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All Journal Zonasi: Jurnal Sistem Informasi JURNAL MANAJEMEN DAN BISNIS EQUILIBRIUM Indonesian Journal of Innovation Studies Jurnal Ekonomi Kreatif dan Manajemen Bisnis Digital (JEKOMBITAL) JAIDE Proceeding of International Conference on Social Science and Humanity International Journal of Artificial Intelligence for Digital Marketing
Almanfaluti, Istian Kriya
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Public Health Social Sciences Other

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THE INFLUENCE OF TIKTOK CONTENT ON DIGITAL MARKETING OF ELECTRONIC PRODUCTS ON E-COMMERCE: A SYSTEMATIC LITERATURE REVIEW Yulianto, Mochamad Rizal; Mubarok, Akhmad Nur; Suyogo, Muhammad; Pebrianggara, Alshaf; Almanfaluti, Istian Kriya
Journal of Artificial Intelligence and Digital Economy Vol. 1 No. 9 (2024): Journal of Artificial Intelligence and Digital Economy
Publisher : PT ANTIS INTERNATIONAL PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61796/jaide.v1i9.588

Abstract

This study aims to analyze the influence of TikTok content on digital marketing of electronic products in e-commerce through a systematic literature review. TikTok, as an increasingly popular social media platform, offers various engaging content features for users. This study examines how elements of content on TikTok, such as creative short videos, viral challenges, and influencer collaborations, can affect digital marketing strategies and sales performance of electronic products on e-commerce platforms. The methodology used is systematic literature review (SLR) by gathering and analyzing various relevant previous studies on the topic. The findings of this review indicate that TikTok content has a significant impact on brand awareness, consumer engagement, and sales conversion. Effective marketing strategies implemented on TikTok can increase product exposure, attract consumer attention, and drive purchasing decisions. These findings provide valuable insights for digital marketing practitioners in leveraging social media platforms to enhance the marketing performance of electronic products in e-commerce.
ANALYSIS OF THE EFFECT OF EUCS VARIABLES ON USER SATISFACTION IN THE APPLICATION OF CEISA 4.0 AS AN ADMINISTRATIVE SYSTEM Marwah, Siti; Prasojo, Bayu Hari; Pebrianggara, Alshaf; Almanfaluti, Istian Kriya
Jurnal Ekonomi Kreatif dan Manajemen Bisnis Digital Vol 3 No 4 (2025): MEI
Publisher : Transpublika Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55047/jekombital.v3i4.948

Abstract

This study analyzes the impact of EUCS (End-User Computing Satisfaction) variables on user satisfaction with the CEISA 4.0 administrative system at KPPBC TMP Juanda. This study aims to evaluate how various factors, including technical support, reporting features, and system usability, contribute to overall user satisfaction. Data were collected through a survey, and analysis used Structural Equation Modeling (SEM) to assess the relationship between the identified variables. Key findings indicated that users experienced satisfactory technical support, characterized by quick responses and effective solutions to problems. In addition, the system's excellent reporting features facilitate the generation of comprehensive and easy-to-understand reports, further increasing user satisfaction. The research also included validity and reliability tests, confirming that the constructs used in this study are valid and reliable for measuring user satisfaction. The results show that improving these factors can significantly increase user satisfaction with CEISA 4.0, ultimately leading to more efficient administrative processes. This research adds to a more profound comprehension of the elements that influence user satisfaction in administrative systems, as well as providing valuable insights for future development of similar technologies.
SENTIMENT ANALYSIS OF CUSTOMER SATISFACTION TOWARDS STEAK HUT MANYAR KERTOARJO RESTAURANT SERVICES USING THE TF-IDF METHOD Abimanyu, Rama Chikal; Almanfaluti, Istian Kriya
Jurnal MBE Manajemen Bisnis, Equilibrium Vol 11 No 2 (2025): Jurnal Manajemen dan Bisnis Equilibrium
Publisher : Program Studi Manajemen, Fakultas Ekonomi dan Bisnis, Universitas Ngurah Rai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47329/jurnal_mbe.v11i2.1463

