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All Journal Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Jurnal Pseudocode Jurnal Edik Informatika : Penelitian Bidang Komputer Sains dan Pendidikan Informatika KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JIKO (Jurnal Informatika dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Computer Based Information System Journal JURNAL TEKNOLOGI DAN OPEN SOURCE JOISIE (Journal Of Information Systems And Informatics Engineering) Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Jurnal Ekonomi Manajemen Sistem Informasi Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Sistem Informasi dan Informatika (SIMIKA) Prosiding National Conference for Community Service Project JISA (Jurnal Informatika dan Sains) JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Jurnal Teknologi Informasi dan Komunikasi Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Telcomatics Journal of Information System and Technology (JOINT) Journal of Computer and Information System (J-CIS) Jurnal Media Computer Science JOINCS (Journal of Informatics, Network, and Computer Science) Indonesian Research Journal on Education Conference on Management, Business, Innovation, Education and Social Sciences (CoMBInES) Conference on Business, Social Sciences and Technology (CoNeScINTech) Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer INOVTEK Polbeng - Seri Informatika
Syaeful Anas Aklani, Syaeful
Universitas Internasioanl Batam
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Pengembangan model pengenalan huruf SIBI pada kondisi low-light berbasis convolutional neural network Francisco, Francisco; Aklani, Syaeful Anas
Jurnal Pseudocode Vol 13 No 1 (2026): Volume 13 Nomor 1 Februari 2026
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.13.1.14-20

Abstract

Deaf and speech-impaired individuals in Indonesia face communication barriers due to limited public understanding of sign language. In real use, SIBI communication often occurs in dim lighting, yet recognition models are mainly evaluated under normal illumination, motivating robust low-light recognition. This study develops a CNN model based on MobileNetV2 to recognize SIBI (Indonesian Sign Language System) letter gestures under low-light conditions (50-100 lux). The dataset comprises 5,579 images of 26 SIBI letters, divided stratified 80:10:10. The methodology includes preprocessing with Bilateral Filter, CLAHE in LAB color space, and Adaptive Gamma Correction, plus transfer learning and fine-tuning with data augmentation. Evaluation results show 97.13% test accuracy, with most errors among similar letters. Real- time testing is stable within 50-100 lux, though accuracy decreases below 50 lux or with shadows. These findings indicate that the proposed preprocessing methods and MobileNetV2 CNN maintain reliable SIBI recognition in low-light environments.
Analisis Dampak Implementasi Payment Gateway Terhadap Peningkatan Penjualan pada E-Business Di Batam Muhammad Dody Firmansyah; Syaeful Anas Aklani; Wilson Wilson
Progresif: Jurnal Ilmiah Komputer Vol 21, No 1 (2025): Februari
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v21i1.2624

Abstract

This research aims to analyze the impact of implementing a payment gateway on increasing sales in e-business in Batam using the Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT) models. This study uses quantitative and qualitative methods, with data collected through questionnaires involving 108 e-business respondents. The research results show that the factors Perceived Usefulness, Performance Expectancy, and Security have a significant influence on the intention to adopt payment gateways. Analysis of the validity and reliability of the model shows that all indicators and variables in this research meet good standards. These findings indicate that the higher the perceived usefulness and security, the greater the likelihood of e-business actors adopting this technology. Therefore, optimizing security features, ease of use, and system reliability are important factors in increasing the adoption of payment gateways in e-businessKeywords: Payment Gateway; E-Business; Technology Acceptance Model; Unified Theory of Acceptance and Use of Technology AbstrakPenelitian ini bertujuan untuk menganalisis dampak implementasi payment gateway terhadap peningkatan penjualan di e-business di Batam dengan menggunakan model Technology Acceptance Model (TAM) dan Unified Theory of Acceptance and Use of Technology (UTAUT). Studi ini menggunakan metode kuantitatif dan kualitatif, dengan data yang dikumpulkan melalui kuesioner yang melibatkan 108 responden pelaku e-business. Hasil penelitian menunjukkan bahwa faktor Perceived Usefulness, Performance Expectancy, dan Security memiliki pengaruh signifikan terhadap niat adopsi payment gateway. Analisis validitas dan reliabilitas model menunjukkan bahwa seluruh indikator dan variabel dalam penelitian ini memenuhi standar yang baik. Temuan ini mengindikasikan bahwa semakin tinggi persepsi manfaat dan keamanan, semakin besar kemungkinan pelaku e-business untuk mengadopsi teknologi ini. Oleh karena itu, optimalisasi fitur keamanan, kemudahan penggunaan, serta keandalan sistem menjadi faktor penting dalam meningkatkan adopsi payment gateway dalam e-business.Kata Kunci: Payment Gateway; E-Business; Technology Acceptance Model; Unified Theory of Acceptance and Use of Technology
ANALISIS KOMPARASI ALGORITMA K-NEAREST NEIGHBOR DAN SUPPORT VECTOR MACHINE DENGAN PENDEKATAN MULTI DATASET Julyan Adi Saputra; Syaeful Anas Aklani
BETRIK Vol. 13 No. 03 (2022): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/zg2znf05

