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All Journal Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Komputer Antartika Jurnal Kecerdasan Buatan dan Teknologi Informasi
Miftahul Jannah
Politeknik Negeri Bengkalis
Computer Science & IT

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DESIGN OF AN IOT-BASED AUTOMATIC MOSQUE DOOR SYSTEM USING PIR AND CAMERA SENSORS FOR SMART WORSHIP ACCESS Annisa Rizqi; Dania Fitriyani; Ika Herni; Rozy Ilhami; M. Rahmadoni Khoiriansyah; Miftahul Jannah
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 2 (2026): May 2026
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i2.501

Abstract

Mosques and mushallas are worship facilities with high congregational activity, requiring a secure, comfortable, and efficient door access system. Manual door operation often causes several problems, such as doors not closing properly, noise caused by slamming doors, and high physical contact between users and the door. This study aims to design and develop an automatic door system based on Passive Infrared (PIR) sensors and surveillance cameras integrated with Internet of Things (IoT) technology to improve security and convenience in mosque and mushalla environments. The research method used is Research and Development (R&D), consisting of system requirement identification, hardware and software design, prototype implementation, testing, and evaluation. The system uses PIR sensors or cameras to detect the presence of worshippers, microcontrollers such as Arduino, ESP32, or Raspberry Pi as the control center, and servo motors or DC motors as automatic door actuators. The system is also equipped with a real-time notification feature through Telegram to send information and visual documentation to administrators. The results show that the system is capable of detecting movement, automatically opening and closing doors, and sending notifications along with visual documentation in real time. The system improves user convenience, reduces physical contact with doors, and facilitates remote security monitoring by administrators. In addition, the use of ESP32-CAM is considered effective and economical for implementing IoT-based automatic door systems.
Pengembangan Sistem Informasi Tracer Study Alumni Berbasis Web Menggunakan Laravel di Politeknik Negeri Bengkalis Dimas Adrian; Dwi Pratiwi; Suci Ramadhani; Cintya Nabila; Elisa Valencia; Abdul Rohim; Miftahul Jannah
Jurnal Komputer Antartika Vol. 4 No. 2 (2026): Juli
Publisher : Antartika Media Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70052/jka.v4i2.1364

Abstract

Tracer study merupakan kegiatan penting bagi perguruan tinggi untuk mengetahui perkembangan lulusan setelah menyelesaikan pendidikan, khususnya terkait kondisi pekerjaan, kesesuaian kompetensi, dan persebaran alumni. Namun, proses pengumpulan data alumni di banyak perguruan tinggi masih dilakukan secara manual atau menggunakan media yang tidak terintegrasi sehingga data sulit diperbarui dan dikelola secara optimal. Penelitian ini bertujuan untuk merancang dan membangun sistem informasi alumni berbasis web menggunakan framework Laravel pada Politeknik Negeri Bengkalis. Metode penelitian yang digunakan meliputi analisis kebutuhan sistem, perancangan sistem menggunakan Unified Modeling Language (UML), implementasi aplikasi, dan pengujian sistem. Sistem yang dikembangkan menyediakan fitur pengelolaan data alumni, pengisian tracer study, dan pengelolaan laporan oleh admin. Hasil penelitian menunjukkan bahwa sistem informasi alumni berbasis Laravel mampu membantu proses pendataan lulusan secara lebih efektif, terstruktur, dan mudah diakses oleh alumni maupun pihak kampus. Sistem ini diharapkan dapat mendukung kebutuhan pelaporan akademik, akreditasi, serta memperkuat hubungan antara alumni dan institusi.   Tracer study is an important activity for higher education institutions to monitor the development of graduates after completing their studies, particularly related to employment conditions, competency relevance, and alumni distribution. However, alumni data collection in many higher education institutions is still conducted manually or through non-integrated media, making the data difficult to update and manage effectively. This study aims to design and develop a web-based alumni information system using the Laravel framework at Politeknik Negeri Bengkalis. The research methods used include system requirement analysis, system design using Unified Modeling Language (UML), application implementation, and system testing. The developed system provides features for alumni data management, tracer study data collection, and report management by administrators. The results of this study indicate that the Laravel-based alumni information system is capable of supporting alumni data collection processes more effectively, systematically, and accessibly for both alumni and campus administrators. This system is expected to support academic reporting, accreditation requirements, and strengthen the relationship between alumni and the institution.
Integrasi K-Means dan Random Forest untuk Rekomendasi Menu Makanan Bergizi (MBG) Berdasarkan Usia Penerima: Integration of K-Means and Random Forest for Recommendation of Nutritious Food Menu (MBG) Based on Recipient Age Miftahul Jannah; Ajang Sopandi; Ryan Zulham Ramadhani; Hengki Rusdianto; Khelvin Ovella Putra
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 6 No. 3 (2026): MALCOM July 2026
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v6i3.2671

Abstract

Program Makan Bergizi Gratis (MBG) bertujuan meningkatkan kualitas gizi anak-anak sebagai upaya mendukung pertumbuhan dan kesehatan peserta didik, namun implementasinya menu makanan MBG yang diberikan setiap harinya masih belum sesuai dengan kebutuhan peserta didik disekolah karena tidak berdasarkan kelompok usia. Perbedaan usia, berat badan, dan tinggi badan memengaruhi kebutuhan nutrisi sehingga diperlukan pendekatan berbasis data untuk menghasilkan rekomendasi menu makanan MBG yang tepat. Penelitian ini mengusulkan integrasi algoritma K-Means Clustering dan Random Forest untuk mengelompokkan penerima berdasarkan kelompok usia peserta didik sehingga nutrisi yang diberikan sesuai dengan rekomendasi status gizi WHO serta Angka Kecukupan Gizi (AKG) Kementerian Kesehatan RI. Data yang digunakan berjumlah 1190 data menu pangan sebagai studi awal pengembangan sistem. Hasil clustering digunakan sebagai dasar pengelompokan menu makanan berdasarkan kategori gizi dari data menu pangan dan menggunakan Random Forest dalam menentukan menu harian berdasarkan data AKG. Hasil penelitian menunjukkan bahwa metode yang diusulkan mampu memberikan rekomendasi menu makanan bergizi secara otomatis sesuai dengan karakteristik individu. Penelitian ini menunjukkan bahwa integrasi metode clustering dan klasifikasi efektif dalam mendukung sistem rekomendasi menu makanan bergizi berbasis data.
Co-Authors Abdul Rohim Ajang Sopandi Annisa Rizqi Cintya Nabila Dania Fitriyani Dimas Adrian Dwi Pratiwi Elisa Valencia Hengki Rusdianto Ika Herni Khelvin Ovella Putra M. Rahmadoni Khoiriansyah Rozy Ilhami Ryan Zulham Ramadhani Suci Ramadhani