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All Journal Jurnal Informatika Universitas Pamulang bit-Tech International Journal of Engineering, Science and Information Technology Kontigensi: Jurnal Ilmiah Manajemen Jurnal Pajak dan Bisnis (Journal of Tax and Business) Elektriese: Jurnal Sains dan Teknologi Elektro Engineering and Technology International Journal (EATIJ) Journal of Social Science and Business Studies Journal of Information System, Technology and Engineering JRIIN :Jurnal Riset Informatika dan Inovasi Jitu: Jurnal Informatika Utama Dinamika: Jurnal Pengabdian Masyarakat Spectrum: Multidisciplinary Journal Marketica: Jurnal Ilmiah Pemasaran Dirya : Journal of Economic Management Jurnal Penelitian Teknik IJSS: International Journal of Social
Zein, Afrizal
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Implementation Of Mobile Web Applications Using Balanced Scorecard KPI Formulation Suharto, Agus; Zein, Afrizal
Journal of Information System, Technology and Engineering Vol. 2 No. 4 (2024): JISTE
Publisher : Yayasan Gema Bina Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61487/jiste.v2i4.111

Abstract

Implementation of mobile web applications has become a key factor in improving organizational performance in the digital era. This research examines the application of the Balanced Scorecard (BSC) model in the formulation of Key Performance Indicators (KPI) for mobile web applications to increase operational effectiveness and efficiency. The Balanced Scorecard, developed by Kaplan and Norton, is a managerial tool that integrates multiple performance perspectives financial, customer, internal processes, and learning and growth in one comprehensive framework. This study focuses on how KPIs designed based on the BSC model can be used to assess and monitor the performance of mobile web applications. The implementation process begins with identifying the organization's strategic objectives and establishing relevant KPIs for each BSC perspective. Next, this research evaluates how these KPIs are applied in the context of mobile web applications and their impact on application performance and user satisfaction. The results of this research show that the use of BSC-based KPIs can increase visibility of mobile web application performance, assist in identifying areas of improvement, and support better strategic decision making. This research also identifies challenges that may be faced in implementing the BSC model in the context of mobile technology and provides recommendations to overcome these challenges.
Drafting of IT Outsourcing Risk Management Policy Proposal with IT Outsourcing Risk Management Framework and Cobit Zein, Afrizal
Journal of Information System, Technology and Engineering Vol. 3 No. 1 (2025): JISTE
Publisher : Yayasan Gema Bina Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61487/jiste.v3i1.130

Abstract

The design of a proposed Information Technology (IT) outsourcing risk management policy is essential in facing the complexity and uncertainty associated with using third-party services. This policy aims to protect organisational assets, ensure operational continuity, and minimise the impact of risks that may arise from outsourcing relationships. In this study, we develop a risk management framework that integrates IT outsourcing risk management principles with the COBIT (Control Objectives for Information and Related Technologies) standard. This framework includes risk identification, analysis, mitigation, and continuous monitoring and evaluation. Through this approach, organisations can improve control and visibility of risks faced in IT outsourcing. The results of this study indicate that implementing a comprehensive risk management policy not only strengthens information security but also improves the effectiveness and efficiency of business processes involving IT outsourcing. Hopefully, this proposed policy can provide practical guidance for organisations in managing risks and maximising the value of IT outsourcing.
A Comprehensive Framework for Integrating Machine Learning with Big Data Analytics Systems for Business Purposes Zein, Afrizal; Ekawati, Fordiana
Journal of Social Science and Business Studies Vol. 3 No. 4 (2025): JSSBS
Publisher : Yayasan Gema Bina Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61487/jssbs.v3i4.246

Abstract

The growth in volume, velocity, and diversity of data has driven the need for analytical systems that are not only capable of handling big data, but also capable of generating intelligent predictions and insights through the integration of machine learning. This study aims to design and analyze a comprehensive framework that integrates machine learning algorithms into big data analytical systems. The research approach is carried out through literature studies and evaluations of various platforms and architectures such as Hadoop, Spark, and TensorFlow, which enable efficient large-scale data processing. The proposed framework includes the stages of ingestion, preprocessing, model training, evaluation, deployment, and feedback loops that support continuous learning. This integration not only improves the predictive capabilities of the system but also enables organizations to respond proactively to real-time data dynamics. The results of this study are expected to be a strategic reference in the development of modern data-driven analytical systems.  
Sentiment Analysis of Product Reviews in E-Commerce Using the Naive Bayes Method Zein, Afrizal; Karimah , Mufidah
Journal of Social Science and Business Studies Vol. 3 No. 4 (2025): JSSBS
Publisher : Yayasan Gema Bina Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61487/jssbs.v3i4.247

Abstract

In the rapidly growing world of e-commerce, customer reviews play a crucial role in influencing purchasing decisions. However, the massive volume of online reviews makes it difficult for potential buyers and sellers to interpret the overall sentiment toward a product. This research aims to perform sentiment analysis on product reviews in e-commerce platforms using the Naive Bayes classification method. The study focuses on classifying reviews into positive, negative, and neutral categories based on textual data. The dataset used consists of customer reviews collected from popular e-commerce sites. The data preprocessing stages include case folding, tokenization, stop word removal, and stemming to ensure clean and meaningful input for the model. The Naive Bayes algorithm, known for its simplicity and efficiency in text classification, is applied to train and predict sentiment labels. Evaluation is conducted using accuracy, precision, recall, and F1-score metrics to measure model performance. Experimental results show that the Naive Bayes classifier achieves high accuracy in detecting sentiment polarity, making it suitable for large-scale sentiment analysis in e-commerce contexts. The findings demonstrate that sentiment analysis can provide valuable insights for businesses in understanding customer satisfaction, improving products, and enhancing overall marketing strategies.  
Transformasi Wavelet Diskrit Dalam Pembuatan Kunci Layet Fisik Untuk Internet Of Things Zein, Afrizal; Rozali, Christien; Jibril, Sunan; Julianto, Renaldi
Jurnal Penelitian Teknik Vol. 2 No. 2 (2025): Jurnal Penelitian Teknik
Publisher : Jurnal Penelitian Teknik

