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Application for data collection and monitoring of COVID-19 patients in Sukorame Community Health Center Toga Aldila Cinderatama; Rinanza Zulmy Alhamri; Fery Sofian Efendi; Kunti Eliyen; Benni Agung Nugroho
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 12 No. 1 (2022): Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (649.893 KB) | DOI: 10.31940/matrix.v12i1.19-30

Abstract

The significant increase in COVID-19 cases in Indonesia in May-July 2021 overwhelmed health workers. One of the efforts to monitor the spread of COViD-19 disease is collecting data on patients and proper monitoring. For example, the Sukorame Community Health Center, Mojoroto Kediri, does not yet have an application to record and monitor COVID-19 patients. Data collection is currently done manually by writing in books and excel. This study designed and built a data collection and monitoring application for COVID-19 patients to help Puskesmas staff obtain more accurate patient data and monitor the related patient data. This study implements the waterfall method, including system requirements, design, implementation, verification, and maintenance. The results of this study are the applications that can help and facilitate Community Health Center in collecting data on COVID-19 as a form of effort in overcoming and preventing the spread of COVID-19 in the work area of Sukorame Community Health Center, Kediri City. Based on the user satisfaction questionnaire results, 75% of users consisting of staff and heads of community health centers were helped by this application.
Pengembangan Aplikasi Mobile untuk Penyelesaian Vehicle Routing Problem Benni Agung Nugroho; Abidatul Izzah; Kunti Eliyen
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 1 (2023): February 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i1.4552

Abstract

The vehicle routing problem (VRP) is a combinatorial optimization problem faced by transportation services related to pick up or delivery, such as industrial raw materials distribution, tour and travel, or travel routing problems in general. VRP is an NP-hard problem where the higher the dimensions of the problem will have a higher computational complexity. Without realizing it, VRP problem are often encountered every day. Therefore, it will be very useful if VRP solver is implemented in mobile application media. So, the aim of this work is developing a mobile application to get the shortest path and minimal cost in VRP problem. It is integrated by both Mapbox API and Google Maps API to get a real distance for modeling problem. The result show that the developed application can run well in all possibility condition.
Peningkatan Produksi dan Jangkauan Pemasaran UMKM "Rizqi" Melalui Mesin dan Marketplace Abidatul Izzah; Yohan Bakhtiar; Ratna Widyastuti; Benni Agung Nugroho; Saiful Arif; Devina Rosa Hendarti; Ahmad Dony Mutiara Bahtiar
ABDI: Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 7 No 3 (2025): Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat
Publisher : Labor Jurusan Sosiologi, Fakultas Ilmu Sosial, Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/abdi.v7i3.1219

Abstract

Indonesia memiliki potensi produksi bawang merah karena tingginya konsumsi masyarakat. Melihat potensi ini, Bapak Surasa dari, Kota Kediri mendirikan usaha bawang merah goreng “Rizqi” sejak 2018. Bapak Surasa menjalankan usaha ini secara mandiri dan manual. Hanya bagian perajangan yang menggunakan alat kayu yang didorong. Selain itu, masalah lain yang ditemui adalah seiring berjalannya waktu jumlah pelanggan tidak bertambah karena pemasaran yang dilakukan masih sebatas menitipkan produk ke warung dan pedagang keliling. Hal ini karena bapak Surasa belum mencoba pemasaran online untuk memperluas jangkauan pemasaran. Oleh karena itu, dalam program pengabdian masyarakat ini, tim pengabdian menawarkan sejumlah solusi untuk mengatasi permasalahan tersebut antara lain dengan memanfaatkan teknologi mesin perajang untuk menambah kapasitas produksi dan memanfaatkan marketplace untuk memperluas jangkauan pemasaran. Metode pelaksanaan kegiatan pengabdian masyarakat dimulai dari pengadaan alat perajang dan dilanjutkan dengan pelatihan penggunaan alat. Kemudian dilanjutkan dengan membuatkan toko online di marketplace sekaligus pelatihan penggunaannya. Tim pengabdian juga melakukan pendampingan proses penggunaan alat dan pemasaran online. Hasil dari program pengabdian masyarakat ini adalah penerapan teknologi alat perajang sehingga UMKM bawang goreng Rizqi mampu menghasilkan enam kali lipat yakni 60kg setiap kali produksi. Di sisi lain, sampai akhir kegiatan pengabdian masyarakat dilaksanakan, UMKM bawang goreng Rizqi sudah mendapat 2 pesanan dari luar kota Kediri yakni Surabaya dan Lamongan masing-masing 5 pcs. Selanjutnya diharapkan UMKM bawang goreng Rizqi mampu memanfaatkan teknologi mesin perajang yang telah diberikan dan aktif memasarkan produk di marketplace yang telah dibuat.
Mobile Based Application for Loan Approval and Loan Distribution Using Machine Learning in Savings and Loan Cooperatives Benni Agung Nugroho; Rinanza Zulmy Alhamri; Toga Aldila Cinderatama
International Journal of Entrepreneurship, Business, and Creative Economy Vol. 5 No. 2 (2025): July
Publisher : Research Synergy Foundation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31098/ijebce.v5i2.3397

