Article Per Year (5 Year)
p-Index From 2021 - 2026
8.427
P-Index
This Author published in this journals
All Journal Jurnal Ekonomi : Journal of Economic JIK Jurnal Ilmu Komputer IKRA-ITH Informatika : Jurnal Komputer dan Informatika Jurnal Pengabdian Masyarakat AbdiMas Jiko (Jurnal Informatika dan komputer) Jurnal Nasional Komputasi dan Teknologi Informasi IKRA-ITH ABDIMAS Aptisi Transactions on Technopreneurship (ATT) Jurnal Mantik JUKI : Jurnal Komputer dan Informatika Jurnal Teknologi Informatika dan Komputer Jurnal Pemberdayaan Komunitas MH Thamrin Journal of Technology and Informatics (JoTI) Indexia Jurnal Eurekamatika IKA BINA EN PABOLO : PENGABDIAN KEPADA MASYARAKAT Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Journal of Scientech Research and Development KOLONI Jurnal Penelitian Rumpun Ilmu Teknik Innovative: Journal Of Social Science Research Media Abdimas Journal of Multidisciplinary Science: MIKAILALSYS Nusantara Journal of Multidisciplinary Science
Binastya Anggara Sekti
Universitas Esa Unggul
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Other

Published : 72 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 72 Documents
Search

 4   5   6   7   8 
PERANCANGAN DAN IMPLEMENTASI SISTEM ZAKAT DAN DONASI ONLINE DENGAN FITUR TRANSPARANSI UNTUK YAYASAN YATIM PIATU LASKAR LANGIT Anggasura Rysmu Rahmatullah; Binastya Anggara Sekti; Nizirwan Anwar; Popong Setiawati
Journal of Scientech Research and Development Vol 8 No 1 (2026): JSRD, June 2026
Publisher : Ikatan Dosen Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56670/jsrd.v8i1.1526

Abstract

Perkembangan teknologi digital menuntut lembaga nirlaba, termasuk yayasan yatim piatu, untuk beradaptasi guna menjaga relevansi dan keberlanjutan. Tantangan utama yang sering dihadapi adalah krisis kepercayaan publik terkait akuntabilitas pengelolaan dana. Yayasan Yatim Piatu Laskar Langit, sebagai objek studi, masih menerapkan sistem pengelolaan donasi konvensional yang manual, sehingga rentan terhadap ketidakakuratan data, memperlambat kinerja, dan menyulitkan penyajian laporan pertanggungjawaban yang transparan. Kondisi ini menghambat optimalisasi penghimpunan dana dan pembangunan hubungan jangka panjang dengan donatur. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem informasi zakat dan donasi online sebagai solusi atas permasalahan tersebut. Metode penelitian meliputi analisis kebutuhan, perancangan sistem, implementasi, dan pengujian. Hasil yang diharapkan adalah sebuah platform digital fungsional yang tidak hanya memfasilitasi transaksi donasi, tetapi juga mengintegrasikan fitur transparansi sebagai intinya. Melalui sistem ini, donatur dapat mengakses laporan alokasi dana secara real-time dan memantau penyaluran bantuan. Dengan demikian, implementasi sistem ini diharapkan mampu meningkatkan akuntabilitas dan kredibilitas yayasan, membangun kembali kepercayaan donatur, serta mengoptimalkan penghimpunan dana demi kesejahteraan anak-anak yatim piatu di Yayasan Laskar Langit.
TELEGRAM-BASED CHATBOT DESIGN FOR ACADEMIC SERVICE AUTOMATION AT FASILKOM UEU USING A LOW-CODE PLATFORM Gabriela Marry Christiana Simanjuntak; Dewi Setiowati; Binastya Anggara Sekti; Sawali Wahyu
JIKO (Jurnal Informatika dan Komputer) Vol 9 No 2 (2026)
Publisher : Program Studi Teknik Informatika Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v9i2.11579