Abstract

On online shopping sites or often referred to as marketplaces, there is a column of comments and reviews of transactions that have been made by buyers for products that have been purchased. With this product assessment feature, buyers can consider decisions about the products they will buy. But at this time there is a problem with the review feature because many buyers give negative comments but give a five-star rating. This results in the feature of giving values from consumers being bad. For this reason, a sentiment analysis study was conducted on the review feature at the Steakhut Manyar restaurant using the naive Bayes method and the Tf-Idf algorithm. Based on the review of reviews at the Steakhut restaurant, 1000 review data have been collected which are divided into two, namely 700 training data and 300 test data. After that, the text preprocessing data stage is carried out, where the text preprocessing stage is collecting product and service review data on the web page (Cleaning data), changing uppercase letters to lowercase letters (Casefolding), separating sentences into single sentences (tokenizing), removing conjunctions that are not used for sentiment analysis (stopwords), changing words to basic words (stemming) and continuing to give weight to each word using the Tf-idf algorithm
KEPUTUSAN PEMBELIAN PRODUK NIKE OLEH GENERASI Z DITINJAU DARI PENGARUH INFLUENCER DAN CONTENT MARKETING Putra Agung, Marcello Dicaprio; Almanfaluti, Istian Kriya; Yulianto, Mochamad Rizal
Jurnal MBE Manajemen Bisnis, Equilibrium Vol 11 No 2 (2025): Jurnal Manajemen dan Bisnis Equilibrium
Publisher : Program Studi Manajemen, Fakultas Ekonomi dan Bisnis, Universitas Ngurah Rai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47329/jurnal_mbe.v11i2.1576

Abstract

Riset ini bertujuan untuk menilai bagaimana Generasi Z Sidoarjo melakukan pembelian produk Nike sebagai respon terhadap influencer dan content marketing. Pengambilan sampel menggunakan teknik nonprobability sampling, salah satu tekniknya adalah purposive sampling, digunakan dalam metodologi kuantitatif penelitian ini. Sampel penelitian ini terdiri dari 96 responden Generasi Z. Data dikumpulkan melalui survei daring. Untuk keperluan analisis data, digunakan metode regresi linier berganda yang diproses menggunakan SPSS. Temuan penelitian ini mengungkap bahwa baik strategi pemasaran konten maupun peran influencer memberikan dampak positif dan signifikan terhadap keputusan pembelian yang diambil oleh konsumen. Hal ini menyiratkan bahwa Generasi Z lebih mungkin membeli produk Nike jika influencer tersebut memiliki lebih banyak pengikut dan jika pendekatan content marketing dijalankan dengan baik. Konsekuensi dari temuan penelitian ini menyoroti betapa pentingnya bagi bisnis untuk meningkatkan kemitraan dengan influencer terkait dan meningkatkan kualitas content marketing mereka guna menumbuhkan loyalitas pelanggan dan menarik minat konsumen Generasi Z untuk melakukan pembelian.
ARTIFICIAL INTELLIGENCE (AI) OPTIMALIZATION IN CUSTOMER BEHAVIOR ANALYSIS TO DETERMINE MARKETING STRATEGIES: SYSTEMATIC LITERATURE REVIEW Prameswari, Amanda Tiara; Pebrianggara, Alshaf; Yulianto, Mochamad Rizal; Almanfaluti, Istian Kriya
Proceeding of International Conference on Social Science and Humanity Vol. 2 No. 1 (2025): Proceeding of International Conference on Social Science and Humanity
Publisher : PT ANTIS INTERNATIONAL PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61796/icossh.v2i1.235

Abstract

Objective: This research aims to examine the optimization of the use of AI in understanding and analyzing customer behavior in developing effective and efficient marketing strategies. Method: The method used in this research is the SLR (Systematic Literature Review) method, by collecting data through various sources of academic database articles such as Google Scholar, IEEE Xplore, Science Direct and others that discuss the application of AI. Results: The results of this literature review show that the application of AI such as machine learning and data analysis is able to identify customer preferences and needs, which will be used by companies in designing more personalized and efficient marketing strategies. Novelty: In the digital era, the use of artificial intelligence (AI) in customer behavior analysis has become one of the effective tools to determine a more appropriate marketing strategy. Optimizing AI through the SLR method is an important step for companies in achieving a competitive advantage in understanding customer behavior patterns more accurately in a dynamic market.
ANALISIS SENTIMEN ULASAN APLIKASI PLN MOBILE MENGGUNAKAN ALGORITMA NAÏVE BAYES CLASFIFIER Panduni, Bima; Pebrianggara , Alshaf; Yulianto, Mochammad Rizal; Almanfaluti, Istian Kriya
ZONAsi: Jurnal Sistem Informasi Vol. 7 No. 3 (2025): Publikasi artikel ZONAsi: Jurnal Sistem Informasi Periode September 2025
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/aeyjxp28

