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Sustainable Business Models for Creative Startups in the Digital Era Judijanto, Loso; Khamaludin, Khamaludin; Mahmudin, Mahmudin; Arisa, Ma’rifani Fitri
Journal of Social Entrepreneurship and Creative Technology Vol. 2 No. 1 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jseact.v2i1.2055

Abstract

The rise of the digital era has transformed the way businesses operate, especially for startups in the creative industries. As digital technologies reshape market dynamics, the need for sustainable business models that can adapt to rapid changes and ensure long-term success has become crucial. Creative startups, often operating in a highly competitive and fast-evolving environment, face unique challenges in maintaining financial stability while staying innovative. This research aims to explore sustainable business models for creative startups in the digital era, identifying strategies that can drive growth, profitability, and resilience. The study uses a mixed-methods approach, combining qualitative case studies of successful creative startups with quantitative surveys to assess common practices and challenges. Findings reveal that startups employing flexible, customer-centric business models, leveraging digital tools for global reach, and emphasizing continuous innovation are more likely to achieve sustainability. Moreover, the integration of sustainable practices, such as environmentally conscious production and ethical business strategies, has shown to contribute to long-term success. The study concludes that creative startups in the digital era must adopt adaptable, tech-driven business models that prioritize customer engagement and sustainability. By embracing digital transformation, startups can not only survive but thrive in a rapidly changing business landscape.
User Motivation Level Analysis of SME Collaboration Gamification Marisa, Fitri; Uda, Tonich; Maukar, Anastasia Lidya; Andarwati, Mardiana; Wardhani, Arie Restu; Handini, Mia
JOIV : International Journal on Informatics Visualization Vol 6, No 3 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.3.791

Abstract

One of the problems of SME is the low motivation to collaborate; the lack of research on exploring the motivation to collaborate is an issue that needs to be focused on solving. Objectives. This research aims to explore the level and type of motivation that influences SME's interest in collaborating to provide new insights for SME managers to apply appropriate treatment in developing collaborative activities. This study analyses six octalysis core drives that affect user interest in the use of SME collaboration gamification applications involving 293 SME respondents in the East Java Province. The research method is descriptive and quantitative, using Smart PLS, with a path analysis and analysis model. This study formulates six hypotheses to determine the effect of six core drives on using the collaborative gamification system. The results showed that the four constructs had a p-value less than 0.05 and a T-Statistic value greater than 1.96, while the other two constructs produced the opposite value. This finding reveals that four core drives (Epic Meaning, Development, Social Influence, and Avoidance) affect user interest in using collaborative gamification applications. In contrast, two core drives (Ownership and Unpredictable) do not affect it. The implication of this study is a recommendation for developers of collaboration-gamification systems to consider the results of this hypothesis, especially the role of core-drive catalysis as a reference in revising or developing collaborative gamification systems. Future work could apply the TAM model to analyze the technology acceptance rate of this system.
Pembelajaran Project Based Learning Memanfaatkan Aplikasi TikTok untuk Meningkatkan Kreativitas Rias Wajah Dasar Korektif Arisa, Ma’rifani Fitri
Jurnal Simki Pedagogia Vol 6 No 2 (2023): Volume 6 Nomor 2 Tahun 2023
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/jsp.v6i2.293

Abstract

The TikTok application is popular with the public as an information medium. The TikTok application is used by students, the TikTok application has makeup filters that can be a source of basic corrective makeup course makeup ideas. This can be a medium of learning so that students become interested. This study aims to utilize TikTok in the learning process by implementing project based learning in basic corrective makeup courses. This study used descriptive qualitative method. In this study using observation techniques, interviews and documentation studies. The findings of this study can describe (1) the reasons for lecturers using the TikTok makeup filter application as a source of makeup inspiration, and applying a project based le arning model so that learning is interesting and accepted by students. (2) The results of utilizing the TikTok makeup filter application have an influence on the learning process in achieving goals and effectiveness in basic corrective makeup courses (3) Obstacles and efforts in utilizing the TikTok makeup filter application, namely an unstable network.
Sentiment Analysis of the Matahari Application to Provide User Experience Insights using Support Vector Machine Rizal, Moch Arif Samsul; Vitianingsih, Anik Vega; Zangana, Hewa Majeed; Maukar, Anastasia Lidya; Marisa, Fitri
Building of Informatics, Technology and Science (BITS) Vol 7 No 3 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i3.8811

