Claim Missing Document
Check
Articles

Found 38 Documents
Search

Internet of Things-Based Home Trash Capacity Tracking System with Instant Notifications Munthe, Era Sari; Diantoro, Karno; Herwanto, Agus
Digitus : Journal of Computer Science Applications Vol. 2 No. 3 (2024): July 2024
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/digitus.v2i3.257

Abstract

Garbage created from routine household activities is collected and stored in household garbage cans. Location This garbage makes rubbish collection easier to live in and helps to maintain a clean household environment. Household garbage cans are often designed to fit specific demands and feature a tight-fitting cover to keep sickness and animals out and to minimize unwanted odors. The layout To stop the spread of bacteria or fungus, something must be easy to clean. Lack of technology to monitor garbage bin fullness and inability to precisely monitor fill capacity, which can lead to trash overflow, offensive odors, and animal nuisances. Thus, volume sensorization techniques and Internet of Things (IoT) technologies are the answers to this challenge. To enable real-time waste capacity volume monitoring and to give users level information about trash charging through the Blynk platform, the system will deliver When the garbage can is full, an alarm sensor-equipped warning will ring. The Arduino IDE and the C programming language are the software used. The findings of the study demonstrate that the garbage can capacity monitoring system The information about waste filling levels that are provided in real-time by this IoT-based system is effective. By using this approach, homeowners can easily keep a clean and healthy home environment by knowing when it's time to remove the trash.
Pelatihan Pengenalan Search Dan Collecting Metadata Ter-Indeks Dimensions AI Sinkronisasi Dengan Mendeley Setiawan, Iwan; Martaseli, Evi; Anwar, Nizirwan; Asri, Jefry Sunupurwa; Ramadhan, Iksan; Herwanto, Agus; Arfian, M. Hadi; Novita, Diana; Widyawan, Tri Ismardiko
Journal Of Human And Education (JAHE) Vol. 4 No. 1 (2024): Journal Of Human And Education (JAHE)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jh.v4i1.648

Abstract

Mendeley perangkat aplikasi reference manager (desktop/web) yang dapat mengintegrasikan pada platform academic social network untuk berkolaborasi pengutipan judul publikasi untuk menghasilkan suatu artikel dan ter-indeks. Aplikasi ini sangat memudahkan pengguna dalam mengelola sejumlah judul artikel dan memudahkan peneliti dalam men-sitasi sehingga tersusun dalam daftar pustaka, dengan style tertentu yang disesuaikan dari pihak penerbit (Harvard, APA 6th, IEEE, Vancouver dan sejenisnya). Pengabdian mempunyai tujuan dan manfaat bagi peserta penelusuran dan penyusunan daftar Pustaka suatu karya ilmiah (nasional/internasional). Metode yang digunakan pelatihan ini dengan (1) ceramah daring; (2) penyajian tutorial bagaimana mengoperasikan reference manager mendeley (online/offline) dengan baik dan benar serta sesuai dengan kaidah penulisan. Dikarenakan pada Mendeley versi desktop (gratis) batas penyimpanan hanya memori sebesar 2 GB, bisa dalam format pdf/ris/bib dapat diupload secara manual maupun otomatis. Dan dalam pelatihan ini akan memamparkan bagaimana cara mengintegrasikan Mendeley dengan Dimension AI, pengguna dapat menelusuri nama penulis, nama jurnal/konferensi, ISSN, ISBN, DOI, penerbit dan tanggal terbit artikel tersebut. Dari hasil pelatihan pasca pemamparan materi dan diskusi serta pendampingan para peserta (mahasiswa dan dosen) memperoleh kemudahan dalam mengoperasikan Mendeley dan Dimensions AI, mengutip referensi (ris/bib) dengan mudah sekali, akurasi, sederhana, effisien dan effektif dengan hasil akhir tersusun daftar pustaka (MyLibrary).
Literacy Alley: Efforts to Enhance Literacy Passion Among Students at Kanisius Demangan Baru Yogyakarta Elementary School Nurhayati, Nurhayati; Herwanto, Agus; Marwan, Marwan
Jurnal Indonesia Sosial Sains Vol. 5 No. 03 (2024): Jurnal Indonesia Sosial Sains
Publisher : CV. Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jiss.v5i03.1052