Abstract

Seiring dengan meningkatnya penggunaan aplikasi digital, ulasan pengguna menjadi sumber informasi penting untuk memahami kepuasan dan kebutuhan pelanggan. Aplikasi PLN Mobile sebagai salah satu aplikasi layanan publik yang banyak digunakan. Penelitian ini bertujuan untuk menganalisis sentimen ulasan pengguna aplikasi PLN Mobile menggunakan algoritma Naive Bayes Classifier. Data diperoleh dari aplikasi Google Playstore dan mendapatkan 400 data, pembagian data menggunakan rasio 50:50. Pengumpulan dan pengolahan data menggunakan tools Google Colab dengan menggunakan bahasa pemrograman Python. Dari 200 data yang digunakan, model Naive Bayes Classifier menunjukkan kinerja yang cukup baik. Untuk sentimen positif, nilai presisi yang dicapai 88%, recall 76%, dan f1-score 82%, dengan dukungan 143 ulasan. Hasil akurasi yang diperoleh adalah 76%. Hasil ini menunjukkan bahwa algoritma Naive Bayes Classifier dapat digunakan secara efektif untuk mengklasifikasikan sentimen ulasan pengguna aplikasi PLN Mobile, memberikan wawasan berharga bagi pengembang aplikasi untuk meningkatkan layanan.
Application Design: Integration of Qris E-Wallet Cryptocurrency Using Prototype Method: Perancangan Aplikasi : Integrasi Qris E-Wallet Cryptocurrency Dengan Metode Prototype Almanfaluti, Istian Kriya; Putri , Niken Amelia; Navaro , Muhammad Saddam
Indonesian Journal of Innovation Studies Vol. 25 No. 1 (2024): January
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v26i1.997

Abstract

This research endeavors to contribute to the rapidly evolving landscape of technology-driven payment systems, with a focus on Indonesia. The primary objective is to design and develop a mobile application for a cryptocurrency digital wallet integrated with Quick Response Code Indonesian Standard (QRIS). The methodology involves utilizing Webservice for seamless implementation and Android Studio Framework for efficient mobile application development. The results showcase the successful creation of a mobile application that enables cryptocurrency owners to convert virtual assets into Indonesian Rupiah for various transactions, including purchasing mobile credits, electricity tokens, travel tickets, and other payments. The evaluation underscores the feasibility and practicality of the proposed solution, emphasizing the potential for increased ease, speed, and efficiency in transaction processing. This research opens avenues for further exploration and implementation of cryptocurrency-based payment systems, addressing the evolving needs of the digital economy in Indonesia and potentially serving as a model for global applications.Highlights : Seamless Implementation: The research successfully employs Webservice for the integration of a cryptocurrency digital wallet with QRIS, ensuring a smooth and efficient transaction process. Android Studio Framework: The use of the Android Studio Framework demonstrates the applicability and versatility of established tools in developing a robust and user-friendly mobile application for cryptocurrency transactions. Efficiency in Digital Transactions: The designed mobile application enables cryptocurrency owners to convert virtual assets to Indonesian Rupiah, enhancing transaction speed, ease, and overall efficiency in various financial interactionKeywords: Cryptocurrency, E-Wallet, QRIS Integration, Mobile Application, Digital Transactions. Keywords : Cryptocurrency, E-Wallet, QRIS Integration, Mobile Application, Digital Transactions.
ARTIFICIAL INTELLIGENCE (AI), DIGITAL MARKETING AND POPULARITY ON PURCHASE INTENTIONS FOR VIRTUAL CONCERTS IN KOREAN GIRLBAND AESPA Al Ubaidah, Fandy; Almanfaluti, Istian Kriya; Yulianto, Mochamad Rizal; Pebrianggara, Alshaf
International Journal of Artificial Intelligence for Digital Marketing Vol. 2 No. 10 (2025): International Journal of Artificial Intelligence for Digital Marketing
Publisher : PT ANTIS INTERNATIONAL PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61796/ijaifd.v2i10.339