Abstract

Several savings and loan cooperatives (KSP) in Kediri City, Indonesia have used a website-based information system for increasing efficiency. However, the financial health of KSP in Kediri City remains low because there are many delays in credit payments and even bad credit occurs. Manual profiling for approving loan application causes bad decisions. The management needs a function to obtain recommendation for approving loan application and also for distributing the loan service to potential members automatically. The purpose of this research is to develop a mobile based application for loan approval recommendation and loan distribution utilizing Machine Learning (ML) in KSP and to study the performance of the model using Support Vector Machine (SVM) method. It adopted Waterfall Method including analysis, design, implementation, and testing for two purposes including SVM model development and Android based application development. The dataset experienced preprocess including data cleaning, label encoding, and normalization. It obtained amounts to 150 data for loan approval recommendation and 150 data for loan distribution. Implementation stage includes developing Android based application and Python based ML. The testing stage uses functional testing for Android application and K-Fold Cross Validation for ML performance. Android application has two users, the first is admin that can manage member, retrieve loan approval recommendation, and manage loan application, then the second is member that can retrieve loan distribution and apply loan. The performance of the ML using SVM includes the accuracy of loan approval recommendation reached 90%, while loan distribution reached 85%.
Deteksi Plat Nomor Kendaraan Angkutan Bus Menggunakan YOLOv11 Benni Agung Nugroho; Toga Aldila Cinderatama; Abidatul Izzah; Ellya Nurfarida
Jurnal Informatika dan Multimedia Vol. 17 No. 2 (2025): Jurnal Informatika dan Multimedia
Publisher : Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jtim.v17i2.9204

Abstract

Penelitian ini mengatasi permasalahan pendataan plat nomor bus secara konvensional di terminal yang rentan terhadap kesalahan manusia, pelaporan yang lambat, dan kurangnya transparansi. Tujuan penelitian ini adalah merancang dan mengimplementasikan sistem deteksi dan pengenalan plat nomor angkutan bus secara otomatis menggunakan kombinasi teknologi Kecerdasan Buatan (AI), khususnya model deep learning YOLOv11, dan Internet of Things (IoT). Penelitian ini menggunakan Raspberry Pi 5 sebagai perangkat edge yang terhubung dengan webcam untuk menangkap video beresolusi 1280x720 , yang kemudian melakukan deteksi plat nomor secara real-time. Model YOLOv11 dilatih menggunakan 682 frame gambar , menunjukkan kinerja yang sangat baik pada dataset validasi dengan nilai mean Average Precision (mAP50) sebesar 0.98674. Meskipun keterbatasan Raspberry Pi 5 tanpa dedicated Neural Processing Unit (NPU) membatasi kecepatan pemrosesan real-time menjadi 10–18 FPS pada resolusi 640x480 , kecepatan ini dinilai mencukupi untuk deteksi bus di lingkungan terminal karena pergerakan kendaraan yang tidak cepat. Teks plat nomor yang berhasil dikenali dan timestamp kemudian dikirimkan ke database Firebase melalui arsitektur IoT. Sistem yang dihasilkan diharapkan dapat membantu dalam pendataan kendaraan bus di terminal dengan lebih cepat, efisien, dan akuntabel