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Prayer Time Reminder and Mobile Phone Jammer for Mosque Based on Raspberry PI Wahyu Aulia Nurwicaksana; Septyana Riskitasari; Supriatna Adhisuwignjo
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 2 No. 1 (2017): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v2i1.159

Abstract

Prayer time reminder based on raspberry pi with LCD TV as a display that not only can be set according to locationbased on GPS coordinates, but also contain information in the form of picture, text, video, etc. This is much betterthan just simple words placed on dot matrix or running text as it is today. Display design can be fully customized asper needed, it can be accommodated because the system based on raspberry pi mini PC. The method used for thisresearch is by conducting literature studies and field studies that are necessary for system design and manufacture.This system had several components involve include raspberry pi, signal jammer, air freshner, and LCD TV. Thisprayer time reminder display information of mosque name, address, clock, prayer schedule based on GPS coordinate,event photo, announcement, video, and running text as per installed program. This reminder also act as mobile phonesignal jammer, so there is no interference based on mobile phone signal. Jammer activated when entered prayer timeup to at least 30 minutes later. It function can also be added as air freshner which will spray as long as the jammer isactivated at 10 minute intervals.
Sistem Komposter Rumah Tangga Berbasis Arduino dengan Monitoring Real-Time Parameter Pengomposan Mila Fauziyah; Ratna Ika Putri; Supriatna Adhisuwignjo
Jurnal Elektronika dan Otomasi Industri Vol. 12 No. 3 (2025): Jurnal Elkolind Vol 12 No 3 (September 2025)
Publisher : Program Studi Teknik Elektronika Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/elkolind.v12i3.9150

Abstract

Peningkatan timbulan sampah organik rumah tangga menuntut metode pengolahan yang lebih terukur, efisien, dan dapat dikendalikan. Proses pengomposan konvensional kerap gagal karena parameter lingkungan seperti suhu, kelembapan, dan pH tidak berada pada rentang optimal. Penelitian ini merancang komposter otomatis berbasis Arduino Uno yang dilengkapi sensor HC-SR04, DS18B20, soil moisture, dan sensor pH untuk melakukan pemantauan real-time dan pengendalian aktuator secara otomatis. Sistem mengaktifkan motor pencacah selama 3 menit, pompa cairan tetes tebu selama 50 detik, serta pompa EM4 selama 2 detik, sebelum memasuki fase pengomposan. Sensor kelembapan mengendalikan pompa air ketika nilai di bawah 40%, dan mengaktifkan motor pengaduk saat kelembapan melebihi 60%, menjaga kondisi aerobik tetap stabil. Pengujian dilakukan pada kapasitas bahan 5 kg, dengan rentang suhu pengomposan tercatat pada 32–45°C dan pH akhir berada pada kisaran 6,5–7,2, yang sesuai untuk kompos matang. Sistem mampu mempertahankan kelembapan pada rentang ideal 40–60% serta menghasilkan kompos dalam waktu lebih cepat dibanding metode manual. Hasil ini menunjukkan bahwa integrasi sensor dan aktuator berbasis mikrokontroler mampu meningkatkan kestabilan proses pengomposan dan mengurangi kebutuhan intervensi operator
Mask Detection App Uses Haar Cascade and Convolutional Neural Network to Alert Comply with Health Protocols Cahya Rahmad; Nurfaidah Nurfaidah; Supriatna Adhisuwignjo; Mamluatul Hani’ah
Applied Information System and Management (AISM) Vol. 6 No. 2 (2023): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v6i2.31396

Abstract

This study aims to identify the face of a person whether wearing a mask or not wearing a mask accompanied by an appeal to the importance of wearing a mask. The contribution of this paper to science is to provide an overview of the results of accuracy, precision, recall used by the method used with data that can be accessed by many people, so that it can be developed further or can be compared. This system uses two techniques, namely the classification of whether a person is wearing a mask or not using the Convolutional Neural Network (CNN) model. The architecture used is DenseNet-12 to detect human face objects. The data used has a total of 2332 data sets, 200 of which were retrieved manually as research objects, and the rest were obtained from Kaggle. All data is evaluated using the camera in real-time. The test results show that testing scenario one has the highest score with an accuracy of 85% while testing scenario two gets results of 80%, the precision value in testing scenario one gets results of 75%, and testing scenario two has results of 88%. Scenarios 1 and 2 also have the same recall value of 100%. Based on the data analysis, it can be concluded that the use of the Haar Cascade approach and the Convolutional Neural Network with the DenseNet-121 architecture produces good performance in the case of real-time detection of masked and non-masked facial objects.
Co-Authors Adhitya Bhawiyuga, Adhitya Adi Candra Kusuma Ahmad Wildan Ridho Syahputra Alia*, Nila Alif, Alif_Komaruddin Anindya Dwi Risdhayanti Anita Dwi Febriyana Arizaldi, Nizar Bagus Fajar Afandi Bagus Fajar Afandi Afandi Bambang Priyadi Bimantara Sakti Cahya Rahmad Dahnial Syauqy Danang Rahmad Setyawan Denda Dewatama Dimas Kukuh Prasetyo Edi Sulistio Budi Eka Mandayatma Ervina Aprilia Saputra Fahmawati Hamida Fahmawati Hamida Febriyana, Anita Dwi Fengky Adie Perdana, Fengky Adie Hamida, Fahmawati Hari Kurnia Safitri Herman Hariyadi Herman Hariyadi Ari Murtono Hilmi Fauzi Indrazno Siradjuddin Kharis Sugiarto Komarudin Achmad Krisnawan Pambudi Krisnawan Pambudi Kusmintarti, Anik Lathifatun Nazhiroh Lathifatun Nazhiroh Ifa Lokendra Aditisna Widigdyo Mamluatul Hani’ah Maskhur Zulkarnain Melani, Erlin Mila Fauziyah Mila Fauziyah Mila Fauziyah Moechammad Sarosa Muhamad Rifa'i Muhammad Jodi Pamenang Muhammad Rifa’i Muhammad Rizki Aditya Mulia Titah Klarista Nadira Aisyah Ibrahim Ningrum, Mery Octavia Nizar Arizaldi Nurfaidah Nurfaidah Nurwicaksana, Wahyu Aulia Pamenang, Muhammad Jodi Patma, Tundung Subali PERMATASARI, DINDA AYU Prasetyo, Budi Eko Ratih Indri Hapsari Ratna Ika Putri Riskitasari, Septyana Ronilaya, Ferdian Septriandi Wirayoga Septyana Riskitasari Septyana Riskitasari Septyana Riskitasari Setiawan, Budhy Sidik Nurcahyo Sigi Syah Wibowo Sungkono Sungkono Wahyu Aulia Nurwicaksana Wahyu Aulia Nurwicaksana WAHYU AULIA NURWICAKSANA Wahyu Aulia Nurwicaksana Wahyu Aulia Nurwicaksana Widhy Hayuhardhika Nugraha Putra Widigdyo, Lokendra Aditisna Winarno, Totok Wirawan Wirawan Yulianto Yulianto Yulianto Yulianto Yulianto Yulianto Yulianto Zaliyah Amalia Zulfikar Iannur Awwal