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All Journal JUITA : Jurnal Informatika Jurnal Tekno Kompak Jurnal Pengabdian Literasi Digital Indonesia
Putu Desiana Wulaning Ayu
Institut Teknologi dan Bisnis STIKOM Bali
Computer Science & IT Control & Systems Engineering

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Digitalisasi Logo dan Pelatihan Penggunaan Media Sosial Bisnis Pada UMKM Eka Multi Teknik Made Liandana; Gede Angga Pradipta; Putu Desiana Wulaning Ayu; I Gusti Ngurah Putu Arya Wijaya; Aditya Naray Artamerta; I Kadek Agus Ari Setiawan
Jurnal Pengabdian Literasi Digital Indonesia Vol. 2 No. 1 (2023): June
Publisher : Puslitbang Akademi Relawan TIK Indonesia (ARTIKA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57119/abdimas.v2i1.27

Abstract

Business recognition through social media is very important in the midst of the ever-increasing development of internet users. Through social media, business profiles can be known by users, the more recognized the potential to increase the number of customers will be more open. Eka Multi Teknik is an UMKM engaged in repairing air conditioners, refrigerators, washing machines and other devices. In particular, these UMKM have not introduced their business through digital platforms, besides that the identity logo business is not yet available in digital form, making it difficult to apply it on social media and other digital media. So the solution offered is to make an identity logo in digital form, Instagram social media, and training on using Instagram social media for business. From the results of this activity, the partners were very enthusiastic about participating in the activity, this can be seen from: the participation of partners in providing a place and time for activities, as well as discussions and questions and answers conducted by partners with the service team. Partners have also been able to use Instagram social media for business, this can be seen from the results of content posts that have been made by partners, including how to use Instagram's Insights feature for business
Pendampingan dan Implementasi Aplikasi Bank Sampah Pada TPS-3R Banjar Bonjaka I Made Darma Susila; Made Liandana; Dandy Pramana Hostiadi; Yohanes Priyo Atmojo; Gede Angga Pradipta; Putu Desiana WUlaning Ayu; Abdul Wahab; Muhamad Rihamzah
Jurnal Pengabdian Literasi Digital Indonesia Vol. 2 No. 1 (2023): June
Publisher : Puslitbang Akademi Relawan TIK Indonesia (ARTIKA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57119/abdimas.v2i1.28

Abstract

Garbage is a common problem that needs serious attention. Waste problems can have an impact on public health and environmental health. The local governments and community's form of effort in dealing with waste problems is the formation of TPS-3R by applying the concept of reduce, reuse, and recycle. Implementing the TPS-3R Institution requires proper management with the support of information technology. One of the TPS-3Rs located in the Gianyar – Bali area is TPS-3R Banjar Bonjaka which provides waste processing services for 345 households. The problem encountered during the observation was the manual recording of TPS-3R operational activities. The recording is currently only in the form of a physical book which carries the risk of errors, loss of records, and physical damage. Thus, in carrying out community service activities, it is proposed to provide assistance activities and implement the Garbage Bank application for TPS-3R managers. Community service activities aim to increase the ability to use information technology to manage TPS-3R. Thus, it can help optimize administrative governance. The activity was carried out for one day and attended by 10-15 participants. The evaluation of community service activities shows that participants have been able to input or manage data in the waste bank application. Achievement of abilities is a benchmark for the success of community service activities, with a success percentage of around 80-90%. This activity's benefit is facilitating administrative recording and management of TPS-3R activities by implementing the waste bank application.
Rancang Bangun Sistem Informasi Administrasi Kantor Pada Badan Usaha Milik Desa Studi Kasus Desa Pemecutan Kaja Mandiri Gede Angga Pradipta; Roy Rudolf Huizen; I Made Darma Susila; Dadang Hermawan; Putu Desiana Wulaning Ayu; Dandy Pramana Hostiadi
Jurnal Tekno Kompak Vol 17, No 2 (2023): Agustus
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jtk.v17i2.2332

