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All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA) 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) 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 IJSS: International Journal of Social
Zein, Afrizal
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The Role of Internet of Things (IoT) in Enhancing Asset Management and Operational Efficiency Zein, Afrizal; Karimah, Mufidah
JAKI : Jurnal Akuntansi Vol 2 No 1 (2025): Dirya : Journal of Economic Management
Publisher : Pascasarjana STIE Miftahul Huda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70283/dirya.v2i1.72

Abstract

The advancement of Internet of Things (IoT) technology has brought significant changes in enhancing asset management and operational efficiency across various organizations. This study aims to explore how IoT implementation can improve asset management through real-time monitoring, automation, and better data integration. The research employs a qualitative approach using a case study of an institution that has adopted IoT technology. Data were collected through in-depth interviews with stakeholders, direct observations, and a comprehensive literature review from reliable online sources such as Google Scholar. The data were analyzed descriptively to identify the impact of IoT on asset management processes and operational efficiency. The findings reveal that IoT enables organizations to reduce manual errors, optimize asset utilization, and significantly lower operational costs. Moreover, IoT accelerates responses to operational issues and enhances transparency in asset management. The study also highlights challenges in implementation, including the need for system integration and data security concerns. These findings contribute valuable insights into the role of IoT in the digital transformation of asset management and operations and serve as a reference for practitioners and academics in developing effective IoT deployment strategies.
Optimizing Artificial Intelligence-Based Waste Bank Management Eriana, Emi Sita; Zein, Afrizal
bit-Tech Vol. 8 No. 1 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i1.2526

Abstract

This study examines the implementation of artificial intelligence (AI) technology to optimize waste bank management in West Pamulang, Indonesia. With the national waste volume reaching 68.5 million tons in 2023 and an annual growth rate of 2-4%, sustainable waste management presents critical challenges. West Pamulang accounts for 60% of regional waste, while Indonesia's 8,000 waste banks only reach 1.7% of the contribution to national waste reduction. Using a mixed method approach, the study was conducted in five waste banks in West Pamulang, South Tangerang during January-April 2025, involving 45 participants selected through purposive sampling. Data collection included participatory observations, interviews, questionnaires, and documentation studies. Reliability was assessed using Cronbach's Alpha 0.89, with validity guaranteed through triangulation. Ethical safeguards include informed consent, data anonymization, and institutional ethical approval. The results show significant operational improvements through AI technologies: computer vision-based classification systems, real-time transaction recording, educational chatbots, and volume prediction systems. Quantitative analysis revealed an increase in transaction efficiency by 75%, a 60% decrease in classification errors, and a decrease in data management time from day to minute. The AI predictive model achieves 92% accuracy in volume estimation and 15% fuel savings through route optimization. The classification system shows an accuracy of 89-97%, reducing the sorting time by 70%. Implementation challenges include limited digital literacy, infrastructure gaps, and inadequate policy support. The study recommends training programs, cost-effective platforms, and multi-stakeholder collaboration for a sustainable AI-enhanced waste management system.
Sistem Monitoring Serangan Dos Dengan Metode Intrusion Detection System (Ids) Snort Menggunakan Aplikasi Berbasis Python Pada Sistem Operasi Linux Gunawan, Heru; Handijono, Ardijan; Putra, Ari; Zein, Afrizal
Spectrum: Multidisciplinary Journal Vol. 2 No. 3 (2025): Spectrum: Multidisciplinary Journal
Publisher : Sapta Arga Nusantara

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Abstract

Perkembangan teknologi informasi telah meningkatkan ketergantungan terhadap sistem jaringan komputer, namun juga memunculkan ancaman keamanan, salah satunya serangan Denial of Service (DoS). Serangan ini membanjiri jaringan dengan lalu lintas berlebih hingga layanan tidak tersedia. Penelitian ini bertujuan membangun sistem pemantauan serangan DoS menggunakan Snort Intrusion Detection System (IDS) pada Ubuntu Server 20.04 LTS dan aplikasi berbasis Python. Snort digunakan untuk menganalisis paket jaringan, sedangkan Python memproses log dan menampilkannya dalam dashboard interaktif menggunakan Flask. Metode yang digunakan adalah Waterfall dengan tahapan analisis kebutuhan, perancangan, implementasi, pengujian, dan pemeliharaan. Hasil pengujian menunjukkan sistem mampu mendeteksi serangan DoS secara efektif, menampilkan informasi seperti IP sumber, jenis serangan, prioritas, dan tren waktu. Penggunaan CPU meningkat saat lonjakan log namun tetap dalam batas wajar. Sistem bekerja stabil tanpa kegagalan dalam pengolahan data. Sistem ini memberikan kontribusi nyata dalam pemantauan lalu lintas jaringan secara real-time dan menjadi dasar pengembangan sistem keamanan yang lebih luas
Perancangan Sistem Informasi Penilaian Rapot berbasis Web menggunakan Metode Waterfall pada SMPIT Cordova Dzaky Muttaqiin, Muhammad; Zein, Afrizal
Jurnal Riset Informatika dan Inovasi Vol 3 No 7 (2025): JRIIN : Jurnal Riset Informatika dan Inovasi (INPRESS)
Publisher : shofanah Media Berkah