Abstract

This study aims to explore and evaluate the efforts made in increasing literacy love in students of Kanisius Demangan Baru Elementary School (SD) in Yogyakarta. Literacy plays a crucial role in students' intellectual and social development, and an understanding and appreciation of literacy can enrich their educational experience. This research method involves collecting qualitative data through classroom observation, interviews with teachers and students, as well as analyzing documents related to literacy programs that have been implemented, and finally drawing conclusions. The results showed that efforts to increase love for literacy involve innovative teaching strategies and integrating literacy into the curriculum. Teachers actively promote students' interest in reading through activities such as book discussion groups, story and storytelling performances, library visits, promoting literacy corner projects in classrooms, and enlivening school walls and hallways with student literacy works. In addition, science literacy programs can also improve students' knowledge of nature, and storytelling teacher programs can improve teachers' and students' abilities with literary appreciation. The evaluation results showed a positive increase in students' reading interest and literacy understanding. The findings may provide insight for other schools looking to increase the love of literacy at the primary level, emphasizing the importance of collaboration between teachers, students, and parents in creating an educational environment that supports children's literacy development.
PENGEMBANGAN APLIKASI WISATA KULINER LOKAL BERBASIS ANDROID MENGGUNAKAN METODE RAPID APPLICATION DEVELOPMENT (RAD) Samuel, Samuel; Herwanto, Agus; Irawan, Bambang; Tjahjono, Budi
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 9 No. 3 (2025): IKRAITH-INFORMATIKA Vol 9 No 3 November 2025
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In the digital era, the regional tourism sector is required to continuously innovate in providing information and services to tourists, including promoting the potential of local culinary tourism. This research aims to design and develop an Android-based local culinary tourism application as an effort to support increased tourist visits to the region. The development method used is Rapid Application Development (RAD), which is considered capable of producing applications with a fast, flexible, and adaptive development process to user needs. The application provides a search feature for nearby culinary locations, recommendations for popular restaurants, travel route maps, and user reviews, supporting a more informative and interactive culinary tourism experience. Testing was conducted through several stages, from unit testing to system testing, to ensure each feature operates according to specifications. The development results indicate that this application can help tourists find culinary information practically while also supporting local culinary businesses in promoting their products digitally. It is hoped that this application can support increasing the attractiveness of culinary tourism in the region, strengthening the local tourism ecosystem, and making a significant contribution to the growth of the technology-based creative economy.
Pemberdayaan UMKM Melalui Pelatihan Strategi Marketing Digital dan Affiliate TikTok untuk Meningkatkan Brand Awareness dan Penjualan Novita, Diana; Hanifah, Hanifah; Ismail, Ismail; Herwanto, Agus
Jurnal Abdimas Kartika Wijayakusuma Vol 6 No 4 (2025): Jurnal Abdimas Kartika Wijayakusuma
Publisher : LPPM Universitas Jenderal Achmad Yani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26874/jakw.v6i4.1195

Abstract

Pemberdayaan UMKM di era digital menjadi kebutuhan mendesak mengingat tingginya tingkat persaingan bisnis serta perubahan perilaku konsumen yang semakin bergantung pada platform digital. TikTok sebagai media sosial berbasis video pendek menunjukkan pertumbuhan signifikan dan menghadirkan peluang besar bagi UMKM melalui fitur TikTok Shop dan TikTok Affiliate. Kegiatan yang dilakukan bertujuan menganalisis efektivitas pelatihan strategi marketing digital dan pemanfaatan program Affiliate TikTok dalam meningkatkan brand awareness dan penjualan UMKM. Media sosial terbukti mampu meningkatkan brand exposure dan interaksi konsumen. Hasil kegiatan menunjukkan bahwa pelatihan digital marketing berbasis TikTok meningkatkan pemahaman UMKM dalam membuat konten, memahami algoritma TikTok, serta bekerja sama dengan kreator melalui sistem afiliasi. Penerapan strategi ini berdampak pada peningkatan jangkauan audiens dan konversi penjualan. Selain itu, kolaborasi dengan affiliate terbukti efektif dalam meningkatkan brand awareness melalui pendekatan influencer-driven marketing. Hasil kegiatan ini mendukung temuan sebelumnya bahwa digital marketing berperan penting dalam memperkuat daya saing UMKM. Hasil studi ini dapat digunakan oleh UMKM dan pemerintah untuk merancang program pelatihan digital yang lebih tepat sasaran.
Perancangan dan Implementasi Aplikasi Virtual Try-On Pakaian dengan Fitur Unggah Model 3D Berbasis Web Menggunakan React dan Three.js Septian, Irfan; Ariessanti, Hani Dewi; Herwanto, Agus; Go, Ratna Yulika
Journal Artificial: Informatika dan Sistem Informasi Vol. 4 No. 1 (2026): April 2026
Publisher : Pustaka Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54065/artificial.1142

