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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Bibliotika : Jurnal Kajian Perpustakaan dan Informasi Building of Informatics, Technology and Science Indonesian Journal of Community Services Journal of Information Systems and Informatics International Journal of Advances in Data and Information Systems Journal of Community Service and Empowerment Journal of System and Computer Engineering Journal of Applied Data Sciences Literatify : Trends in Library Development Journal of Economics and Management Scienties
Fahmi, Faisal
Universitas Airlangga
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Library & Information Science Social Sciences Other

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The Importance of Literacy on Artificial Intelligence for the Higher Education Students: A Systematic Literature Review Mahadewi, Mega Putri; Aysya, Alf Arira Ananta; Sofiyani, Zulfatun; Fahmi, Faisal
International Journal of Advances in Data and Information Systems Vol. 6 No. 1 (2025): April 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i1.1350

Abstract

The rapid development of AI technology makes AI literacy crucial in providing individuals with an understanding of the essential functions of AI and its ethical application in higher education. This study used a scoping literature review method by searching the Scopus, Web of Science, Science Direct, and Sage Journals databases. Based on the search results, the eligibility criteria data were analyzed. Authors found as many as 153 pieces of literature, and eleven were declared to meet the eligibility criteria for the literature reviewed in this study. This study shows that AI literacy is essential in higher education. Educators and higher education institutions are responsible for providing programs that support the development of AI literacy skills in students. The application of AI literacy for students in higher education is essential in dealing with the development of AI technology. However, the lack of studies that address the evaluation of the importance of AI literacy and its implications limits the in-depth understanding of this topic.
NLP-Based Sentiment Analysis of Alfagift and Klik Indomaret Application Reviews: A Comparative Study Fuji Lestari, Nur Laili Indah; Naraya, Tri Vani Diah; Anggraini, Handari Niken; Fahmi, Faisal
Journal of Information System and Informatics Vol 7 No 3 (2025): September
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i3.1178

Abstract

Amid competition for online shopping applications, Alfagift and Klik Indomaret compete for the same market share. This study aims to analyze and compare user reviews of both applications using sentiment analysis based on Natural Language Processing (NLP) with the E-Servqual approach, focusing on Efficiency and System Availability indicators, to determine the advantages and disadvantages of each application and provide a basis for service improvement, strategic decision making, and reference for users in choosing online shopping applications that suit their needs. Methods include data collection, data grouping, data processing, selecting analyzed samples with consensus, and data analysis to describe user perceptions of the quality of service of each application. The results showed that on the positive side, both apps experienced an increase in efficiency although not significant, with gradual improvements in user experience. Alfagift showed improvements in technical responsiveness and ease of use, while Klik Indomaret was relatively stable with a simple user experience. On the negative side, efficiency issues still arise consistently and impact user perception. Alfagift often faces access and login issues, while Klik Indomaret tends to be slow when accessing various features. These findings reflect that despite year-on-year improvements, both apps still face technical challenges that need to be resolved to improve the overall quality of digital services.
Analisis Sentimen terhadap Ulasan Pengguna Aplikasi Gojek dengan Menggunakan Pemrosesan Bahasa Alami Yuliani, Silvia Putri; Muharani, Ari Ati Putri; Fatmawati, Riyana Qori; Fahmi, Faisal
Journal of System and Computer Engineering Vol 6 No 4 (2025): JSCE: October 2025
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v6i4.2062

Abstract

Gojek, a leading proponent of on-demand services in Indonesia, has garnered a total of 142 million downloads. However, it has received the fewest reviews compared to other on-demand applications. The objective of this research is to identify sentiment in Gojek application user reviews on Google Playstore using Natural Language Processing (NLP) approaches and machine learning algorithms through the Orange platform. The reviews utilized in this study were collected in June 2025 and encompass a total of 3,615 data points, including 2,892 training data and 723 testing data. Sentiments are classified into two categories based on their ratings: positive (rating 4-5) and negative (rating 1-2). The research process is comprised of four primary stages: data collection and labeling, text pre-processing, feature transformation using TF-IDF, and testing five classification algorithms: neural network, naïve Bayes, random forest, decision tree, and k-nearest neighbors. The evaluation results indicate that the Neural Network model demonstrates optimal performance, exhibiting 93.20% accuracy, 93.00% F1-score, and 75.80% MCC. These findings suggest that the NLP approach can be utilized effectively to comprehend user perceptions of applications. It is anticipated that this research will assist Gojek developers in the monitoring and enhancement of service quality, with this enhancement being informed by user feedback.
Analisis Pengaruh Makro Ekonomi Terhadap Perkembangan Indeks Saham di BSI Pada Tahun 2021-2024 Fahmi, Faisal; Maidalena, Maidalena; Tambunan, Khairina
Journal of Economics and Management Scienties Volume 8 No. 1, December 2025 (Accepted)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jems.v8i1.271