Abstract

Administrative services at the Faculty of Computer Science, Universitas Esa Unggul, face persistent challenges due to high volumes of repetitive inquiries and limited operational hours, which may reduce service efficiency and responsiveness. This study aims to design, implement, and evaluate FasilkomAssist, a 24/7 Telegram-based chatbot developed using the ADDIE framework and a Low-Code/No-Code (LCNC) approach via the n8n workflow automation platform. The system integrates Google Gemini as a Large Language Model (LLM) with Google Sheets, Google Drive, Google Calendar, and Telegram to automate the dissemination of Thesis information and administrative procedures. Evaluation was conducted through Black-box testing, the System Usability Scale (SUS), and User Acceptance Testing (UAT) involving 30 respondents. Results indicate a 96% response accuracy across 17 valid testing scenarios, with an average response time of 4–6 seconds. The SUS score of 70.75 places the system within the “Acceptable” range (Grade C), indicating satisfactory usability with opportunities for optimization. Furthermore, UAT conducted with Faculty Administration Staff yielded a score of 84.67%, confirming functional adequacy and user acceptance. These findings demonstrate that an LCNC-based chatbot can improve efficiency, accessibility, and service quality in academic administrative environments without requiring advanced programming expertise.
Perancangan dan Pembangunan Sistem Portal IT Service Management Berbasis Flutter (Studi Kasus CV. Sabar Maju) Aulia Ilham Zukri; Hendry Gunawan; Binastya Anggara Sekti; Tri Ismardiko Widyawan
Nusantara Journal of Multidisciplinary Science Vol. 2 No. 4 (2024): NJMS - November 2024
Publisher : PT. Inovasi Teknologi Komputer

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

Abstract

CV. Sabar Maju sebagai perusahaan yang bergerak dibidang retail sangat bergantung pada sistem IT untuk membantu proses bisnisnya yang beroperasional pada multi cabang. Sistem IT yang berjalan belum didukung oleh sistem layanan IT (IT services) sehingga menyebabkan tidak aktualnya data terkait dengan layanan IT yang berjalan seperti data aset IT dan data perbaikan aset IT sehingga riwayat aset tidak jelas. Proses pelaporan kendala juga masih dilakukan secara manual sehingga penanganan kendala menjadi tidak efektif. IT Service Management (ITSM) merupakan seperangkat kebijakan dan praktek untuk mengimplementasikan, memberikan, dan mengelola layanan IT untuk end-user yang ditentukan dan tujuan bisnis yang ditentukan juga. Pembuatan sistem portal dengan acuan ITSM dapat membantu perusahaan dalam menjalankan layanan IT pada perusahaan. Front-end sistem portal ini dibangun menggunakan kerangka kerja Flutter yang bermanfaat dengan dukungan multi-platform yang baik sehingga sistem portal dapat berjalan pada platform mobile dan web dengan 1 basis kode. Back-end pada sistem ini menggunakan Laravel yang bermanfaat pada kecepatan proses dalam pembangunan sistem. Pengujian sistem dilakukan menggunakan System Usability Scale (SUS) dan black-box testing. Hasil pengujian menunjukan bahwa sistem portal yang dibangun sudah membantu memberikan sistem layanan IT yang efektif dan efisien
Implementasi Algoritma Constraint-Based Filtering dan Hybrid Data Retrieval pada Aplikasi Fit Meal Berbasis Mobile Menggunakan Flutter Amru Abbay; Binastya Anggara Sekti
Jurnal Penelitian Rumpun Ilmu Teknik Vol. 5 No. 3 (2026): Jurnal Penelitian Rumpun Ilmu Teknik
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juprit.v5i3.7073

Abstract

An unbalanced diet is a major risk factor for various chronic diseases, such as obesity and hypertension. Although public awareness of nutrition has begun to increase, the phenomenon of "choice overload" in existing diet-tracking applications often makes it difficult for users to select menus that are truly healthy. This research aims to design and develop a mobile-based application named "Fit Meal," which is capable of providing personalized and filtered food menu recommendations. The application was developed using the Flutter framework to support cross-platform flexibility and integrates the Constraint-Based Filtering algorithm to filter food based on health criteria (such as the elimination of fried and junk food). Additionally, the Hybrid Data Retrieval technique is applied to optimize nutritional data searching by combining the speed of the local SQLite database with the data completeness of an external API. The test results indicate that the Hybrid method successfully improves data search efficiency, while the Constraint-Based algorithm provides accurate daily menu variations according to the user's calorie target, achieving a 100% success rate in filtering unhealthy food ingredients. Fit Meal is expected to be an effective digital solution for smartphone users in implementing a healthy diet independently and consistently.
Implementation Of LSTM, GRU, And BI-LSTM Algorithms For LQ45 Index Prediction Angga Muhammad Galih; Binastya Anggara Sekti
KOLONI Vol. 5 No. 3 (2026): SEPTEMBER 2026
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/koloni.v5i3.1460

