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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika CogITo Smart Journal Seminar Nasional Teknologi Informasi Komunikasi dan Industri Jurnal Teknologi Informasi dan Pendidikan Informatika Majalah Ilmiah UPI YPTK Journal of Computer Scine and Information Technology Jurnal Pustaka Mitra : Pusat Akses Kajian Mengabdi Terhadap Masyarakat Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Ekonomika Dan Bisnis Jurnal Komtekinfo Jurnal Pengabdian Masyarakat Dharma Andalas Jurnal Quancom: Jurnal Quantum Komputer Jurnal Riset Pendidikan Multidisiplin dan Pengabdian Kepada Masyarakat Journal of Integrated Knowledge and Innovation
Rahman, Sepsa Nur
Universitas Putra Indonesia YPTK Padang
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Decision Support System for Determining Recipients of Subsidized Foodstuffs for Poor Families Using the Simple Addictive Weighting Method Afifah Sagita Pratiwi; Gushelmi; Sepsa Nur Rahman
Journal of Computer Scine and Information Technology Volume 10 Issue 4 (2024): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v10i4.111

Abstract

Technology is increasingly becoming a necessity that must be met, both in the world of education and in the world of business and social, especially information technology is used not only as a support but also as a primary need that can be used to provide information quickly. In accordance with what has been determined to obtain Subsidized Food, criteria are needed to determine who will be selected to receive subsidized food. The distribution of subsidized food is distributed to underprivileged or poor citizens. To assist in determining who is eligible to receive subsidized food, a decision support system is needed. One method that can be used for Decision Support Systems is by using Simple Additive Weighting (SAW). In this study, a case will be raised, namely finding the best alternative based on predetermined criteria by using the SAW method to calculate the method in the case. This method was chosen because it is able to select the best alternative from a number of alternatives, in this case the intended alternative is those who are entitled to receive subsidized food based on the specified criteria. The study was conducted by finding the weight value for each attribute, then a ranking process was carried out which would determine the optimal alternative, namely the poor. After the study was conducted, the results obtained were that there were 4 alternatives receiving Subsidized Food and the one with the highest value was alternative 5 with the name Yuhel Fentri with a value of 0.875.
Implementasi Face Recognition dan Algoritma Otp Pada Akses Keamanan Monitoring Pembangkit Listrik Masril, Mardhiah; Yesha Aishya Aprila; Sepsa Nur Rahman; Firdaus
JURNAL QUANCOM: QUANTUM COMPUTER JURNAL Vol. 4 No. 1 (2026): Juni 2026
Publisher : LPPM-ITEBA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62375/d13myx30

Abstract

The development of digital technology demands smarter and more integrated security systems, particularly for critical infrastructure such as power plants, which play a crucial role in national energy distribution. Power plant monitoring systems that still use conventional authentication methods like static passwords and RFID have weaknesses such as the risk of theft, forgery, and access misuse. Furthermore, the lack of integration with Internet of Things (IoT) systems means that the monitoring process is not fully real-time and potentially causes delays in detecting intrusions and security threats. This situation highlights the need for a layered security system capable of accurately and dynamically verifying user identity. This research aims to implement facial recognition technology and the Time-Based One-Time Password (TOTP) algorithm as a layered authentication system for IoT-based power plant monitoring. The system is designed to combine facial biometric verification with a time-based OTP code that can be generated independently of an internet connection. The integration of these two methods is expected to improve access security by minimizing the risk of identity spoofing, credential theft, and cyberattacks. The methods used include system design, hardware and software implementation, and performance testing of authentication and IoT integration. The expected outcome of this research is the creation of a more adaptive, reliable security system capable of recording access activity in real time. Therefore, the implementation of IoT-based facial recognition and TOTP can be an effective solution for enhancing protection for power plant monitoring systems, which are vital national assets.
Rancang Bangun Box Makanan Berkuah Panas Berbasis Esp32 dengan Kontrol Suhu Otomatis dan Monitoring Blynk Muhammad Nico Rinaldi; Okta Andrica Putra; Sepsa Nur Rahman
Journal of Integrated Knowledge and Innovation Vol. 2 No. 1 (2026): Vol.2 No.1 2026
Publisher : Universitas Pahlawan Tuanku Tabusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jiki.v2i1.38