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Abstract

SMPIT CORDOVA dalam pengelolaan nilai akhir raport membutuhkan waktu yang lama dalam proses pengelolaan nilai sehingga terjadi keterlambatan dalam pelaporan karena banyaknya kriteria penilaian ditentukan. Tujuan dari penelitian ini adalah Meningkatkan efisiensi dalam proses pengolahan dan distribusi data penilaian, sehingga guru lebih cepat dan akurat dalam memberikan penilaian. Metode penelitian yang digunakan adalah waterfall model mulai dari tahap analisis, perancangan, implementasi, dan pengujian. Penelitian ini mengahsilkan website yang membantu guru dalam mempercepat proses pengolahan nilai raport. Website menghasilkan nilai yang dapat diunduh menjadi file PDF. Dari kasus tersebut mendorong penulis untuk melakukan penelitian dengan membuat sistem informasi pengelolaan data nilai siswa. Pengujian menghasilkan output yang sesuai dengan input dari guru dan membuktikan perbedaan waktu, dan keakuratan dalam pengelolaan nilai raport siswa.
Personalized Explainable AI: Dynamic Adjustment of Explanations for Novice and Expert Users Zein, Afrizal
Jurnal Penelitian Pendidikan IPA Vol 11 No 9 (2025): September: In Progress
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i9.12586

Abstract

Explainable Artificial Intelligence (XAI) has emerged as a crucial aspect of building trust and transparency in AI-driven systems. However, existing explanation methods often apply a uniform approach, overlooking the diverse backgrounds and expertise levels of users. This paper proposes a personalized explainable AI framework that dynamically adjusts the complexity, depth, and presentation of machine-generated explanations according to the user's expertise—be it novice or expert. By integrating user modeling and adaptive explanation strategies, the system can deliver tailored information that enhances user understanding, satisfaction, and decision-making. We evaluate the proposed approach through experiments involving participants with varying expertise levels interacting with AI-based decision systems. The results show that adaptive explanations significantly improve comprehension for both novice and expert users compared to static, one-size-fits-all explanations. These findings highlight the importance of user-centered design in XAI and suggest practical pathways for future implementation in real-world applications.
Artificial Intelligence In Strategic Decision Making Zein, Afrizal
International Journal of Social Sciences Vol. 1 No. 1 (2025): IJSS: International Journal of Social Sciences
Publisher : STEBIS Bina Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51805/ijss.v1i1.311

Abstract

Artificial Intelligence (AI) has become an increasingly important tool in strategic decision-making across a range of industry sectors. In an increasingly complex and uncertain world, AI offers the ability to analyze large amounts of data, identify patterns, and provide recommendations that can improve the quality of decisions made by managers and organizational leaders. The use of AI in strategic decision-making not only increases efficiency, but also enables more accurate planning and responsiveness to market changes. This article discusses various applications of artificial intelligence in supporting strategic decision-making, including in the areas of market forecasting, resource optimization, and long-term planning. In addition, this article also reviews the challenges and limitations in implementing AI, such as data quality, model reliability, and potential ethical risks. While AI can speed up and improve the decision-making process, it is important to still involve human perspectives in the final decision-making process to ensure that the policies taken still consider social, ethical, and environmental factors. By understanding the role and potential of AI in strategic decision-making, organizations can adopt this technology more effectively, increase competitiveness, and optimize future business outcomes.
Technician Absence Information System Design Pt Rps Tangerang Web-Based Using Waterfall Method Shahputra, Faidal; Zein, Afrizal
International Journal of Social Sciences Vol. 1 No. 2 (2025): IJSS: International Journal of Social Sciences
Publisher : STEBIS Bina Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51805/ijss.v1i2.405

Abstract

Because of the many jobs in the company using information technology to help office work. Employee attendance related to employee performance and discipline in the company is an important thing for the company. PT RPS is a company of various business units, including labor services. The problems that exist in the company are long absences that become long queues, leave applications that must use paper and meet HRD directly and there is no leave recording and employee absence processes that do not have an accurate system. The purpose of this absence and leave application can overcome the problem of absence and work report / report. The web-based attendance system requires PHP language and the WATERFALL method with stages such as needs analysis, system design, implementation, testing and maintenance to create a system as expected. The results of this study are that the attendance system with this website can help employees in attendance and can help the attendance recapitulation process. And the test results in the application show that this website-based attendance and work report application all functions run well without any problems or errors in the application so that it can be implemented in the organization.
Co-Authors Agustiansyah, Salim Ari Putra Arief Kurniawan Dzaky Muttaqiin, Muhammad Ekawati, Fordiana Eriana, Emi Sita Farizy, Salman Gunawan, Heru Handijono, Ardijan Karimah, Mufidah Rozali, Christien Shahputra, Faidal Tristianto, Chrisantus Utami, Ersi Putri