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All Journal Jurnal Teknik Informatika (JUTIF) Prosiding Seminar Nasional Biologi Journal of Advances in Information Systems and Technology Jurnal Abdi Negeri
Yusuf Wisnu Mandaya
Department Of Computer Science, Universitas Negeri Semarang
Agriculture, Biological Sciences & Forestry Computer Science & IT Library & Information Science

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Analysis of Factors Affecting Continued Interest in Using Online Food Delivery Features Using ECM and UTAUT2 Subhan Subhan; Afan Ismi Fauzan; Yusuf Wisnu Mandaya
Journal of Advances in Information Systems and Technology Vol. 6 No. 1 (2024): April
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jaist.v6i1.6568

Abstract

The development of e-commerce in Indonesia itself is currently at the level of being able to provide online food delivery services, making it easier for users to order food. In addition, the Covid-19 pandemic has indirectly changed consumer behavior to avoid or reduce activities outside the home, including ordering food. This study was conducted to identify what factors influence consumers in using online food delivery services with continuance intention after the pandemic and uses a method that integrates variables from the ECM (Expectancy Confirmation Model) and UTAUT2 (Extended Unified Theory of Use and Acceptance of Technology 2). The data in this study were obtained by distributing questionnaires online on 252 online food delivery users. Meanwhile, the data analysis method uses excel for the data screening process and the SmartPLS 3 application to test the inner model and outer model. The results of this study show that the most frequently used online food delivery service application is Go-Food and is dominated by women, with an age group of 17 years to 25 years, the majority of students domiciled mostly in West Java province. Then, there are six accepted hypotheses and five rejected hypotheses. Based on the accepted hypothesis, it is found that the variable price saving orientation, habit has an effect in influencing users in using online food delivery services in continuance intention. This research is expected to provide positive input for the authorities to be able to improve the quality of service provided to users in the future.
Optimization Artificial Neural Network (ANN) Models with Adam Optimizer to Improve Customer Satisfaction Business Banking Prediction Ifriza, Yahya Nur; Mandaya, Yusuf Wisnu; Sanusi, Ratna Nur Mustika; Febriyanto, Hendra; Jabbar, Abdul; Kamaruddin, Azlina
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 3 (2025): JUTIF Volume 6, Number 3, Juni 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.3.4776

Abstract

Customer satisfaction prediction is critical for business banking to retain clients and optimize services, yet existing models struggle with imbalanced data and suboptimal convergence. Traditional approaches lack adaptive learning mechanisms, limiting accuracy in real-world applications. This study developed an optimized Artificial Neural Network (ANN) model using the Adam algorithm to improve prediction accuracy for banking customer satisfaction. We trained an ANN on the Santander Customer Satisfaction Dataset (76,019 entries, 371 features) with Adam optimization. Preprocessing included normalization, removal of quasi-constant features, and an 80-20 train-test split. Adam’s adaptive learning rates and momentum were leveraged to address gradient instability. The model achieved 95.82% accuracy, 99.99% precision, 95.83% recall, a 97.87% F1-score, and 0.82 AUC, outperforming traditional optimizers like SGD. Training loss reduced by 30% with faster convergence. This work demonstrates Adam’s efficacy in handling imbalanced banking data, providing a scalable framework for customer analytics. The results advance computer science applications in fintech by integrating adaptive optimization with deep learning for high-stakes decision-making. This research contributes to the growing body of knowledge in machine learning applications for business analytics and provides a valuable framework for improving customer satisfaction prediction models in various industries and the advancement of deep learning applications in business intelligence, particularly in banking service quality prediction.
PENGUATAN KOMPETENSI PROFESIONAL GURU BIOLOGI DALAM IMPLEMENTASI PEMBELAJARAN DEEP LEARNING BERBASIS TIK MELALUI PELATIHAN TERPROGRAM Sukaesih, Sri; Marianti, Aditya; Saptono, Sigit; Sriyadi, Sriyadi; Lemmuela, Litania Hephzibah; Zahra, Siti Nur Fathimatuz; Ulhaq, Hasnaa’ Dhiya’; Pangastuti, Aulia Tirani; Mandaya, Yusuf Wisnu; Masrikhah, Ririn
Prosiding Seminar Nasional Biologi Vol. 13 (2025)
Publisher : Prosiding Seminar Nasional Biologi