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

Abstract

Seiring dengan perkembangan Internet of Things (IoT), keamanan komunikasi dan transmisi data menjadi aspek yang semakin penting. Penelitian ini mengusulkan metode pembuatan kunci lapis fisik (physical layer key generation) menggunakan Discrete Wavelet Transform (DWT) yang dirancang khusus untuk lingkungan IoT. Metode ini memanfaatkan sifat multi-resolusi dan lokalisasi dari DWT untuk meningkatkan keamanan dan keandalan kunci yang dihasilkan. Dalam pendekatan ini, data mentah yang diperoleh dari perangkat IoT fisik, seperti sinyal analog atau derau acak (random noise), diproses menggunakan DWT untuk menghasilkan representasi yang lebih terstruktur dan unik. Proses transformasi ke domain wavelet memungkinkan kunci yang dihasilkan memiliki ketahanan tinggi terhadap interferensi, serangan pemalsuan, dan variasi lingkungan, sehingga cocok untuk digunakan pada perangkat IoT dengan sumber daya terbatas. Metode ini juga dirancang agar efisien secara komputasi, sehingga dapat diimplementasikan pada perangkat dengan daya pemrosesan dan memori yang terbatas. Hasil eksperimen menunjukkan bahwa metode ini mampu menghasilkan kunci dengan entropi tinggi, konsistensi yang baik, serta ketahanan terhadap berbagai jenis serangan, termasuk serangan brute-force dan analisis statistik. Selain itu, metode ini dapat diintegrasikan dengan sistem keamanan IoT yang sudah ada tanpa memerlukan perangkat keras tambahan. Dengan demikian, metode pembuatan kunci lapis fisik berbasis DWT ini menawarkan solusi yang efektif dan inovatif untuk meningkatkan keamanan pada aplikasi IoT.
Strategi Peningkatan Jangkauan Pasar Melalui Branding Dan Digital Marketing Menggunakan SEM-PLS Dan Analisis SWOT Zein, Afrizal
Jurnal Pajak dan Bisnis Vol 7 No 1 (2026): Journal of Tax and Business
Publisher : LPPM-STPI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55336/jpb.v7i1.411

Abstract

Penelitian ini bertujuan untuk menganalisis strategi peningkatan jangkauan pasar melalui penguatan branding dan penerapan digital marketing dengan menggunakan pendekatan Structural Equation Modeling–Partial Least Squares (SEM-PLS) dan analisis SWOT. Di era transformasi digital, perusahaan dituntut untuk membangun identitas merek yang kuat serta mengoptimalkan kanal pemasaran digital guna meningkatkan daya saing dan memperluas pangsa pasar. Namun demikian, efektivitas strategi tersebut memerlukan pengujian empiris untuk memahami hubungan antar variabel yang memengaruhi peningkatan jangkauan pasar. Metode penelitian yang digunakan adalah pendekatan kuantitatif dengan teknik survei terhadap pelaku usaha dan konsumen yang aktif menggunakan media digital. Data dianalisis menggunakan SEM-PLS untuk menguji pengaruh branding dan digital marketing terhadap jangkauan pasar, baik secara langsung maupun tidak langsung. Selain itu, analisis SWOT digunakan untuk mengidentifikasi faktor internal (strengths dan weaknesses) serta faktor eksternal (opportunities dan threats) yang memengaruhi implementasi strategi pemasaran digital. Hasil penelitian menunjukkan bahwa branding memiliki pengaruh positif dan signifikan terhadap peningkatan jangkauan pasar, baik secara langsung maupun melalui mediasi efektivitas digital marketing. Digital marketing juga terbukti memberikan kontribusi signifikan terhadap peningkatan visibilitas merek, interaksi pelanggan, dan konversi pasar. Analisis SWOT mengidentifikasi kekuatan utama perusahaan terletak pada keunikan nilai merek dan pemanfaatan media sosial, sementara tantangan utama berasal dari persaingan digital yang semakin ketat dan perubahan perilaku konsumen yang dinamis. Implikasi penelitian ini memberikan rekomendasi strategis berupa penguatan konsistensi identitas merek, optimalisasi Search Engine Marketing (SEM) dan media sosial, serta integrasi analisis data pelanggan untuk mendukung pengambilan keputusan berbasis data. Penelitian ini berkontribusi pada pengembangan model strategis peningkatan jangkauan pasar berbasis pendekatan kuantitatif dan analisis strategis terpadu.
Co-Authors Agus Suharto, Agus Agustiansyah, Salim Ari Putra Arief Kurniawan Dzaky Muttaqiin, Muhammad Ekawati, Fordiana Eriana, Emi Sita Farizy, Salman Gunawan, Heru Handijono, Ardijan Jibril, Sunan Julianto, Renaldi Karimah , Mufidah Karimah, Mufidah Marwati, Fingki Rozali, Christien Shahputra, Faidal Suharyanto, Eko Tristianto, Chrisantus Utami, Ersi Putri