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Penerapan Faster RCNN + ResNet 50 untuk Mengidentifikasi Spesies dan Stadium Parasit Plasmodium Malaria Prananda, Alifia Revan; Novichasari, Suamanda Ika; Fatkhurrozi, Bagus; Abdillah, Muhammad Nurkholis; Frannita, Eka Legya; Majidah, Zharifa Nur; Wibowo, Fadhila Syahida
TIN: Terapan Informatika Nusantara Vol 6 No 2 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i2.7187

Abstract

Malaria is one of the epidemic health diseases and is well-known as a serious infectious disease. The malaria examination process had occurred by analyzing the digital microscopic images using a microscope. Those examination procedures were conducted manually, which lead to some hurdles such as misinterpretation, misdiagnosis and may produce subjective results. This research aims to develop a method for detecting the Plasmodium parasite and identifying the species and stage of Plasmodium parasite. The proposed method was performed into 488 raw data comprising of 538 parasites. The proposed method was started by conducting a data augmentation process for balancing the number of data, training model, testing model, evaluation. In this study, both the training and testing processes were performed by applying Faster RCNN + ResNet-50. The result of the testing process shows that Faster RCNN + ResNet-50 successfully achieved mAP of 0,603. It also achieved accuracy of 93.91%, sensitivity of 66.20%, specificity of 96.10%, PPV of 60.14% and NPV of 97.30%. This result indicates that the proposed method is powerful for detecting Plasmodium parasites and identifying all species and stadiums.
Pengembangan Intelligent Leather Inspection Method Berbasis Interpretable Artificial Intelligence Frannita, Eka Legya; Wulandari, Dwi; Putri, Naimah; Rahmawati, Atiqa; Prananda, Alifia Revan
TIN: Terapan Informatika Nusantara Vol 6 No 2 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i2.7425

Abstract

The Industry 4.0 revolution, characterized by the widespread adoption of artificial intelligence and automation, has fundamentally transformed quality inspection processes in manufacturing sectors. Nevertheless, the leather tanning industry continues to rely on conventional visual inspection methods conducted by human operators, which are inherently susceptible to subjectivity, inter-operator variability, and inconsistent outcomes. This study proposes an integrated deep learning framework utilizing the NasNet-Large architecture combined with Local Interpretable Model-Agnostic Explanations (LIME) to automate objective defect detection and quality classification of pickled leather. The research employs a digital image dataset comprising four distinct leather grade categories, each annotated with expert-validated ground truth labels and professional interpretations. Experimental results demonstrate consistent model performance with 75% accuracy in both training and validation phases while achieving improved testing accuracy of 79%. LIME-based interpretability analysis reveals significant spatial convergence between model-identified defect regions and expert-annotated ground truth references. These findings indicate that the developed model exhibits remarkable competence in replicating professional leather quality inspection capabilities. The proposed approach not only enhances inspection efficiency by reducing human-dependent errors but also provides transparent decision-making interpretability - a critical requirement for reliable AI implementation in industrial applications. This research contributes to the advancement of explainable AI systems in material quality assessment, offering methodological innovation and practical implementation value for the leather manufacturing sector.
Analisis Kekuatan Material Hasil Teknologi Fused Deposition Modelling Sebagai Material Alternatif Shoelast Oktavian, Dicky; Prihadianto, Braam Delfian; Setyawan, Wawan Budi; Frannita, Eka Legya
Jurnal Sains dan Teknologi (JSIT) Vol. 5 No. 3 (2025): September-Desember
Publisher : CV. Information Technology Training Center - Indonesia (ITTC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jsit.v5i3.3411

Abstract

Pada industri alas kaki penggunaan shoelast merupakan aspek penting dalam proses manufaktur alas kaki. Dalam produksiMass, shoelast materials are generally made of wood, metal, or plastic which requires complex and high-costmanufacturing processes. For limited production needs, prototypes, or custom made materials require quite high costs andlong manufacturing process time. For limited production needs, alternative materials are needed that can be used asshoelast materials. This study aims to analyze the mechanical strength of the material produced by Fused DepositionModelling (FDM) technology as an alternative to shoelast making materials that are more flexible and efficient. The typesof materials used in this study are Polylactic Acid (PLA), Acrylonitrile Butadiene Styrene (ABS), and PolyethyleneTerephthalate Glycol (PETG). The three types of thermoplastic materials were printed with fill density variationparameters using a 3d printer and pressed testing was carried out. The data were analyzed by calculating the average valueand standard deviation of the compressive strength. The results showed that all materials have a compressive strengthhigher than 5 MPa, thus meeting the basic mechanical requirements as a shoelast material. Furthermore, PLA material hasthe characteristics that are suitable for making precise shoelast prototypes, but it is not suitable for repetitive lastingprocesses. While ABS material is more relevant for repetitive lasting processes and PETG material is relevant for limitedproduction but still requires durability
AR-FootIN 4.0 : Aplikasi Pengenalan Teknologi Industri 4.0 Pada Bidang Alas Kaki Berbasis Mobile Augmented Reality Prananda, Alifia Revan; Marwanto, Marwanto; Frannita, Eka Legya; Hidayat, Anwar
TIN: Terapan Informatika Nusantara Vol 4 No 10 (2024): March 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i10.4956