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Guru merupakan pendidik profesional yang perlu meningkatkan kompetensi profesional secara berkelanjutan. Guru profesional diharapkan mampu menciptakan pembelajaran yang mendalam dan bermakna bagi peserta didik. Pembelajaran mendalam (deep learning) menjadi pendekatan pembelajaran inovatif yang digulirkan oleh Kementerian Pendidikan Dasar dan Menengah Republik Indonesia. Hasil analisis permasalahan dan kebutuhan dengan Guru Biologi SMA Kota Semarang menunjukkan belum ada sosialisasi yang terprogram dari pemerintah terkait pembelajaran deep learning, guru belum memahami kerangka kerja dan penerapan deep learning dengan memanfaatkan teknologi informasi dan komunikasi (TIK) dan implementasinya dalam pembelajaran. Tujuan kegiatan ini untuk meningkatkan pemahaman dan keterampilan guru MGMP Biologi SMA dalam merancang pembelajaran deep learning berbasis TIK dan implementasinya di pembelajaran biologi untuk meningkatkan kompetensi profesional guru. Metode kegiatan melalui Pelatihan Terprogram dengan tahapan: analisis kebutuhan di MGMP Biologi SMA, merumuskan solusi, pelaksanaan kegiatan, monitoring, dan evaluasi hasil program. Kegiatan IHT diikuti 50 orang guru Biologi. Hasil program menunjukkan guru biologi memiliki pemahaman yang baik dan sangat baik terkait pembelajaran deep learning, serta 90% guru terampil merancang pembelajaran dengan pendekatan deep learning berbasis TIK. Hasil monitoring menunjukkan guru mampu mengimplementasikan pembelajaran deep learning dalam praktik pembelajaran di kelas. Berdasarkan evaluasi dan tanggapan guru, program yang dilaksanakan sangat bermanfaat, memberi dampak positif bagi kreativitas dan inovasi pembelajaran biologi di kelas yang lebih mendalam, serta mendorong peningkatan kompetensi profesional guru secara berkelanjutan.
Peningkatan Loyalitas Pelanggan Melalui Integrasi Digital Marketing dan Desain Kemasan Produk Berbasis Behavioral Consumer Insights Pada UMKM Ifriza, Yahya Nur; Efrilianda, Devi Ajeng; Mandaya, Yusuf Wisnu; Alamsyah, Alamsyah
Jurnal Abdi Negeri Vol 2 No 2 (2024): September 2024
Publisher : Informa Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63350/jan.v2i2.19

Abstract

Customer loyalty is an important element that determines the long-term success of MSMEs, especially in the midst of increasingly fierce market competition. Previous research shows that digital marketing and attractive packaging design play an important role in increasing customer loyalty and attracting new consumers emphasize that digital-based marketing strategies enable small and medium businesses to reach a wider market at low costs, while research by [3] shows that consumer behavior-based packaging design can increase consumer appeal and trust. Based on these results, this service program aims to integrate digital marketing strategies and packaging design based on behavioral consumer insights in 15 MSMEs in the culinary and crafts sectors. The results of the service showed an increase in MSMEs' understanding of digital marketing from 30% to 85% after the training. In addition, assistance with packaging design resulted in an increase in product attractiveness from 25% to 78%. Customer loyalty also increased significantly, with 68% of customers making repeat purchases after implementing the new strategy. This program supports previous research which confirms that the integration of digital marketing strategies and packaging design based on consumer behavior can increase MSME customer loyalty and competitiveness in the market.
Co-Authors Abdul Jabbar Aditya Marianti Afan Ismi Fauzan Alamsyah - Efrilianda, Devi Ajeng Febriyanto, Hendra Kamaruddin, Azlina Lemmuela, Litania Hephzibah Masrikhah, Ririn Pangastuti, Aulia Tirani Sanusi, Ratna Nur Mustika Sigit Saptono Sri Sukaesih Sriyadi Sriyadi, Sriyadi Subhan Subhan Ulhaq, Hasnaa’ Dhiya’ Yahya Nur Ifriza Zahra, Siti Nur Fathimatuz