Abstract

Objective:  The impact of the Behavioral Control Model, Personal Innovation, and Technology Acceptance on Shopee Online Purchase Interest is examined in this study. Method: Data was gathered from 96 respondents via questionnaires sent to Shopee platform users utilizing a quantitative study design and SmartPLS software. Results: These results show a favorable association between the factors of the Technology Acceptance Model, Personal Innovation, and Behavioral Control, and how these affect Online Purchase Interest. The study's findings emphasize the significance of the Shopee platform's use of the technology acceptance model, consumer creativity, and the application of efficient behavioral management to boost platform users' enthusiasm in making purchases. Novelty: The implications of this research contribute to consumer understanding in the context of online product or service shopping, assisting researchers in developing strategies that can increase customer engagement and satisfaction.
ANALYSIS OF THE LSTM MODEL ON THE DEMAND PATTERNS OF INDONESIAN TRADITIONAL COOKIES IN ONLINE MARKETPLACES Azsyams, Luke Farrer; Pebrianggara, Alshaf; Almanfaluti, Istian Kriya
International Journal of Artificial Intelligence for Digital Marketing Vol. 2 No. 10 (2025): International Journal of Artificial Intelligence for Digital Marketing
Publisher : PT ANTIS INTERNATIONAL PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61796/ijaifd.v2i10.419

Abstract

Objective:  This study aims to analyze the application of the Long Short-Term Memory (LSTM) model in predicting demand patterns for Indonesian culinary products in online marketplaces. Method: Using monthly sales data from January 2022 to May 2024, the model was trained and evaluated with the metrics Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R². Results: The results showed an MSE of 899.70, an RMSE of 30.00, and an R² value of 0.09, indicating that the model has limitations in capturing variations in historical data. Nevertheless, LSTM still has potential as a forecasting tool for MSME entrepreneurs in decision-making related to inventory management, production planning, and marketing strategies. Novelty: Future research is recommended to expand the dataset, incorporate external factors such as seasonal trends and promotions, and explore hybrid approaches to improve prediction accuracy.
THE IMPACT OF ARTIFICIAL INTELLIGENCE (CHATGPT) ON PRODUCT AND SERVICE INNOVATION IN MICRO, SMALL, AND MEDIUM ENTERPRISES (MSMES) AMONG GENERATION Z ENTREPRENEURS Abimanyu, Mochammad Rakha; Almanfaluti, Istian Kriya; Prasojo, Bayu Hari
International Journal of Artificial Intelligence for Digital Marketing Vol. 2 No. 10 (2025): International Journal of Artificial Intelligence for Digital Marketing
Publisher : PT ANTIS INTERNATIONAL PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61796/ijaifd.v2i10.420

Abstract

Objective: This study aims to analyze the effect of ChatGPT utilization on product and service innovation in Micro, Small, and Medium Enterprises (MSMEs) managed by Generation Z in East Java. The purpose is to determine whether the application of artificial intelligence can significantly enhance the creativity, efficiency, and market relevance of MSME products and services. Method: The research employed a quantitative approach using a simple linear regression with the PLS-SEM method. A total of 99 respondents were selected through purposive sampling, focusing on Gen Z MSME owners who have used ChatGPT in their business activities. The data were analyzed using SmartPLS, which included measurement model testing (validity and reliability) and structural model testing (path coefficient, R², f², and significance). Results:  The findings indicate that ChatGPT usage has a positive and significant influence on product and service innovation, with a path coefficient value of 0.507, R² of 0.257, and f² of 0.346. These results demonstrate that although the explanatory power of the independent variable is statistically limited, the substantive effect is considered strong. This suggests that ChatGPT can support innovation processes by improving efficiency and enabling new ideas that align with market needs. Novelty: This research highlights the empirical evidence of how generative AI tools like ChatGPT can be directly linked to innovation outcomes among young entrepreneurs in Indonesia. The study contributes by emphasizing the role of AI adoption as a strategic driver of competitiveness for MSMEs in the digital era.
Co-Authors Abimanyu, Mochammad Rakha Abimanyu, Rama Chikal Al Ubaidah, Fandy Alshaf Pebrianggara Azsyams, Luke Farrer Bayu Hari Prasojo Marwah, Siti Mochamad Rizal Yulianto Mubarok, Akhmad Nur Navaro , Muhammad Saddam Panduni, Bima Pebrianggara , Alshaf Prameswari, Amanda Tiara Putra Agung, Marcello Dicaprio Putri , Niken Amelia Rachmadany, Andry Suyogo, Muhammad Yulianto, Mochammad Rizal