Abstract

The expansion of Indonesia's digital commerce ecosystem has pushed retail companies to strengthen the quality of their online services to remain competitive. Matahari, one of the country's leading retail brands, launched its mobile app as a platform for shopping, promotions, and customer interaction. However, user feedback on the Google Play Store indicates persistent problems with system responsiveness, ease of use, and the consistency of promotional information. This study examines sentiment patterns in 2,500 user reviews and classifies them using a Support Vector Machine (SVM) based model that incorporates three kernel types: Linear, RBF, and Polynomial. Before modelling, the text corpus underwent several pre-processing steps—such as tokenization, stopword filtering, and stemming represented numerically using TF-IDF weighting. Among all tested configurations, the Linear kernel produced the strongest results, achieving an accuracy rate of 88%. Despite a moderate distribution across categories (1030 negative, 886 neutral, and 584 positive), the model achieved consistent performance across all classes. Evaluation using Precision, Recall, and F1-Score confirmed the validity of the 88% accuracy without the need for additional sampling techniques. From a scholarly standpoint, this research adds insight into sentiment analysis for retail applications within the Indonesian context by applying a machine-learning approach. In practice, the outcomes highlight areas for improvement, particularly technical stability, the intuitiveness of user flows, and promotional clarity to support a better overall user experience.
Co-Authors Addian Nur Rijal Agustinus Noertjahyana Ahmad, Sharifah Sakinah Syed Akbar, Ismail Ali muhajir, Ali Alifia Nandira Maharani Anastasia Lidya Maukar Andy Hardianto Anik Vega Vitianingsih Anjani, Sofia Puspa Araujo, Aprilio Demetrius De Arie Restu Wardhani Arisanti, Diah Aviv Yuniar Rahman Badrussalam, Nanda Baehaqi Bagas Imadani Putra, Alif Bambang Amir Alhakim Bura, Audyel Umbu Chatarina Umbul Wahyuni Christine Ulina Tarigan Conteh, Alusine Dahlia Denny Bernardus Dewa Oka Suparwata Dini Kristianti, Dini Domingos Sinorio de Araujo, Domingos Dwi Fita Heriyawati Dwi Purnomo Efendi, Dedi Usman Elok Novita Fahmi, Muchammad Alvi Nur Fatmawati, Amelia Firman Hidayat Firman Nurdiyansyah Firman Nurdiyansyah, Firman Hajar Mukaromah Handajani, Endah Tri Esti Handini, Mia Hardiyanto, Andy Haryanto, Kurniawan Wahyu Ika Pranita Siregar Imran, Hamzah Al Indah Dwi Mumpuni Indra Dharma Wijaya, Indra Dharma Istiadi jauhar, afif Judijanto, Loso Khamaludin, Khamaludin KRISTIAWAN KRISTIAWAN Kushariyadi Kushariyadi Ladopurab, Bartolomeus Wadan Larasati, Isbalaikana Luruk, Maria Ovalia Mahmudin Mahmudin, Mahmudin Mardiana Andarwati Margaret Stevani Marilaeta Nurak, Yulita Maukar, Anastasia Maukar, Anastasia L Maukar, Anastasya Lidya Mausa Agrevinna Meidy Diliana Agustin Nahak, Redemtus Neno, Adi nisti, Melita Nova Ch. Mamuaya NURDIANSYAH, FIRMAN Nurfitri, Indah Karminia Pradana, Teguh Pramisela, Intan Yosa Pramudita, Atanasia Purnamasari, Putri Indah Puspitarini, Erri Wahyu Putra, Dimas Rossiawan Hendra Putra, Rangga Pahlevi Putri, Avira Maresa Putri, Chauliyah Fatma Putri, Jessica Ananda Rivaldiknas Gampar, Philipus Rizal, Moch Arif Samsul Rochmawati, Sofi Nur Rosario, Maria Madalena Do Rudy Joegijantoro, Rudy Salmanarrizqie, Ageng Sidi, Husri Slamet Riyadi, Slamet Riyadi Sofyan Rachma Danni, Muhammad Sufa, Siska Armawati Sufianto, Dani Suksmawati, Affi Nizar Uda, Tonich Ulfah Rahamawati, Ulya Un, Fransiskus Deni Wahyu Iriananda, Syahroni Warda Indadihayati Wardianto, Wardianto Wijaya, Indra Darma Yudi Kristyawan, Yudi Zangana, Hewa Majeed