Abstract

Penelitian ini bertujuan untuk menganalisis pengaruh indikator makroekonomi yang terdiri dari inflasi, kurs, dan Produk Domestik Bruto (PDB) terhadap indeks saham PT Bank Syariah Indonesia Tbk (BSI) pada periode Juli 2021–Desember 2024. Penelitian ini menerapkan pendekatan kuantitatif dengan analisis regresi linier berganda. Sumber data yang digunakan berupa data sekunder yang diperoleh dari publikasi resmi Bank Indonesia, Badan Pusat Statistik, serta Bursa Efek Indonesia. Hasil penelitian menunjukkan bahwa secara parsial inflasi berpengaruh negatif signifikan terhadap indeks saham BSI, yang berarti kenaikan inflasi cenderung menurunkan harga saham. Kurs juga berpengaruh negatif signifikan, sehingga pelemahan nilai tukar rupiah berdampak pada penurunan indeks saham BSI. Sementara itu, PDB berpengaruh positif signifikan, menandakan bahwa pertumbuhan ekonomi nasional mendorong peningkatan kinerja saham BSI. Hasil uji simultan (F-test) memperlihatkan bahwa ketiga variabel bebas secara bersama-sama berpengaruh signifikan terhadap indeks saham BSI dengan nilai F-hitung 23,954 lebih besar dari F-tabel 2,76 dan signifikansi 0,000 < 0,05. Nilai Adjusted R² sebesar 0,671 menunjukkan bahwa 67,1% variasi pergerakan saham BSI dapat dijelaskan oleh variabel inflasi, kurs, dan PDB, sementara 32,9% sisanya dipengaruhi oleh faktor lain di luar model penelitian ini.
AI-driven creativity in software development using services information Fahmi, Faisal; Wang, Feng-Jian; Subramaniam, Hema
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i6.pp4474-4483

Abstract

In competitive markets, organizations that do not innovate risk becoming outdated. At it is core, innovation depends on creativity, with creative outcomes typically characterized by novelty, usefulness, and surprisingness. In software development, creative solutions are often generated through brainstorming sessions. However, brainstorming is constrained by the knowledge of the participant and facilitator. In this paper, we present an artificial intelligence (AI)-based method to generate creative solutions in software by leveraging service information. The presented method includes two phases, where the first phase involves constructing creativity resources through text clustering (TF-IDF, K-medoid) and capability extraction (dependency parsing), and the second phase employs semantic similarity along with structured creativity techniques (exploration, transformation, and combination) to generate creative solutions in software. Besides, experimental results showed that the AI-based method achieved comparable creativity scores to traditional brainstorming with more limited time, demonstrating fast and strong performance in generating novel and useful solutions, although participants perceived some results as less surprising due to overlap with brainstorming outcomes.
Co-Authors Ab Hamid, Siti Hafizah Abdul Rashid, Razailin Adira Novanda Widyasari Anggraini, Handari Niken Anindi Alfi Syahrina Anisia Zulia Rahma Dewi Atmaja, Sigit Tri Aysya, Alf Arira Ananta Bunga Anggraini Mahameru Erwandi Erwandi Fatmawati, Riyana Qori Fitri Mutia, Fitri Fuji Lestari, Nur Laili Indah Halim, Yunus Abdul Hanindia Aisyah Rosanti Harun, Rodyah Mulyani Hasyim, Fayyaz Mubarak Hema Subramaniam Irdiana Rahma Kurniawati Jannah, Qonita Miftahul Kurniawan, Yanuar Dwi Lisa Mauludia Sari Mahadewi, Mega Putri Maidalena Maidalena, Maidalena Muhammad, Rizqi Nur Muharani, Ari Ati Putri Naraya, Tri Vani Diah Nila Arofa’ina Nizar, Niken Nuzulia Pratiwi, Ajeng Mustika Pratiwi, Bertha Niken Ayu Puti Hanalya Rengganis Putri Nur Amalia Ragil Tri Atmi, Ragil Tri Rahuna, Daif Rizqon Fajar Sugeng Riyadi Syamsi, Nur Khalisha Tambunan, Khairina Wang, Feng-Jian Yuliani, Silvia Putri Yuwinanto, Helmy Prasetyo Zainab Zainab Zakkiya Farah Nadiya Santoso Zulfatun Sofiyani