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All Journal JUKI : Jurnal Komputer dan Informatika Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB Jejak digital: Jurnal Ilmiah Multidisiplin
Muhammad Iqbal
Universitas Pelita Bangsa
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences Other

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Rancang Bangun Website Rukun Tetangga Menggunakan Pendekatan MVC Dedi Afandi; Muhammad Iqbal
JUKI : Jurnal Komputer dan Informatika Vol. 8 No. 1 (2026): JUKI : Jurnal Komputer dan Informatika, Edisi Mei 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53842/juki.v8i1.2380

Abstract

The manual administrative system in RT 02, RW 022, Bahagia Subdistrict, Babelan District, Bekasi Regency faces several issues, including inefficiency, data loss risks, and limited public access to administrative services. This study aims to develop a web-based information system to improve administrative efficiency and transparency at the neighborhood level. The system was designed using the Model-View-Controller (MVC) approach with React.js for the frontend, Express.js for the backend, and MySQL for the database. The research method included observation, interViews, system design, implementation, and testing using the Black Box Testing method. The results show that the system facilitates the management of public information, document submissions, resident administration, financial records, and cash tracking in a structured and responsive manner. This research contributes to the digitalization of neighborhood-level administrative services through a user-friendly and transparent web platform.
Analisis Efisiensi Proses Drafting 2D Dies pada Empat Proses Dies Menggunakan Metode Diagram Fishbone melalui Integrasi Siemens NX 7.5 Avifan Septianto; Rafli Alfandi; Muhammad Iqbal; Akmal Arfie; Yudi Prasetyo
Jejak digital: Jurnal Ilmiah Multidisiplin Vol. 2 No. 4 (2026): JUNI-JULI
Publisher : INDO PUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63822/fskne577

Abstract

The 2D dies drafting process in the manufacturing industry plays an important role in supporting tooling dies production. A common problem encountered is the use of different software platforms between Siemens NX for 3D modeling and AutoCAD for 2D drafting, resulting in longer processing times, potential data inconsistencies, and increased file storage requirements. This study aims to analyze the improvement of 2D dies drafting efficiency through full integration using Siemens NX 7.5. The method used in this research is the fishbone diagram method to identify the root causes of the problems. The research object involved four dies processes, with an initial average drafting time of 36 hours, which was reduced to 16 hours after implementation. The results showed an efficiency improvement of 55.6%, a reduction in the potential for data synchronization errors, and a decrease in additional software usage costs. The implementation of drafting standards, NX templates, work instructions, and internal training became the main factors contributing to the success of this improvement.
Analisa Algoritma K-Nearest Neighbor (KNN), Naive Bayes dan Decision Tree C4.5 dengan Metode Klasifikasi Pada Kanker Payudara Menggunakan RapidMiner Agung Nugroho; Muhammad Iqbal
Jurnal SIGMA Vol 14 No 2 (2023): Juni 2023
Publisher : Teknik Informatika, Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/sigma.v14i2.7311

Abstract

Kanker payudara adalah kanker yang terbentuk di sel-sel bagian payudara. Ini adalah kanker yang paling umum pada wanita dan penyebab utama kematian akibat kanker pada wanita di seluruh dunia. Kanker payudara biasanya dibagi menjadi dua jenis: benign, atau biasanya disebut jinak dan malignant, atau biasanya disebut ganas. Kanker jinak biasanya ditandai dengan benjolan kecil bulat dan lembut. Di bidang obat, keuangan, marketing, dan sains sosial, data mining adalah alat yang populer untuk melakukan analisis yang sudah dibuktikan. Studi ini akan membandingkan pendekatan K-Nearest Neighbor (KNN), Naive Bayes, dan Decision Tree C4.5 untuk mengklasifikasikan kanker payudara. Masalah penelitian ini adalah algoritma mana yang memiliki tingkat akurasi tinggi yang dapat digunakan dengan dataset kanker payudara dan dapat memberikan informasi tentang pola atau model untuk deteksi dini kanker payudara. Hasil penelitian yang dilakukan menggunakan CRISP-DM menunjukkan bahwa K-Nearest Neighbor (KNN) memiliki nilai akurasi tertinggi dengan 97,14% dan nilai AUC-nya 0,976. Nilai AUC-nya juga menunjukkan klasifikasi yang sangat baik, dengan nilai AUC antara 0,90 dan 1,00.
Co-Authors Agung Nugroho Akmal Arfie Avifan Septianto Dedi Afandi Rafli Alfandi Yudi Prasetyo