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All Journal Journal of Computer Networks, Architecture and High Performance Computing Jurnal Algoritma Proceeding of International Conference Health, Science And Technology (ICOHETECH) Equivalent : Journal of Economic, Accounting and Management
Harsanto
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Health Professions Industrial & Manufacturing Engineering Medicine & Pharmacology

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Strategi Optimasi Kinerja Teknologi Informasi Dalam Pengembangan Produk Baru pada Persaingan Pasar Dinamis Harsanto; Afu Ichsan Pradana
Equivalent : Journal of Economic, Accounting and Management Vol. 3 No. 2 (2025): Equivalent : Journal of Economic, Accounting and Management
Publisher : CV. Doki Course and Training

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61994/equivalent.v3i2.1196

Abstract

Abstract : The residential property construction industry in Indonesia faces dynamic challenges that demand strategic management of Information Technology (IT) performance. Limited resources and knowledge remain the main obstacles to IT optimization. This causal-comparative study examines the roles of IT performance optimization strategy, dynamic capability in new product development (NPD), functional competence, and market turbulence in achieving competitive advantage of new products. Analysis using Structural Equation Modeling (SEM) with a Partial Least Squares (PLS) approach reveals that dynamic capability and functional competence in NPD have a significant positive effect on competitive advantage, while IT optimization strategy and market turbulence show only weak positive effects. These findings emphasize the importance of strengthening internal competencies to develop adaptive business strategies in dynamic markets. Abstrak : Industri konstruksi properti residensial di Indonesia menghadapi tantangan dinamis yang menuntut strategi pengelolaan kinerja Teknologi Informasi (TI). Keterbatasan sumber daya dan pengetahuan menjadi kendala utama dalam optimasi TI. Penelitian kausal komparatif ini menguji peran strategi optimasi TI, kemampuan dinamis pengembangan produk baru (PPB), kompetensi fungsional, dan turbulensi pasar terhadap keunggulan kompetitif produk baru. Analisis menggunakan Structural Equation Modeling (SEM) berbasis Partial Least Squares (PLS) menunjukkan bahwa kemampuan dinamis PPB dan kompetensi fungsional berpengaruh signifikan terhadap keunggulan kompetitif, sementara strategi optimasi TI dan turbulensi pasar hanya memberikan pengaruh positif lemah. Hasil ini menegaskan pentingnya penguatan kompetensi internal untuk membangun strategi bisnis yang adaptif di pasar yang dinamis.
Intelligent Surveillance for Mask Regulation in Healthcare Using the YOLOv11 Algorithm Pradana, Afu Ichsan; Harsanto; Aboobaider, Burhanuddin Bin Mohd; Harsanto, Malika
Proceeding of the International Conference Health, Science And Technology (ICOHETECH) 2025: Proceeding of the 6th International Conference Health, Science And Technology (ICOHETECH)
Publisher : LPPM Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47701/23mc9656

Abstract

The use of face masks in healthcare settings is a crucial measure in preventing the spread of infectious diseases, particularly since the outbreak of the COVID-19 pandemic. However, public compliance with mask-wearing remains a challenge despite the implementation of various regulations. This study aims to design and develop an automatic mask-wearing detection system by leveraging the YOLOv11 algorithm, which is renowned for its superior speed and accuracy in object detection. The methodology involved collecting a dataset of facial images with and without masks, data labeling, model training using YOLOv11, and evaluating the system's performance in real-world conditions. Test results demonstrate that the system can perform real-time mask detection with a mean Average Precision (mAP) of 0.9, establishing it as an effective solution for supporting health protocol monitoring in medical facilities. Consequently, this system not only enhances monitoring efficiency but also has the potential to minimize the risk of infection spread through an intelligent technological approach.
Hybrid Decision Tree Method and C4.5 Algorithm for a Recommendation System in Determining Recipients of Direct Cash Assistance (BLT) Bhactiar , Rio Rizq Nur; Hartanti, Dwi; Harsanto
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 2 (2023): Article Research Volume 5 Issue 2, July 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i2.2414

Abstract

Development of a recommendation system to determine recipients of Direct Cash Assistance (BLT) using the C4.5 algorithm hybrid method and decision tree. In the current era of digitalization, the BLT program is a solution for the Indonesian government to help people affected by the COVID-19 pandemic. In this study, we propose a recommendation system that combines the C4.5 algorithm and a decision tree to increase accuracy and efficiency in determining BLT beneficiaries. Primary data was obtained through interviews and observations, while secondary data was obtained from the village administration, written reports, journals, theses and previous research. The results showed that the C4.5 algorithm and decision tree hybrid method gave good performance in determining BLT recipients. The C4.5 algorithm is used to calculate the accuracy of the training data and testing data with a ratio of 80% : 20%, while the decision tree is used to create a decision tree that classifies prospective BLT recipients. This research fills in the previous research gap regarding the recommendation system for determining BLT beneficiaries. The results of this study are expected to provide useful information for the government in making decisions regarding the BLT program, especially at the village or sub-district level. With an accurate and efficient recommendation system, financial assistance can be provided to those who really need it, helping to meet the basic daily needs of affected communities.
Optimalisasi Akurasi Model Identifikasi Penyakit Pada Daun Padi Dengan Fine-Tuning YOLOv11 Untuk Ketahanan Pangan Berkelanjutan Harsanto; Pradana, Afu Ichsan; Wahyu Pamekas, Bondan
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2945

Abstract

Rice is one of Indonesia's main food commodities, whose productivity often declines due to leaf disease. Early detection of rice leaf disease is an important aspect of maintaining sustainable food security. This study aims to optimize the accuracy of early identification of rice leaf disease by fine-tuning the YOLOv11 model. The research stages included dataset collection, annotation, data preprocessing, data augmentation, model training, fine-tuning, and model performance evaluation. The results showed an improvement in model performance after fine-tuning, with the overall recall value increasing from 0.760 to 0.788 and mAP from 0.764 to 0.785. The confusion matrix also shows a more stable prediction distribution in the fine-tuned model compared to the initial model. Thus, fine-tuning YOLOv11 has proven to be effective in improving the accuracy of early identification of rice leaf diseases and has the potential to support the application of artificial intelligence in the agricultural sector to strengthen food security in Indonesia.
Co-Authors Aboobaider, Burhanuddin bin Mohd Afu Ichsan Pradana Bhactiar , Rio Rizq Nur Dwi Hartanti Harsanto, Malika Pradana, Afu Ichsan Wahyu Pamekas, Bondan