Abstract

Perkembangan layanan pengiriman makanan berbasis aplikasi meningkatkan kebutuhan akan sistem yang mampu menjaga kualitas makanan berkuah panas selama proses distribusi. Penelitian ini bertujuan merancang dan membangun box makanan berkuah panas berbasis ESP32 dengan kontrol suhu otomatis dan monitoring menggunakan aplikasi Blynk. Sistem memanfaatkan sensor DHT22 untuk mendeteksi suhu di dalam box, kemudian data diproses oleh ESP32 untuk mengendalikan heater dan kipas DC secara otomatis berdasarkan batas suhu minimum 60°C dan maksimum 65°C. Selain itu, sistem dilengkapi dengan aplikasi Blynk untuk monitoring suhu secara real-time dan pengiriman notifikasi ketika suhu mencapai batas yang telah ditentukan maupun saat box terbuka. Pengujian dilakukan pada beberapa kondisi, yaitu box tanpa heater, box dengan heater menggunakan air panas, box dengan heater menggunakan air bersuhu normal, serta pengujian monitoring dan notifikasi. Hasil pengujian menunjukkan bahwa tanpa heater suhu air panas menurun dari 78,5°C menjadi 49,3°C dalam waktu 30 menit, sedangkan dengan heater aktif suhu hanya menurun hingga 60,7°C. Pengujian menggunakan air bersuhu normal juga menunjukkan peningkatan suhu dari 27,9°C menjadi 40,3°C selama 30 menit. Hasil tersebut menunjukkan bahwa sistem mampu memperlambat penurunan suhu, meningkatkan suhu secara bertahap, serta melakukan monitoring dan pengiriman notifikasi melalui aplikasi Blynk sesuai dengan perancangan. Dengan demikian, sistem yang dirancang dapat membantu mempertahankan kualitas makanan berkuah panas selama proses pengiriman.
Penerapan Digital Image Processing Dalam Mendeteksi dan Pengenalan Penggunaan Masker Pada Laboratorium Obat Kimia Farma Okta Andrica Putra; Sepsa Nur Rahman; Mhd Irfandi
Journal of Integrated Knowledge and Innovation Vol. 2 No. 1 (2026): Vol.2 No.1 2026
Publisher : Universitas Pahlawan Tuanku Tabusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jiki.v2i1.40

Abstract

Laboratorium Obat Kimia Farma merupakan lingkungan kerja yang memiliki risiko tinggi terhadap paparan bahan kimia, partikel berbahaya, serta potensi kontaminasi biologis sehingga penerapan Keselamatan dan Kesehatan Kerja (K3), khususnya penggunaan masker, menjadi aspek yang wajib dipatuhi. Namun, pengawasan penggunaan masker masih dilakukan secara manual sehingga kurang efektif dan berpotensi menimbulkan kelalaian. Penelitian ini bertujuan untuk menerapkan Digital Image Processing dalam mendeteksi dan mengenali penggunaan masker pada Laboratorium Obat Kimia Farma menggunakan metode Convolutional Neural Network (CNN). Sistem dikembangkan menggunakan bahasa pemrograman Python dengan memanfaatkan kamera sebagai media akuisisi citra untuk melakukan deteksi wajah dan klasifikasi penggunaan masker secara real-time. Model CNN dilatih menggunakan dataset citra wajah bermasker dan tidak bermasker sehingga mampu mengidentifikasi kondisi penggunaan masker secara otomatis..
Co-Authors Afifah Sagita Pratiwi Afrialdi Afrialdi Afrialdi, Afrialdi Andro Nugraha Aulia Fitrul Hadi Dari, Rahmatia Wulan Eva Rianti Febri Hadi Firdaus Firna Yenila Gushelmi Hadi Syahputra Hadi, Aulia Fitrul Hafizul Fadli Jafnihirda, Lika Jamhur, Annisak Izzaty Kurnia, Hezy Lavena, Deri Lika Jafnihirda Mardhiah Masril Mayang Sajida Mhd Irfandi Muhammad Gafa Akbar Awidani Muhammad Nico Rinaldi Naf’an, Emil Novi Trisna nozomi, irohito Okta Andrica Putra Okta Andrica Putra Okta Andrica Putra Ondra Eka Putra Pradani Ayu Widya Purnama Riyan Saputra Sofika Enggari Sri Rahmawati Surmayanti, Surmayanti Sylvia Kurniati Teri Ade Putra Wirawan, Nanda Tommy Yesha Aishya Aprila Yesri Elva Yusvi Diana