Abstract

The Indonesian capital market, particularly the LQ45 Index and its leading sectoral stocks, exhibits high volatility and complex non-linear price patterns. This complexity renders conventional statistical methods insufficient for accurate forecasting and risk mitigation. This study aims to develop and compare three Deep Learning architectures Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Bidirectional LSTM (Bi-LSTM) in predicting the daily close prices of the LQ45 Index and six highly liquid stocks. The research methodology adopted the CRISP-DM framework utilizing historical data from January 2020 to May 2026. To prevent data leakage and ensure scientific rigor, model training incorporated a 5-Fold Walk-Forward Validation with an expanding window and multi-seed training. Performance was evaluated and benchmarked against statistical baseline models (Naïve, ARIMA, ETS) using RMSE, MAPE, and Directional Accuracy (DA). Experimental results reveal that all Deep Learning models achieved highly accurate performance with an average MAPE below 5%. The GRU model proved to be the most optimal, recording the lowest RMSE across the majority of assets. While statistical models showed slight superiority in minimizing short-term nominal errors, Deep Learning architectures consistently outperformed in recognizing market trend directions. Finally, the best models were successfully deployed into StockAI, an interactive web application built on the Flask framework using Model-View-Template (MVT) architecture for real-time live inference.
Pengembangan Sistem Monitoring Barang Berbasis QR Code untuk KPI dan Insentif Payroll Karyawan Menggunakan Metode Waterfall Hafiz Ramadhan; Raden Teddy Iswahyudi; Nizirwan Anwar; Binastya Anggara Sekti
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 10 No. 2 (2026): IKRAITH-INFORMATIKA Vol 10 No 2 Juli 2026
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

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

Abstract

Penelitian ini mengusulkan pengembangan sistem monitoring keluar masuk barang berbasis QR Code yangmengintegrasikan pencatatan transaksi gudang, penilaian Key Performance Indicator (KPI), dan perhitungan insentifpayroll karyawan. Permasalahan utama yang ditangani meliputi pencatatan manual, keterlambatan pembaruan stok,kesalahan input, keterbatasan jejak audit, serta belum terhubungnya data aktivitas operasional dengan evaluasi kinerjadan insentif. Pengembangan sistem menggunakan metode Waterfall melalui tahapan analisis kebutuhan, perancangan,implementasi, pengujian, dan pemeliharaan. Setiap barang dan transaksi diidentifikasi melalui QR Code, kemudian sistemmerekam waktu, jenis transaksi, kuantitas, identitas petugas, dan perubahan stok. Data transaksi digunakan sebagaisumber terukur untuk membentuk indikator KPI yang mencakup akurasi pencatatan, ketepatan waktu proses,produktivitas transaksi, dan kepatuhan prosedur. Nilai KPI selanjutnya menjadi masukan bagi mekanisme insentif payrolldengan parameter bobot dan ambang yang dapat dikonfigurasi sesuai kebijakan organisasi. Perancangan juga menerapkanpemisahan hak akses administrator, petugas gudang, supervisor, dan bagian keuangan serta menyediakan dashboardmonitoring dan audit trail. Pengujian fungsional dirancang menggunakan pendekatan black-box dan evaluasi usabilitysebelum penerapan operasional. Hasil penelitian pada tahap ini berupa arsitektur proses, model data, rancangan KPI,aturan perhitungan insentif, dan skenario pengujian yang dapat menjadi dasar implementasi. Rancangan sistemdiharapkan meningkatkan ketertelusuran transaksi, konsistensi data persediaan, transparansi evaluasi kinerja, danakuntabilitas perhitungan insentif tanpa menggantikan proses validasi manajerial.
Integrated Web-Based Point of Sale and Sales Analytics: A Case Study of Ngunjuk Sardana, Gusti Muhamad; Sekti, Binastya Anggara
Journal of Multidisciplinary Science: MIKAILALSYS Vol 4 No 3 (2026): Journal of Multidisciplinary Science: MIKAILALSYS
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mikailalsys.v4i3.12097

