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Perancangan Sistem Informasi Persediaan Barang Berbasis Web Pada Toko Kuat Irvan Triana; Agus Nugroho; Meisak, Despita
Jurnal Informatika Dan Rekayasa Komputer(JAKAKOM) Vol 4 No 1 (2024): JAKAKOM Vol 4 No 1 APRIL 2024
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jakakom.2024.4.1.1644

Abstract

The Strong Shop is a shop that organizes business activities in the basic food, electronics and household furniture sectors. Currently, in inventory management at the Strong Store, they experience problems in the process of providing information on the inventory they have, where the process of counting goods is still carried out by means of physical counting. every time and takes a long time due to labor limitations, time constraints, and the many types of goods that exist. The purpose of this study is to analyze and study the problems that exist in the inventory system that runs on the Strong Store to help in designing the inventory system. To design the inventory system for the Strong Store using the PHP programming language and MySQL DBMS. The author develops the system using the waterfall method and uses the unified model language system model approach using use case diagrams, activity diagrams and class diagrams. This study resulted in an inventory system design to make it easier to search for certain information, for example information on goods data, supplier data, outgoing goods data, incoming goods data, supply reports, goods reports, incoming goods reports, outgoing goods reports related to inventory activities in Strong Shop.
Deteksi Bahasa Isyarat Bisindo Menggunakan Metode Machine Learning Agus Nugroho; Setiawan, Roby; Harris, Abdul; Beny
Jurnal PROCESSOR Vol 18 No 2 (2023): Jurnal Processor
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/processor.2023.18.2.1380

Abstract

This study aims to develop a machine learning-based application capable of detecting hand gestures and patterns in Indonesian Sign Language (BISINDO). Sign language plays a crucial role in non-verbal communication, particularly for individuals with speech impairments like the deaf. However, the challenge of comprehending sign language often inhibits interactions between the deaf and others. In an effort to address this barrier, the research leverages machine learning techniques with a focus on the Convolutional Neural Network (CNN) method, utilizing a dataset annotated with hand gesture landmarks. Landmark information providing detailed positions and shapes of key points on the hand, the CNN model can learn specific features essential for classification. The resulting application aims to bridge communication between the deaf and other individuals who may not understand sign language. By harnessing this technology, a significant improvement in the accuracy of hand gesture classification in sign language is anticipated, thereby strengthening the communication and interaction capabilities of the deaf within their environment.
Analisis Kualitas Layanan Website Rumah Sakit Umum Daerah Prof.Dr.H.M Chatib Quzwain Sarolangun Terhadap Kepuasan Pengguna Menggunakan Metode Webqual 4.0 Hendri; Merisa; Agus Nugroho
Jurnal Manajemen Teknologi Dan Sistem Informasi (JMS) Vol 5 No 2 (2025): JMS Vol 5 No 2 September 2025
Publisher : LPPM STIKOM Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jms.2025.5.2.2628

Abstract

Dalam era perkembangan teknologi dan informasi yang berkembang pesat seperti saat ini. Hal ini menjadi faktor pendorong penerapan sistem pemerintahan berbasis teknologi. Rumah sakit umum daerah prof. Dr. H. M. Chatib quzwain sarolangun merupakan salah satu pelayanan publik yang memanfaatkan website sebagai media persebaran informasi dan komunikasi, namun berdasarkan 12 angket kuesioner yang telah disebarkan melalui google form ke beberapa pengguna dan didapatkan beberapa masalah pada website seperti informasi yang kurang up to date dan banyak fitur yang tidak dapat diakses untuk mengetahui seberapa besar pengaruh kualitas layanan website terhadap kepuasan pengguna. Maka perlu dilakukan analisis terhadap website RSUD tersebut melalui metode yang digunakan adalah webqual 4.0 yang merupakan metode analisis website berdasarkan persepsi pengguna. Pengumpulan data menggunakan kuesioner berdasarkan skala likert. Populasi pada penelitian ini adalah pengguna website rumah sakit umum daerah prof. Dr. H. M. Chatib quzwain sarolangun dengan jumlah sampel yang digunakan berjumlah 338 orang dari hasil perhitungan yang telah dilakukan, diperoleh nilai t hitung variabel usability quality sebesar 4,636 dibandingkan dengan nilai t hitung variabel information quality sebesar 5,547 dan variabel service interaction quality sebesar 4,389 dengan begitu variabel information quality memiliki pengaruh yang lebih besar dibandingkan usability quality dan service interaction qualitity
Penguatan Literasi Keselamatan Masyarakat pada Perlintasan Sebidang Kereta Api melalui Sharing Session Partisipatif Agus Nugroho; Sonya Sidjabat; Astri Rumondang Banjarnahor; Irwan Chairuddin; Sinung Tri Nugroho
Jurnal Pelayanan dan Pengabdian Masyarakat Indonesia Vol. 5 No. 2 (2026): Juni : Jurnal Pelayanan dan Pengabdian Masyarakat Indonesia
Publisher : Sekolah Tinggi Ilmu Administrasi Yappi Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jppmi.v5i2.2801

Abstract

The community service program entitled “Level Crossings, Transportation Mode Safety, and Contemporary Issues” aims to improve public literacy, compliance, and preparedness in managing risks at intersections between railway tracks and roadways. This program was motivated by the high potential for conflict at level crossings due to differences in the operational characteristics of trains and road vehicles, limited safety facilities, the existence of unauthorized crossings, and risky road-user behavior. The activity was implemented through a participatory-educational approach in an online sharing session involving community members, students, academics, road-user communities, transportation practitioners, and relevant stakeholders. The program included material presentation, interactive discussion, experience sharing, problem identification, and formulation of follow-up recommendations. The results indicate improved participant understanding of railway priority, safe crossing behavior, the importance of signs and markings, and the need for social supervision. The activity also encouraged collective awareness, local leadership potential, and collaborative commitment to developing a safety culture. Recommended actions include continuous safety education, mapping of high-risk locations, stronger coordination, improved safety facilities, and better management of hazardous crossings. Thus, this program serves as an initial step toward community empowerment and a safer, more orderly, participatory, and sustainable transportation safety system.
Analisis Performa Model Random Forest dan Support Vector Regression untuk Prediksi Suhu Maksimum Harian di Kota Jambi R. Zaevan Khazafi Putra; Riza Pahlevi; Ronald Naibaho; Agus Nugroho
Prosiding Seminar Nasional Ilmu Teknik Vol. 2 No. 2 (2025): Desember: Prosiding Seminar Nasional Ilmu Teknik
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/prosemnasproit.v2i2.103

Abstract

The dynamic changes in weather patterns in Jambi City require an accurate temperature prediction system, thus this study aims to compare the performance of Random Forest and Support Vector Regression (SVR) algorithms in predicting daily maximum temperatures using weather data from 2020–2024 obtained from OpenMeteo with the application of Feature Engineering including lag and rolling window features. The test results indicate that the SVR model with a Radial Basis Function (RBF) kernel optimized using Grid Search (C=10, epsilon=0.2, gamma=0.01) significantly outperforms Random Forest based on a statistical Paired T-test (p-value < 0.05), yielding an R-squared (R²) value of 87.46%, Mean Absolute Error (MAE) of 0.3818 °C, and Root Mean Squared Error (RMSE) of 0.4964 °C compared to Random Forest's R² of 84.05%, where the previous day's temperature (lag) and three-day rolling average were identified as the most dominant predictors, leading to the recommendation of SVR as the more effective method for temperature prediction in the study area.