampak Pemanfaatan Teknologi SEO dalam Pengembangan Website Promosi untuk Meningkatkan Visibilitas UMKM Pariwisata Sulistianingsih, Indri; Ade Rizka; Virdyra Tasril; Donny Sanjaya; Rama Prameswara Ritonga
JPM: Jurnal Pengabdian Masyarakat Vol. 5 No. 4 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jpm.v5i4.2424

Abstract

Digital technology development offers significant opportunities for tourism SMEs to increase their visibility and marketing reach. However, limited knowledge and practical implementation of digital marketing, especially SEO (Search Engine Optimization), remain major obstacles for tourism SMEs in Bali. This community service program aims to enhance the online visibility of Explore Tour and Travel Bali SME through the development of an SEO-optimized website and improvement of the SME team's digital capabilities. The community service partner is Explore Tour and Travel Bali SME, which operates in tour guide services and travel packages targeting both domestic and international tourists. The implementation method uses a participatory approach through five stages: (1) preparation, including problem identification and needs analysis; (2) SEO strategy planning and website content design; (3) website implementation and on-page and off-page SEO optimization accompanied by SME team training; (4) website performance evaluation and team capability assessment; and (5) sustainable development through periodic mentoring. Results show significant improvements with organic website traffic increasing by 42%, 8 keywords ranking on Google's first page, and SME revenue growing by 27% within 6 months of implementation. Positive changes were also observed in attitude aspects (78% increase in digital literacy), socio-cultural aspects (business process transformation from conventional to digital), and economic aspects (market diversification and marketing cost efficiency). This program demonstrates the effectiveness of implementing an SEO-optimized website as a strategy for enhancing visibility and sustainability of SMEs in the tourism sector.
Optimasi Struktur Website dan Kualitas Konten Berbasis SEO untuk Peningkatan Visibilitas Digital Unit Bisnis Pendidikan Vokasi Sulistianingsih, Indri; Dito Putro Utomo; Virdyra Tasril; Rama Prameswara Ritonga
Jurnal Nasional Teknologi Komputer Vol 5 No 4 (2025): Oktober 2025
Publisher : CV. Hawari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jnastek.v5i4.309

Abstract

Penelitian ini bertujuan untuk meningkatkan visibilitas digital unit bisnis pendidikan vokasi melalui optimasi struktur dan kualitas konten website berbasis Search Engine Optimization (SEO). Pendekatan yang digunakan adalah metode campuran (mixed-method), yang menggabungkan analisis kuantitatif terhadap metrik SEO dan evaluasi kualitatif terhadap keterlibatan pengguna. Penelitian dilakukan melalui enam tahap iteratif yang meliputi audit SEO, perancangan strategi, implementasi, monitoring, analisis data, serta interpretasi hasil. Proses optimasi mencakup peningkatan Core Web Vitals, responsivitas mobile, penguatan internal linking, peningkatan kualitas konten, serta penerapan prinsip E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness). Hasil penelitian menunjukkan peningkatan trafik organik sebesar 638% dalam enam bulan, rata-rata peningkatan peringkat kata kunci sebesar 39,6 posisi, serta peningkatan conversion rate sebesar 209%. Performa teknis situs juga meningkat signifikan dengan penurunan LCP sebesar 57%, FID sebesar 70%, dan CLS sebesar 71%, sehingga seluruh metrik mencapai kategori “Good”. Nilai Return on Investment (ROI) mencapai 2.060% (21,6 kali lipat), menunjukkan bahwa strategi SEO memberikan dampak tinggi dan berkelanjutan dibandingkan iklan berbayar. Penelitian ini menegaskan bahwa integrasi antara optimasi teknis, konten berkualitas, dan pengalaman pengguna merupakan faktor kunci dalam meningkatkan daya saing digital jangka panjang bagi institusi pendidikan vokasi.
Teknik Data Mining Dengan Menggunakan Algoritma Decision Tree Untuk Mengetahui Pola Pemahaman Mahasiswa Pada Matakuliah Pemrograman Sri Novida Sari; Putri Annisa; An Nisa Dian Rahma; Rama Prameswara Ritonga; Dito Putro Utomo
Bulletin of Information Technology (BIT) Vol 6 No 4 (2025): Desember 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i4.2339

Abstract

Medan State Polytechnic, as one of the leading vocational universities in Medan City, plays a crucial role in producing graduates who are ready to work and possess applied competencies according to industry needs. One of the strategic departments is the Computer Engineering and Informatics Department, which focuses on developing students' abilities in technology and programming. Programming courses are an important foundation in developing students' analytical and logical skills. However, many students still experience difficulties in understanding basic programming concepts, which results in low academic achievement and learning motivation. This study aims to identify patterns of student understanding in programming courses using the Decision Tree algorithm as a classification method. Through a data mining approach, this study attempts to extract hidden patterns from students' academic data to identify factors that influence their level of understanding. The Decision Tree algorithm was chosen because it is able to produce classification models that are easy to understand and interpret, and is effective in handling both categorical and numerical data. The research data was processed using Google Collaboratory with the help of the scikit-learn library. The testing process was carried out through the formation of a classification model, decision tree visualization, and confusion matrix analysis to measure model performance. Based on the test results, an accuracy value of 50% and an F1-score of 51.68% were obtained, indicating that the Decision Tree model has a good ability to predict and classify students' level of understanding of programming courses. Overall, this research provides an important contribution to the development of data-based learning strategies in vocational education environments. Through the results obtained, lecturers are expected to be able to adjust teaching methods according to student characteristics and abilities, so that the learning process becomes more adaptive, effective, and has a positive impact on improving student understanding of programming courses.
Co-Authors Ade Rizka An Nisa Dian Rahma Dito Putro Utomo Donny Sanjaya Putri Annisa Sri Novida Sari Sulistianingsih, Indri Virdyra Tasril