Abstract

Limited transaction records constrain microenterprises’ ability to trace sales and evaluate business performance, highlighting the need for integrated digital tools that convert operational data into actionable information. This study developed a web-based point-of-sale system incorporating sales analytics through a case study of Ngunjuk, a beverage microenterprise in Tangerang, Indonesia. The system was developed using Rapid Application Development, encompassing requirements planning, user design, construction, and cutover. Data were collected through direct observation, semi-structured interviews, and a literature review. The resulting application integrates employee-facing transaction processing with an owner-facing administrative dashboard and provides structured transaction recording, searchable transaction histories, product and category performance analysis, period-based sales trends, monthly sales reports, promotional-package evaluation, and internal financial estimates. Black-box testing covered 62 functional scenarios, comprising 28 employee point-of-sale scenarios and 34 administrative-dashboard scenarios, all of which produced the expected outcomes. User acceptance testing with the owner and an employee further confirmed the acceptance of all nine role-specific scenarios. These findings demonstrate that integrating transaction processing with sales analytics can transform daily sales records into traceable information that supports operational control and managerial evaluation. This study contributes context-specific evidence concerning the digitalization of sales management in microenterprises. Nevertheless, because the findings derive from a single case study, they do not establish the system’s generalizable effectiveness across microenterprise settings. Future research should therefore evaluate longitudinal use, usability, security, and system performance in broader operational contexts.
Design and Development of a Web-Based CRM Information System to Support Product Sales Strategies for Coffee MSMEs Zahran, Muhammad Adi Zacky; Sekti, Binastya Anggara
Journal of Multidisciplinary Science: MIKAILALSYS Vol 4 No 3 (2026): Journal of Multidisciplinary Science: MIKAILALSYS
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mikailalsys.v4i3.12127

Abstract

The rapid growth of the coffee shop industry requires Micro, Small, and Medium Enterprises (MSMEs) to adopt digital technologies that strengthen customer loyalty, retention, and operational efficiency. Kopi Banget MSME continues to rely on manual transaction recording and lacks an integrated customer database, limiting its ability to implement systematic retention strategies and manage customer relationships effectively. This study aims to design and develop a web-based Customer Relationship Management (CRM) system based on the CRM Lite-Loyalty concept to support customer loyalty and retention strategies. The system was developed using the Rapid Application Development (RAD) methodology, which facilitates iterative development and flexible adaptation to user requirements. The application was implemented using the Laravel framework and a MySQL database and integrated with a WhatsApp Gateway API and automated scheduling mechanisms. System evaluation employed Black-Box Testing to validate functionality and PageSpeed Insights to assess application performance. The findings show that the developed system supports rapid customer onboarding, automated loyalty point calculation, reward redemption validation, and proactive customer retention through personalized WhatsApp messaging. Functional testing achieved 100% successful validation across 26 test scenarios, while performance testing indicated responsive interface performance. These results demonstrate that the CRM Lite-Loyalty system can integrate loyalty management and retention mechanisms into a unified web-based platform. The study contributes a practical digital CRM solution for MSMEs and provides an implementable approach for improving customer relationship management, loyalty program administration, and retention activities through integrated digital processes.
Comparative Evaluation of Deep Learning Architectures for Early Skin Cancer Detection Using Dermatoscopic Images  Aurel Elviolita Putri; Agung Mulyo Widodo; Nizirwan Anwar; Binastya Anggara Sekti
Journal of Technology and Informatics (JoTI) Vol. 8 No. 2 (2026): Vol. 8 N. 2 (2026)
Publisher : Universitas Dinamika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37802/

Abstract

Early identification of skin cancer is essential for improving diagnostic reliability and patient outcomes. Although convolutional neural networks (CNNs) have demonstrated promising performance in dermoscopic image classification, comparative evaluations on imbalanced multiclass datasets remain challenging. This study compares three transfer learning-based CNN architectures—VGG16, ResNet50, and MobileNetV2—for seven-class skin lesion classification using the imbalanced HAM10000 dataset. All models were evaluated using the same dataset partitions, image resolution, and performance metrics, while architecture-specific augmentation and loss-function strategies were retained. In particular, VGG16 used MixUp, ResNet50 used CutMix, VGG16 and ResNet50 employed Focal Loss, and MobileNetV2 used label smoothing. Performance was assessed using accuracy, precision, recall, F1-score, confusion matrices, and ROC–AUC. ResNet50 achieved the best overall performance, with 85.71% accuracy and a weighted F1-score of 0.8502, ahead of VGG16 (82.52%, 0.8172) and MobileNetV2 (79.32%, 0.7739). ResNet50 also showed the highest recall for melanoma and dermatofibroma among the three tested configurations, although minority-class sensitivity remained limited. These results favor ResNet50 under the evaluated training configurations; however, differences in augmentation and loss functions prevent attributing performance gaps solely to network architecture.
Training in the Use of Artificial Intelligence Software for Academic Purposes of High School Students Yohanes Bowo Widodo; Mohammad Narji; Sondang Sibuea; Agung Suryatno; Binastya Anggara Sekti; Kodrat Mahatma
Jurnal Pemberdayaan Komunitas MH Thamrin Vol. 7 No. 1 (2025): Jurnal Pemberdayaan Komunitas MH Thamrin
Publisher : LPPM Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jpkmht.v7i1.2566

