Article Per Year (5 Year)
p-Index From 2020 - 2025
2.771
P-Index
This Author published in this journals
All Journal Jurnas Nasional Teknologi dan Sistem Informasi INOVTEK Polbeng - Seri Informatika Digital Zone: Jurnal Teknologi Informasi dan Komunikasi J-SAKTI (Jurnal Sains Komputer dan Informatika) EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science bit-Tech Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics MEANS (Media Informasi Analisa dan Sistem) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) J-SAKTI (Jurnal Sains Komputer dan Informatika) Indonesian Journal of Community Empowerment Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Kharisma, Ivana Lucia
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Energy Engineering Environmental Science Public Health

Published : 16 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : bit-Tech

 1 
Implementation of Technique for Order Preference by Similarity to Ideal Solution for Selecting Content Kharisma, Ivana Lucia; Yustiana, Indra; Zahra, Falya Amrina
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2768

Abstract

This study addresses the challenge faced by the Sukabumi Creative Hub Instagram team in identifying the most engaging content by proposing a web-based Decision Support System (DSS) utilizing the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Instagram, as a dominant social media platform in Indonesia, serves as a vital tool for promoting local creative industries, yet current content evaluation lacks systematic analysis. The system developed ranks 62 content items based on three engagement metrics—likes, views, and shares—weighted at 5, 3, and 1 respectively. Data were processed using Microsoft Excel and visualized through an Input-Process-Output (IPO) model. The results show that “Rekap Merangkum Sukabumi” achieved the highest relative closeness (RC = 0.8793), demonstrating TOPSIS’s effectiveness in ranking content based on proximity to ideal engagement levels. Compared to previous studies that applied TOPSIS in different contexts, this research offers a novel contribution by applying it to localized social media content, filling a gap in digital content analytics literature. Despite limitations such as subjective weighting, platform specificity, and manual calculations, the system offers a replicable, structured approach to content evaluation, with implications for improved social media strategy and future research in automated, cross-platform DSS applications. Ultimately, this study bridges practical needs in creative content management with theoretical development in decision support systems for digital engagement analysis.
Co-Authors Agung Gumelar Al-Basori, Muhamad Cepnur Alhidamkara, Salman Alun Sujjada Angelina, Nadila Apriliyanti, Silvi Ayu Lestari, Melani Bila, Nida Aulia Salsa Dewi, Dhita Diana Fatalifi, Amerjid Ghulamson Fergina, Anggun Firdaus, Asep Rizki Gunawan, Muhamad Sahrul Hafidzh Al Muhiddin, Muhammad Ibnu Sina, Rivaldi Insany, Gina Purnama Kamdan Khairiyah Ivanka, Najwa Kustandi, Agus Mamun, Yuliana Maulana Yusuf Muhammad Dzulqarnain, Fajar Munandar, Rifki Arief Natanael, Brillian Aji Natasya, Sandra Pauzi, Yoviar Perkasa, M. Juang Pajri Prayoga , Rizki Haddi Purnama Insany, Gina Ramdan, Hari Muhammad Rohmat, Satria Rizki Rosmawati Rosmawati Sebayang, Alvin Christoper Septiani, Dhea Ayu Serliani, Siska Meyisa Amelia Somantri, S Somantri, Somantri Sukmawan, Dede Sulaeman, Asep Surahman Tresna Ati, Mutiara Annisa Yasin, Fakhriyal Riyandi Yustiana, Indra Zahra, Falya Amrina Zaki Hibatullah, Muhammad