Abstract

Badan Usaha Milik Desa (BUMDes) dikenal sebagai lembaga yang dikelola oleh masyarakat suatu desa. BUMDes umumnya memiliki banyak kegiatan yang bertujuan untuk menggerakan perekonominan masyarakat dalam suatu desa. Dalam perkembangannya, seringkali administrasi pencatatan kegiatan yang meliputi pencatatan aset, keanggotaan, akuntansi, arsip surat menyurat dan absensi pegawai belum dilakukan secara optimal. Hal ini menyebabkan beberapa teknik pencatatan administrasi menjadi tidak teratur, tidak sesuai, hilang serta pencatatan manual dalam buku sering kali hilang. Maka pencatatan secara komputerisasi atau dalam bentuk digitalisasi administrasi perlu dilakukan dalam kantor BUMDes untuk menertibkan mekanisme pencatatan yang bersifat administratif. BUMDes Pemecutan Kaja Mandiri merupakan salah satu BUMDes yang telah menerapkan pemanfaatan teknologi berbasis komputerisasi. Hal ini di dukung telah dilakukannnya pencatatan dalam dokumen digital, namun masih belum optimal. Pencatatan administrasi belum terkomputerisasi dalam bentuk sistem yang optimal dan bersifat partial. Sehingga memerlukan sebuah aplikasi terintegrasi dalam pemenuhan kebutuhan pencatatan administrasi di kantor BUMDes. Pada penelitian ini, diusulkan sebuah rancang bangun sistem informasi administrasi kantor yang bersifat dinamis dan interaktif berdasarkan kebutuhan pada BUMDes. Rancang bangun terdiri dari proses perancangan alur data, perancangan relasi antar entitas dalam sistem, implementasi dan pengujian sistem. Perancangan alur data dan relasi antar entitas menggunakan metode System Development Life Cycle (SDLC) dengan model waterfall yang terdiri atas analisis kebutuhan, perancangan desain, implementasi dalam bentuk kode pemrogram dan pengujian. Hasil dari rancang bangun adalah sebuah sistem informasi administrasi kantor BUMDes berbasis website. Terdapat 8 fitur utama dalam sistem informasi, yaitu pengelolaan biodata pengguna, dashboard sistem, data pegawai, profil kantor, pendataan surat masuk, pendataan surat keluar, inventaris dan absensi. Pengujian yang digunakan adalah blackbox testing dengan melihat fungsionalitas setiap fungsi dan tombol dalam laman website. Pengujian menunjukkan bahwa seluruh fungsionalitas sistem berjalan sesuai dengan yang diharapkan sengan kelas uji sebanyak 170. Berdasarkan pengujian telah diimplementasikan penginputan data, sistem dapat menampilkan engan baik dan sistem dinyatakan telah bekerja secara optimal.
Voting Scheme Nearest Neighbors by Difference Distance Metrics Measurement Gede Angga Pradipta; Made Liandana; Putu Desiana Wulaning Ayu; Dandy Pramana Hostiadi; Putu Sumardika Eka Putra
JUITA: Jurnal Informatika JUITA Vol. 11 No. 2, November 2023
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v11i2.19298

Abstract

K-Nearest Neighbor (KNN) is a widely used method for both classification and regression cases. This algorithm, known for its simplicity and effectiveness, relies primarily on the Euclidean formula for distance metrics. Therefore, this study aimed to develop a voting model where observations were made using different distance calculation formulas. The nearest neighbors algorithm was divided based on differences in distance measurements, with each resulting model contributing a vote to determine the final class. Consequently, three methods were proposed, namely k-nearest neighbors (KNN), Local Mean-based KNN, and Distance-Weighted neighbor (DWKNN), with an inclusion of a voting scheme. The robustness of these models was tested using umbilical cord data characterized by imbalance and small dataset size. The results showed that the proposed voting model for nearest neighbors consistently improved performance by an average of 1-2% across accuracy, precision, recall, and F1 score when compared to the conventional non-voting method.
Modified of Single Deepest Vertical Detection (SDVD) Algorithm for Amniotic Fluid Volume Classification Putu Desiana Wulaning Ayu; Gede Angga Pradipta; Roy Rudolf Huizen; Kadek Eka Sapta W; I Gede Edy Artana
JUITA: Jurnal Informatika JUITA Vol. 11 No. 2, November 2023
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v11i2.18435

Abstract

Amniotic fluid a crucial role in ensuring the well-being of the fetus during pregnancy and is contained within the amnion cavity, which is surrounded by a membrane. Several studies have shown that volume of amniotic fluid can vary throughout pregnancy and is closely linked to the health and safety of the fetus. This indicates that it is essential to perform accurate measurement and identification of its volume. Obstetric specialist often use a manual method to identify amniotic fluid by visually determining the longest straight vertical line between the upper and lower boundaries. Therefore, this study aims to develop detection model, known as modified Single Deepest Vertical Detection (SDVD) algorithm to automatically measure the longest vertical line by following medical rules and regulations. SDVD algorithm was designed to measure the depth of amniotic fluid vertically by searching the column of pixels that comprised the image sample, excluding any intersection with the fetal body. Performance testing was carried out using 130 images by comparing the manual measurement results obtained by obstetric specialists and the proposed model. Based on the experimental results using modified SDVD, the average accuracy, precision, and recall achieved for amniotic fluid classification were 92.63%, 85.23%, and 95.6%, respectively.
Combining Oversampling and Pretrained Feature Extractor For Classification Diabetic Foot Uclear Thermogram Images I Wayan Jepriana; I Gede Bintang Arya Budaya; Gede Angga Pradipta; Putu Desiana Wulaning Ayu
JUITA: Jurnal Informatika JUITA Vol. 12 No. 2, November 2024
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v12i2.23386