Abstract

E-commerce telah berkembang pesat, dengan visualisasi produk dan kecerdasan buatan (AI) menjadi faktor kunci dalam meningkatkan pengalaman pengguna dan membantu pengambilan keputusan pembelian. Penelitian ini bertujuan merancang dan mengembangkan aplikasi web Virtual Try-On untuk produk busana, di mana pengguna dapat melihat pakaian dalam bentuk model 3D interaktif serta memanfaatkan fitur chatbot AI untuk rekomendasi fashion. Aplikasi dibangun menggunakan framework React.js di sisi frontend dan Three.js untuk merender model 3D pakaian yang dapat diunggah (upload) ke sistem. Fitur 3D memungkinkan pengguna memutar, memperbesar, dan melihat pakaian dari berbagai sudut seolah-olah mencobanya secara virtual, memberikan gambaran yang lebih nyata dibanding foto 2D. Selain itu, diintegrasikan AI “Gemini” sebagai virtual stylist – berupa chatbot interaktif yang dapat menjawab pertanyaan seputar produk dan memberikan saran outfit personal. Metodologi penelitian meliputi analisis kebutuhan, perancangan UI/UX, implementasi sistem, serta pengujian fungsional (black-box) dan uji coba pengguna. Hasil implementasi menunjukkan platform e- commerce dengan fitur try-on 3D dan chatbot AI dapat berjalan dengan baik. Pengguna dapat berinteraksi dengan model 3D secara lancar dan mendapatkan rekomendasi fashion secara real-time. Fitur-fitur ini terbukti meningkatkan pemahaman pengguna teqrhadap produk sekaligus memberikan dukungan keputusan yang lebih akurat melalui teknologi AI. Pengujian menunjukkan seluruh fungsionalitas utama sudah sesuai kebutuhan, dan umpan balik pengguna awal mengindikasikan pengalaman belanja yang lebih interaktif, informatif, dan percaya diri dengan adanya visualisasi 3D dan asisten virtual.
Sistem Monitoring Sensor Udara Berbasis Arduino dengan Menggunakan Telegram Visal Mohammad Rizki; Agus Herwanto; Budi Tjahjono; Bambang Irawan
Jurnal Informatika Universitas Pamulang Vol 10 No 3 (2025): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jiup.v10i3.53436

Abstract

This study aims to design and implement an Arduino Uno and NodeMCU ESP8266-based air quality monitoring system integrated with Telegram as an Internet of Things (IoT)-based automatic notification medium. This system uses MQ-7, MQ-135, and MG811 sensors to detect CO, CO₂, and other air pollutants. The research method is descriptive quantitative with testing at two locations with different activity levels, namely (1) Lebak Bulus Terminal (heavy traffic) and (2) Jl. H. Midar Pondok Pinang (low activity). The results show that CO levels reached 120 PPM at Lebak Bulus Terminal in the afternoon, which is categorized as “unhealthy” based on the Air Pollutant Standard Index (ISPU). The system was able to detect differences between clean and polluted air with 97% accuracy, a response time of 2.3 seconds, and a 98% notification success rate via Telegram. These results indicate that the system operates in real-time, efficiently, and is easily accessible, while also increasing public awareness of air quality and mitigating health risks due to pollution.
Convolutional Neural Networks-Based Deep Learning for Diabetic Retinopathy Detection Nurmalasari, Mieke; Kurniawati, Anastasia Cyntia Dewi; Herwanto, Agus; Kurniawati, Dyah; Muchlis, Husni Abdul; Pertiwi, Tria Saras
Indonesian Journal of Artificial Intelligence and Data Mining Vol 9, No 1 (2026): March 2026
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v9i1.38631