Abstract

Data mining is a process of identifying data that is valid and has the potential to be useful to the person who did it. One of the purposes of data mining is to study previously existing data that composes certain patterns and is used to make predictions. Machine learning works by utilizing data and algorithms to create models with patterns from the data set. There are many algorithms that can be used, such as C4.5, K-Means, Support Vector Machine (SVM), K-Nearest Neighbor (K-NN), Naïve Bayes, and others. Since there are many algorithms in data mining, each has its own advantages and disadvantages. This research will focus on the comparison between the Support Vector Machine algorithm and the K-Nearest Neighbor algorithm in terms of accuracy, precision and processing time.
ANALISIS ALGORITMA MONTE CARLO UNTUK MEMPREDIKSI KEUNTUNGAN PEMBANGUNAN APARTEMEN MENGGUNAKAN SCRUM FRAMEWORK Welliam Ali; Syaeful Anas Aklani
BETRIK Vol. 13 No. 03 (2022): Jurnal Ilmiah BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : PPPM Institut Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/0085zg91

Abstract

This study aims to predict profits in apartment projects. This research was made using the Scrum framework in making AI applications and predicting the benefits of using Monte Carlo. Besides that, making AI applications uses PHP and Xampp to make AI. This study uses qualitative methods to 5 people at different developers. The findings of this study indicate that the results on the analysis of ai applications on the benefits of apartment projects are in accordance with the results on the benefits of projects in the field. The model used by the author is Scrum to help authors complete work one by one quickly and can be recognized in doing Scrum. Scrum is divided into 3 namely Product Owner, Development Team and Scrum Master. Where the Scrum Master is in charge of ensuring the sprint goes well and the Development Team and Product Owner to analyze and design applications. The findings of this study are useful for developers to predict profits in apartment projects to be built.
Agile Scrum Analysis Of Stakeholder Management Effectiveness In The Batam Real Estate Industry (Case Study: Pt Crisanta Jaya Abadi) Fernando Jose; Zulkarnain Zulkarnain; Syaeful Anas Aklani
Jurnal Media Computer Science Vol 5 No 2 (2026): April
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v5i2.10608

Abstract

The real estate industry in Batam City faces dynamic market conditions and high stakeholder complexity, requiring the adoption of flexible and adaptive project management approaches. Agile Scrum has emerged as an alternative method; however, empirical studies examining its implementation in stakeholder management within the real estate sector remain limited. This study aims to analyze the implementation of Agile Scrum and its impact on the effectiveness of stakeholder management in real estate projects at PT Crisanta Jaya Abadi. The research employs a qualitative approach using a case study method. Data were collected through in-depth interviews with eight informants consisting of company management and project team members directly involved in project execution. The collected data were analyzed using thematic analysis to identify key patterns and themes based on stakeholder perceptions. The results indicate that the implementation of Agile Scrum enhances flexibility in responding to dynamic stakeholder requirements, improves project transparency and communication effectiveness, and supports faster and more accurate cross-functional decision-making. Furthermore, both internal and external stakeholder involvement becomes more active through continuous feedback mechanisms throughout the project lifecycle. Nevertheless, the success of Agile Scrum implementation is strongly influenced by human resource readiness and consistency in applying Agile principles. This study is expected to provide practical insights for real estate companies and contribute to academic literature on the application of Agile Scrum in non-information technology sectors.
Development of an Automated Attendance System Based on Facial Recognition Using Convolutional Neural Networks (CNN) for Kaca Super Jaya MSME: Pengembangan Sistem Kehadiran Otomatis Menggunakan Pengenalan Wajah Menggunakan Convolutional Neural Network (CNN) terhadap UMKM Kaca Super Jaya Syaeful Anas Aklani; Jetset; Suwarno Suwarno
JOINCS (Journal of Informatics, Network, and Computer Science) Vol. 9 No. 1 (2026): April
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/joincs.v9i1.1692

Abstract

Attendance management is a critical component of human resource administration, yet conventional methods such as manual sign-in sheets and card-based systems are often inefficient, error-prone, and vulnerable to manipulation. This study aims to design and implement an automatic attendance system based on face recognition using Convolutional Neural Networks (CNN) for UMKM Kaca Super Jaya. The proposed system replaces manual attendance by enabling real-time, contactless, and automated attendance recording through facial identification. An applied research approach with qualitative methods was employed, involving system development, direct observation, and structured interviews with users. The CNN model was trained using facial image datasets under various conditions, including different lighting levels, facial expressions, and viewing angles, to improve robustness and accuracy. The system architecture integrates a camera as input, a CNN-based face recognition model, a backend server, and a web-based dashboard for attendance monitoring and reporting. Experimental results show that the system achieved an average face recognition accuracy of 96%, demonstrating reliable performance even under suboptimal lighting and non-frontal face angles. The implementation significantly reduced attendance processing time, minimized human error, and lowered the potential for fraudulent practices such as proxy attendance. These findings indicate that CNN-based face recognition is an effective and practical solution for enhancing attendance management efficiency and accuracy in small and medium enterprises.
ANALISIS EMPIRIS BIG DATA ANALYTICS BERBASIS POWER BI TERHADAP KAPABILITAS DINAMIS UKM RITEL INDONESIA Diana Rose, Felicia; Eryc, Eryc; Aklani, Syaeful Anas
JOISIE (Journal Of Information Systems And Informatics Engineering) Vol. 10 No. 1 (2026)
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/joisie.v10i1.5330