Abstract

Diabetic Foot Ulcers (DFUs) represent a significant health concern, often leading to severe complications if not diagnosed and treated promptly. Early and accurate classification of DFUs is crucial for effective patient management. However, In the realm of machine learning, the imbalanced data problem is a prevalent issue that arises when the classes in a dataset are not represented equally. This study proposes a novel approach to enhance the classification performance of DFU thermogram images by integrating oversampling techniques with pretrained feature extractors. This study use pretrained model method with InceptionV3 architecture to automatically obtain features in the DFU thermogram datasets. Overall, InceptionV3 as a feature extractor resulted in satisfactory performance, achieving an accuracy of 83.1% on non-diabetic data and 81.1% on diabetic data. Subsequently, the second experiment incorporated the oversampling technique SMOTE, leading to an improvement in performance, with accuracy rising to 98.1% on non-diabetic data and 96.1% on diabetic data. Finally, the SMOTE IPF method achieved accuracy of 98.7%, with a precision of 99.1% for the diabetic class and 98.7% for the non-diabetic class, a recall of 98.2% for the diabetic class and 98.1% for the non-diabetic class, and F-Measure of 98.1% for both the diabetic and non-diabetic classes.
Combination of VGG19 (Encoder) and U-Net (Decoder) for Colorectal Polyp Segmentation Image Nuri Sutiyaningsih; Putu Desiana Wulaning Ayu; Roy Rudolf Huizen
JUITA: Jurnal Informatika JUITA Vol. 14 Issue 1, March 2026
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v14i1.25783

Abstract

Health involves the proper function of the body and organs, with colon polyps being a common issue. Doctors often face challenges in segmenting medical images, especially endoscopic images for polyp detection. The complexity and variation in the appearance of polyps make accurate identification challenging, and the subjective manual segmentation process can result in misdiagnosis or delayed treatment.  This study examines the effectiveness of the combination of U-Net decoder model architecture and VGG19 encoder in segmentation of colon polyp images.  This study uses a public dataset, namely Kvasir-Seg with a total of 1000 images of colon polyps.  An innovative approach using VGG19 as encoder and U-Net as decoder improves colorectal polyp segmentation, achieving high performance with a Loss of 0.05, Accuracy 0.95, Precision 0.96, Recall 0.92, IoU 0.89, and Dice 0.94. Using optimal parameters such as Nadam Optimizer, 5 Fold Cross Validation, Learning Rate 0.0001, and 25 Epochs significantly improved performance, increasing the Dice Coefficient to 0.92 and IoU to 0.86 compared to previous studies.   This study concludes that the proposed architecture is reliable for colon polyp segmentation. Future work should explore attention mechanisms or transformer-based models to enhance accuracy and efficiency.
Performance Analysis of Deep Learning Architectures in Classifying Fake and Real Images Arya Faisal Akbar; Putu Desiana Wulaning Ayu; Dandy Pramana Hostiadi
JUITA: Jurnal Informatika JUITA Vol. 13 Issue 2, July 2025
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v13i2.25790

Abstract

The advancements in artificial intelligence (AI) have significantly enhanced image manipulation capabilities, yet they also raise concerns regarding the proliferation of synthetic images. This study investigates the impact of Dynamic Dropout in optimizing deep learning models, including ResNet-101, DenseNet-201, VGG-19, and AlexNet, for classifying real and synthetic images using the CIFAKE and Real and Fake Face datasets. Dynamic Dropout was applied with a progressively increasing rate from 20 percent to 50 percent to enhance training stability and generalization. The results indicate that the optimal configuration consisting of 15 epochs, the Adam optimizer, and Dynamic Dropout consistently outperformed Static Dropout across all models. DenseNet-201 with Dynamic Dropout achieved the highest accuracy of 97.42%, with a precision of 97.33%, recall of 97.58%, and an F1-score of 97.45%. ResNet-101 and VGG-19 exhibited enhanced training stability, while AlexNet proved efficient for lightweight datasets. The Adam optimizer outperformed Nadam, offering greater stability in deeper architectures. Additionally, the 15th epoch was identified as the optimal training duration, balancing accuracy and overfitting mitigation. These findings underscore the importance of selecting optimal training configurations to enhance deep learning performance. Future research should explore adaptive dropout strategies, assess scalability on diverse datasets, and validate these techniques in real-world applications such as digital forensics and AI-generated content detection
Co-Authors Abdul Wahab Aditya Naray Artamerta Arya Faisal Akbar Dadang Hermawan Dandy Pramana Hostiadi Gede Angga Pradipta Gede Angga Pradipta, Gede Angga I Gede Bintang Arya Budaya I Gede Edy Artana I Gusti Ngurah Putu Arya Wijaya I Kadek Agus Ari Setiawan I Made Darma Susila I Wayan Jepriana Kadek Eka Sapta W Made Liandana, Made Muhamad Rihamzah Nuri Sutiyaningsih Putu Sumardika Eka Putra Roy Rudolf Huizen Yohanes Priyo Atmojo