Abstract

Diabetic retinopathy (DR) is a major complication of diabetes that can cause permanent vision loss, affecting about 35% of people with type 2 diabetes worldwide. However, existing diagnostic models often struggle with class imbalance and limited generalizability across diverse real-world datasets. Early detection is crucial, yet manual screening is time-consuming and depends on expert assessment. This study develops an automated DR diagnostic system using deep learning to classify fundus images by severity. The model uses an EfficientNetB3 CNN pretrained on ImageNet, combined with CLAHE preprocessing to enhance image contrast. The preprocessing steps include resizing, CLAHE, normalization, and data augmentation (±20° rotation, horizontal flipping, and ZCA whitening). The dataset is the Gaussian-filtered APTOS 2019 set, consisting of 2,750 images across five DR levels (0–4). The model achieved 95% training accuracy and 75% validation accuracy, with overfitting observed after epoch 14. While training performance was high, evaluation metrics (Precision, Recall, F1-Score, and AUC) indicate the need for early stopping or regularization to improve generalization. Overall, CNN-based deep learning can effectively automate DR detection, though further optimization is required for better performance on unseen data. Clinically, this automated pipeline offers a reliable decision-support tool to prioritize high-risk patients for immediate ophthalmological review
Co-Authors A.A. Ketut Agung Cahyawan W Adi Widiantono Adrian Adrian Akbar, Habibullah Alfian Mahendra, Muhammad Anggoro, Rio Anwar Senen Ardana Putri, Sevtia Azis, Nur Bambang Irawan Budi Tjahjono Cahyomayndarto, Eko Diah Aryani, Diah Diana Novita Diana Novita Diantoro, Karno Donny Hamzah P.H. Dyah Kurniawati Dzikra, Alfi Muhammad Elsy Rahajeng, Elsy Era Sari Munthe Essy Malays Sari Sakti Evi Martaseli Fahrul Nurzaman Hani Dewi Ariessanti hanifah hanifah Hanifah Hanifah Husni Abdul Muchlis Ichwani, Arief Insana, Dwi Rorin Mauludin Irawan, Bambang Irwanto, Dola Ismail Ismail Istianingsih, Nanik Iwan Setiawan Jason, Aaron Jefry Sunupurwa Asri Khasanah Khasanah Komul, Theodora Maria Putri Kurniawati, Anastasia Cyntia Dewi Latumapayahu, Febrian Firmansyah Malabay Malabay Marwan Marwan Mayndarto, Eko Cahyo Melinda Melinda Moch Anton Maulana Mooduto, Hanriyawan Adnan Muhammad Hadi Arfian Muhlasin, Muhlasin Nafisah Yuliani Nixon Erzed Nizirwan Anwar Novia Aprilia Nugroho, Irfan Hari Nurchaerani, Meiyanti Nurhayati Nurhayati Nurmalasari, Mieke Pangestu Selokaton, Anjang Prabowo, Ary Pramesty, Feranti Destina Primaranti, Jenyta Putera Setiawan, Erlangga Rahaman, Mosiur Ratna Yulika Go Roy Budiharjo RR. Ella Evrita Hestiandari Samuel Samuel Sembiring, Rinawati Septian, Irfan Setiowati, Dewi Sheha, Kholid Nur Sitti Suhada Sri Kurniawati Sucipto, Purwo Agus Sutanto, Imam Tria Saras Pertiwi Unik Ambarwati Visal Mohammad Rizki Wahyu, Sawali Widyanto, Muhammad Laras Widyawan, Tri Ismardiko Yulhendri Yulhendri Yuliani, Nafisah Yuliati -