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All Journal Jurnal Keteknikan Pertanian Prosiding Semnastek POROS TEKNIK INTEKNA Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Jurnal Sains dan Informatika Jurnal Sinergitas PkM & CSR Angkasa: Jurnal Ilmiah Bidang Teknologi Jurnal Elemen Jurnal IMPACT: Implementation and Action Infotekmesin Buletin Profesi Insinyur Bubungan Tinggi: Jurnal Pengabdian Masyarakat Indonesian Journal for Social Responsibility International Journal of Mechanical Engineering Technologies and Applications (MECHTA) Journal of Mechanical Engineering, Science, and Innovation Jurnal Pengabdian Ilung (Inovasi Lahan Basah Unggul) International Journal of Innovation in Mechanical Engineering and Advanced Materials
Gunawan Rudi Cahyono
Universitas Lambung Mangkurat
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A Text Mining Approach to Analyzing the Omnichannel Retail Business Performance of the KlikIndomaret App Budianto, Akhmad Ghiffary; Suryo, Arief Trisno Eko; Zulkarnain, Andry Fajar; Cahyono, Gunawan Rudi; Rusilawati, Rusilawati; Az-Zahra, Siti Fatimah
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 26 No. 2 (2024): December 2024
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.26.2.131-144

Abstract

The evolution of Web 2.0 technology has significantly influenced the use of Android applications, enabling users to provide feedback through reviews and star ratings. In managing omnichannel retail businesses, this user-generated content serves as a valuable source of information for performance evaluation and strategic management of both online and offline operations. Large-scale user review data is well-suited for analysis through text mining, particularly in sentiment analysis, when combined with topic and keyword filtering in the business domain. This study utilizes the RoBERTa Transformer model for the sentiment classification of user reviews. Among the 520 user reviews, 211 displayed good emotion, while 309 showed negative sentiment. By applying filtering processes to topics and keywords within the omnichannel retail business domain, the study identifies "economic value" and "delivery and CRM" as priority areas for improvement. This conclusion is drawn based on the significant disparity between positive and negative sentiments. As a result, management can formulate strategies to enhance the performance and user experience of the KlikIndomaret Android application.
Peningkatan Kompetensi Siswa SMK di Bidang Computer Vision dengan Implementasi YOLO dan Raspberry Pi 4 Arief Trisno Eko Suryo; Akhmad Ghiffary Budianto; Andry Fajar Zulkarnain; Gunawan Rudi Cahyono; Rusilawati Rusilawati; Bayu Setyo Wibowo; Marcfiliadi Ezra Nugroho; Fridho Ery Dwi Atmadja; Feby Zulviana Efendi
Indonesian Journal for Social Responsibility Vol. 8 No. 01 (2026): June 2026
Publisher : LPkM Universitas Bakrie

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36782/ijsr.v8i01.543

Abstract

The rapid development of Artificial Intelligence (AI) technology up to 2025 has positioned Computer Vision (CV) as a crucial field in industrial applications, increasing the demand for competent graduates. Vocational High Schools (SMKs) are intended to prepare students for high employability; however, a situational analysis conducted at SMK Telkom Banjarbaru, South Kalimantan, Indonesia, revealed a gap in students’ understanding and practical application of CV technologies caused by limited learning resources and inadequate curriculum integration. The Community Service Program (Pengabdian kepada Masyarakat, PkM) of the Electrical Engineering Department aimed to introduce fundamental CV concepts to enhance students’ competencies and support digital literacy initiatives. The program employed a project-based training approach, combining theoretical sessions with practical demonstrations of a real-time face detection system using Raspberry Pi 4, OpenCV, and YOLO. The effectiveness of the program was evaluated through pre- and post-assessment surveys involving 30 participants (28 students and 2 supervising teachers). The results demonstrated successful implementation of an object detection system capable of detecting single and multiple faces with accuracy approaching 1.00 (100%). Survey findings indicated an increase in participants’ understanding of CV and digital literacy from 57% to 85%. Students’ comprehension of the difference between object classification and object detection improved from 64% to 89%, while their understanding of machine learning principles increased from 60% to 89%. Overall satisfaction with the program reached 89%. In conclusion, this community service program effectively bridged the competency gap and serves as a collaborative model between higher education institutions and vocational schools.
Co-Authors Abdul Ghofur Abdul Ghofur Aji Nihin Akhmad Ghiffary Budianto Akhmad Syarief Andy Nugraha Apip Amrullah Apip Amrullah Arifin, M Ilham Atmadja, Fridho Ery Dwi Az-Zahra, Siti Fathimah Az-zahra, Siti Fatimah Bayu Setyo Wibowo Dewi Dewantara, Dewi Fajar Zulkarnain, Andry Feby Zulviana Efendi Fridho Ery Dwi Atmadja Hartoyo, Muhammad Hendrawan Septian Hutabarat, Putri Pradita Isworo, Hajar Jamalulail, Nanda Jerry Iberahim Joni Riadi Joni Riadi Joni Riadi, Joni Khairunnisa Khairunnisa Khairunnisa Khairunnisa Lukmana, Wahyu M. Reynaldi Perdana Saputra M. Reynaldi Perdana Saputra Ma'ruf, Ma'ruf Marcfiliadi Ezra Nugroho Martunus Martunus Muhammad Firdaus Jauhari, Muhammad Firdaus Muhammad Muntaha Muhammad Munthaha Muhammad Nizar Ramadhan Muntaha, Muhammad Munthaha, Muhammad N. Alexius Mikael Najua, Siti Nur Noviani Haty Lala Nurahma, Yosnandia Dwi Nurmahaludin Nurmahaludin Nuryasin Qadimil Awaly Nuryasin Qadimil Awaly Obie Farobie P.S.M. Reynaldi Pathur Razi Ansyah Rachmat Subagyo Rachmat Subagyo Ramadhan, M. Nizar Rusdi Rusdi Rusilawati Rusilawati Saputra, M. Reynaldi Perdana Sarifudin Sarifudin Sarifudin sarifudin, Sarifudin Silalahi, Dani Surya Hamonangan Sri Hartini Sunu Hasta Wibowo Suryo, Arief Trisno Eko Wibowo, Bayu Setyo Zainal Aqli