Abstract

Rapid development of technology gave a positive impact on the footwear industry. The emergence of various types of technology as part of the industrial revolution 4.0 has greatly helped various types of work in industry. However, technology also need to be supported by good quality resource. Knowledge regarding how to use and maintain these technologies is needed so that the benefits of these technologies can be utilized. An alternative way is by developing good quality of human resource to being proficient in using technology. Furthermore, cultivating technological literacy is also one of the essential factors. Regarding to this situation, we proposed research that aims to develop the AR-FootIN 4.0 application as a learning media for introducing industry 4.0 in the footwear sector. This learning media is developed by employing mobile augmented reality. The proposed learning media is developed by using the SDLC method. The resulted learning media is then evaluated by conducting two types of evaluation, which are expert evaluation and user evaluation. The results of expert evaluation and user evaluation obtain a percentage of 93.33% and 86% respectively, which means that the feasibility of the application to support the technological literacy process in the footwear industry is very good.
Penerapan Metode CNN (Convolutional Neural Network) untuk Mengklasifikasikan Jenis Cacat pada Kulit Hewan Frannita, Eka Legya; Prananda, Alifia Revan
TIN: Terapan Informatika Nusantara Vol 5 No 2 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i2.5390

Abstract

Recently, leather industry was rapidly growth in several countries. In Indonesia, leather industry became one of the government's priority industries since there were quite a lot of leather industries developing in various regions in Indonesia. On the other hand, there were large number of consumer demand for leather products. Regarding to this fact, maintaining the quality of leather was strongly important. An alternative solution for maintaining leather quality is to conduct leather quality inspection process. However, currently the leather inspection process was still carried out manually by identifying directly the types of defects found on the surface of the leather. This manual inspection process certainly has several hurdles such as time consuming, requiring high accuracy, and requiring experienced operators. This research aimed to develop convolutional neural network architecture that can classify types of leather defects. This research was done by conducting four main processes which were literature study and data collection processes, develop CNN architecture, training process, and testing process. This research work used public dataset consisting of 3600 digital leather images distributed into six classes (folding mask, grain off, growth marks, loose grains, pinhole, non-defective). Based on the training and testing process, the model obtained training accuracy of 90.43% and testing accuracy of 88.47%.
REVITALISASI PRODUK KERAJINAN KULIT MANDING DENGAN PENGAPLIKASIAN ORNAMEN TAMANSARI YOGYAKARTA Hidayahtullah, Mochammad Charis; Frannita, Eka Legya; Utanto, Taufik Rudhi
Dinamika Kerajinan dan Batik: Majalah Ilmiah Vol. 42 No. 1 (2025): DINAMIKA KERAJINAN DAN BATIK : MAJALAH ILMIAH
Publisher : Balai Besar Standardisasi dan Pelayanan Jasa Industri Kerajinan dan Batik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22322/dkb.v42i1.8452

Abstract

UMKM lokal merupakan aspek yang penting untuk meningkatkan perekonomian di Yogyakarta, salah satunya adalah UMKM kerajinan kulit di Desa Manding. Problematika yang dihadapi sekarang ini oleh UMKM Manding adalah kurangnya inovasi pengembangan produk. Tak hanya itu, ornamen Kala Makara Tamansari merupakan ornamen tradisional ikonik dari Yogyakarta yang patut dilestarikan dan diaplikasikan pada produk kulit. Tujuan penelitian ini adalah revitalisasi produk kulit UMKM Manding dan pelestarian tradisi Yogyakarta. Metode penelitian ini menggunakan metode ATUMICS untuk mengembangkan produk UMKM Manding yang lebih ikonik. Hasil dari penelitian didapatkan data bahwa Kala Makara memiliki makna sebagai simbol penolak bala/bencana dan transformasi. Pada revitalisasi produk kulit yang dimodernkan adalah elemen artefak dengan teknik (Technique) produksi menggunakan mesin autocutting, bentuk tas kulit (Shape) dibuat lebih modern dengan ikonisasi (Icon) ornamen Kala Makara. Sedangkan elemen yang tetap sama adalah kegunaan produk tas (Utility), material kulit (Material), serta konsepnya (Concept). Produk revitalisasi ini diharapkan memberikan dampak cultural dan economy motivation untuk UMKM Manding Yogyakarta.