Abstract

Perkembangan teknologi digital telah menghasilkan lonjakan big data yang menuntut kemampuan analisis lebih maju. Namun, di negara berkembang seperti Indonesia, tingkat adopsi Big Data Analytics (BDA) di kalangan Usaha Kecil dan Menengah (UKM) ritel masih rendah, sehingga menciptakan gap empiris terkait bagaimana keterbatasan sumber daya memengaruhi pemanfaatan teknologi analitik. Penelitian ini bertujuan menguji pengaruh BDA berbasis Power BI terhadap penguatan kapabilitas dinamis UKM ritel Indonesia. Pendekatan kuantitatif digunakan melalui survei berskala Likert kepada 100 pemilik atau pengelola UKM yang telah menggunakan Power BI. Data dianalisis menggunakan regresi linear berganda untuk mengevaluasi pengaruh parsial maupun simultan antara variabel penelitian. Hasil penelitian menunjukkan bahwa BDA, Power BI, dan efisiensi operasional berpengaruh positif dan signifikan terhadap kapabilitas dinamis, dengan nilai Adjusted R² sebesar 0,526. Efisiensi operasional merupakan faktor paling dominan dalam memperkuat kemampuan adaptasi dan respons terhadap perubahan pasar. Temuan ini memperkaya literatur mengenai kapabilitas dinamis pada UKM di negara berkembang serta memberikan implikasi praktis bahwa investasi pada teknologi analitik dan optimalisasi proses operasional dapat membantu UKM meningkatkan daya saing secara berkelanjutan.
Co-Authors Aldovanda Haflah Setiawan Alex Setiawan Aliefazlea, Qanaya Dherryl Anderson, Atnan Ari Anson Anson Basiron, Halizah Chadric, Felix Charles, Kevin Christina, Lidya Daniel Lim David David Dayton Dayton Delvin Jason Derwin Galen Diana Rose, Felicia Dr. Hendi Sama, S.Kom., M.M.e-Business. Edwin Charley Eka Sucipto Elia, Elia Elvert Elvert Eric Lau Erlina Erlina Erwin Erwin Eryc, Eryc Felix Favian Felix, Ivan Fernando Jose Firmansyah, Muhamad Dody Francisco, Francisco Franky Chainoor Johari Haeruddin Haeruddin Haeruddin, . Haslim, Sartika Dewi Hendi Sama Hertianto Hertianto Hosse Fernando Irawan, Calvianthieno Ivan Felix Jacky Jacky Jacky, Jacky Jason Aaron Yang Jenary Randa Liling Jenry Winata Jesselyn Jesslyn, Jesslyn Jetset Jimmy Chandra Jonathan Jonathan Josua Yoprisyanto Julyan Adi Saputra Julyan Adi Saputra Julyanto Julyanto Junifer, Junifer Juzariah Juzariah Juzariah, Juzariah Kelvin Wijaya, Kelvin Kelvyn Kelvyn Kelvyn Kendrik Jonatan Kenny Wilson Lubis, Nywara Natriyasmara Melsen Melsen Muhamad Dody Firmansyah Muhammad Ardiansyah Muhammad Dody Firmansyah Mungkap Mangapul Siahaan Novita Putri Parlindungan Tampubolon Petrick Handy Putra Prasetyo, Stefanus Eko Purwandi, Nellsen Puspitasari, Divanaka Putra, Muhamad Zhabiyan Dwi Putri, Novita Randa Liling, Jenary Regina, Alya Renata, Doreen Rio Fernando, Rio Rosario, Rakit Ricardo Ryan Gunawan Ryo Winata Salsabila, Nanda Salsabilah, Anisah Sama, Hendi Setiawan, Aldovanda Haflah Shanata Limanto Sherlyn, Sherlyn Shermay Sihombing, Angelika Putri Stephanie Stephanie Steven Steven Susanti, Aida Suwarno Suwarno Liang Suwarno Suwarno Suwarno Suwarno Tjahyadi, Surya Tony Jack Tan Ding Welliam Ali Welliam Ali Wilson Wilson Wiyandi, Wiyandi Yang, Jason Aaron Yasa, Irma Sefina Yoprisyanto, Josua Yu Lun Zoin, Shania Zulkarnain Zulkarnain Zulkarnain, Nur Zareen