Abstract

In the ever-evolving digital era, understanding and skills in artificial intelligence (AI) technology are becoming increasingly important, especially for students at the secondary level. This training aims to introduce students to the basic concepts of AI and its applications in academic contexts, as well as to improve their ability to use AI-based software to support the teaching and learning process. Research shows that the application of AI in education can provide strong technical support for personalized learning, allowing students to learn according to their own style and pace. In addition, AI also has the potential to increase student engagement through gamification methods, which can create a more engaging and effective learning experience. However, it is important to consider ethical and transparency issues in the use of AI, including the protection of student data and the adaptation of the role of teachers in learning contexts that are increasingly influenced by this technology. This training involves a variety of interactive and practical methods, including simulations and the use of relevant AI software, to ensure that students not only understand the theory but can also apply it in real situations. Thus, it is hoped that students can develop the skills needed to face challenges in the academic and professional world that are increasingly influenced by technology. The program also seeks to build awareness of the importance of AI education among students, which is in line with the national education policy that encourages the development of digital skills. Through this training, it is expected that students will not only gain knowledge about AI, but also develop a positive attitude towards this technology, so that they can utilize it optimally in their studies and in the future.
Co-Authors Ady Sutjahyono Agung Suryatno Ahmad, Ahluddin Saiful Alfiana, Rita Amru Abbay Andri Kurnia Maulana Angga Muhammad Galih Angga Novita Prasetyo Ningrum Anggasura Rysmu Rahmatullah Annisa Fitria Antara, Nyoman Putra Anton Nurfendi Ary Prabowo Aulia Ilham Zukri Aurel Elviolita Putri Badie Uddin Bere, Emilianto Sefri Budi Tjahjono Darlan, Muhamad Davies Tandianto Dedi Setiadi Dita Chandra Samsiya Dwi Rio Aryanto Euis Sadeli Evi Martaseli Evi Martaseli Fadhil Ezar Rahman Fathur Andre Fadilah Fatwa Arrevi Fatwa Arriva Febrianti Widyahastuti Freddy Harris, Freddy Gabriela Marry Christiana Simanjuntak Gusti Muhamad Sardana Gusti, Aldo Prima Hafiz Ramadhan Hani Dewi Ariessanti Hasanah, Diannur Haziro Ulfa Hendry Gunawan Hendry Gunawan Hendry Gunawawan Ibnu Hadi Ichwani, Arief Ilham Adi Maulana Ilham Banuaji Irma Tiara Irsyad Taufiq Ilham Supardi Iwan Setiawan Iwan Setiawan Julius Jerry Nolasco Kalagi, Richard Kevin Maruli Kodrat Mahatma Krisogonus Wiero Baba Kaju Laksono, Mohamad Iqbal Ajie Lim Jong Su Lisasih, Nin Yasmine Mahatma, Yudi Mamok Andri Senubekti Marwan, Rudi Heri Meria, Lista Mohamad Iqbal Ajie Laksono Mohammad Norman Gaza Laksono Muhammad Hadi Arfian Muhammad Kaisar Stevan Priadi Mulyana, Imam Narji, Mohammad Nicholas Patrick Varian Nisa Aulia Nixon Erzed Nizirwan Anwar Prianto Roito Siregar Putri Adella Cahyaningtyas Putri Jelita Syifa Eraydya Raden Teddy Iswahyudi Rafli Al Ihsan Rahaman, Mosiur Rahmahani, Adhining Prabawati Ramadhan, Akmil Maulana Rano Agustino Ricky Rivandy A’oetpah Rizki Dwi Sanjaya Rizky Nur Azizah Roesfiansjah Rasjidin Ryan Putra Laksana Sardana, Gusti Muhamad Setiawati, Popong Setiowati, Dewi Shefia Anggraeni Siti Nur Kholifah Sondang Sibuea Sopian, Abu Suherman, Reza Bintang Sutjahyono, Ady Syifa Maulida Akmalia Tandianto, Davies Tri Ismardiko Ulfa, Haziro Ulum, Muhamad Bahrul Ummanah Ummanah, Ummanah Utami, Aliph Putri Vanessa, Delivia Vincent Laurensius Hambaya Wahyu, Sawali Wahyudi, Endik Wasahua, Idris Widodo, Agung Mulyo Widyawan, Tri Ismardiko Yanathifal Salsabila Anggraeni Yohanes Bowo Widodo Yulfitri, Alivia Yulhendri Yulhendri Zahran, Muhammad Adi Zacky Zhafira Anindya Tiaraputri