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Klasifikasi Alexnet dan Deteksi Tepi Canny untuk Identifikasi Citra Repomedunm Dwiza Riana; Daniati Uki Eka Saputri; Sri Hadianti
Jurnal Informasi dan Teknologi 2023, Vol. 5, No. 1
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v5i1.295

Abstract

Deteksi dini kanker serviks dapat mencegah dan menunda kematian, salah satunya dengan memanfaatkan teknologi komputer untuk mendiagnosa berbagai jenis sel kanker serviks. Penelitian dilakukan terhadap citra Pap smear yang diambil dari RepomedUNM dengan tujuan mengklasifikasikan citra Pap smear menjadi dua kelas yaitu sel normal dan sel abnormal dengan menggunakan metode AlexNet. Proses awal klasifikasi citra terdiri dari mengubah ukuran dan mengubah citra asli menjadi skala abu-abu. Penelitian ini juga bertujuan untuk mendeteksi tepi citra pap smear yang terdiri dari dua kelas yaitu sel normal dan sel koilocyt. Deteksi tepi menggunakan metode Canny untuk mendapatkan nilai luas, keliling dan diameter sel sitoplasma dan inti sel (nukleus). Proses deteksi tepi Canny terdiri dari proses cropping, mengubah citra asli menjadi grayscale, dan segmentasi citra menggunakan metode thresholding. Hasil klasifikasi 2000 citra Pap smear menghasilkan akurasi sebesar 97,66% dan hasil deteksi tepi dari 50 citra Pap smear dengan metode Canny mampu memberikan hasil yang baik dengan mendeteksi tepi citra sebenarnya dan hasilnya.
Desain UI/UX Aplikasi D’Laundry Dengan Metode Design Thinking Ridan Nurfalah; Sri Hadianti; Putri Permata Sari; Mohamad Ragil Ramadhan; Winda Astariyah Fatimah
IJCIT (Indonesian Journal on Computer and Information Technology) Vol 9, No 1 (2024): IJCIT Mei 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/ijcit.v9i1.22000

Abstract

Perancangan desain User Unterface (UI) dan er Experience (UX) pada aplikasi D’Laundry dilakukan pada penelitian ini, yang bertujuan untuk memfasilitasi transaksi antara masyarakat dengan toko laundry pakaian terdekat. Metode yang digunakan dalam penelitian ini adalah Design Thinking, yang melibatkan serangkaian tahap dari emphatize, define, ideate, prototype, dan test. Tahap awal penelitian, emphatize, memungkinkan untuk memahami dengan mendalam tantangan yang dihadapi oleh masyarakat, seperti kesulitan dalam mengakses toko laundry dan kurangnya transparansi dalam proses transaksi, termasuk ketidakjelasan tentang kapan pakaian akan selesai dicuci. Tahap define kemudian mengidentifikasi permasalahan utama yang harus diselesaikan melalui desain UI/UX. Dari situ, melalui tahap ideate, berbagai solusi kreatif dihasilkan untuk mengatasi permasalahan-permasalahan tersebut. Desain UI/UX yang dihasilkan kemudian dikembangkan melalui prototype dan diujikan kepada 100 responden sebagai evaluasi akhir dengan pertanyaan kuisioner, yang menghasilkan 93 responden menerima dan terbantu dengan desain UI/UX yang diujikan.hasil penelitian ini dapat diterima dengan baik oleh user yang akan menggunakan aplikasi D’Laundry. Penelitian ini diharapkan memberikan kontribusi penting dalam pengembangan aplikasi D’Laundry yang lebih efektif dan memenuhi kebutuhan masyarakat.  The design of the user interface (UI) and user experience (UX) for the application named D’Laundry was carried out in this research, which aims to facilitate transactions between the public and nearby clothing laundry shops. The method used in this research is Design Thinking, which involves a series of stages from emphatize, define, ideate, prototype, and test. The initial phase of the research, emphatize, enabled researchers to understand in depth the challenges faced by the community, such as difficulties in accessing laundry shops and a lack of transparency in the transaction process, including uncertainty about when clothes will be washed. The define stage then identifies the main problems that must be resolved through UI/UX design. From there, through the ideate stage, various creative solutions are produced to overcome these problems. The resulting UI/UX design was then developed through a prototype and tested on 100 respondents as a final evaluation with questionnaire questionswhich resulted in 93 respondents accepting and being helped by the UI/UX design being tested. The results of this research can be well received by users who will use the D'Laundry application.This research is expected to make an important contribution in developing D’Laundry applications that are more effective and meet community needs.
Combination of Technology Acceptance Model and Decision-making Process to Study Retentive Consumer Behavior on Online Shopping Rudini, Edwin; Riana, Dwiza; Hadianti, Sri
International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) Vol 4 No 1 (2023): INJIISCOM: VOLUME 4, ISSUE 1, JUNE 2023
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injiiscom.v4i1.9414

Abstract

During the spread of the Covid-19 virus, generally the Indonesian people began to switch from conventional markets to buying and selling goods and services online with various features and conveniences offered to users. The purpose of this study is to find out the extent to which indicators of satisfaction and trust influence consumer attitudes and behavior when deciding to make transactions at online shops. The study method uses a combination of TAM (Theory Acceptance Model) and DMP (Decision Making Process) models using a sampling of 110 student respondents and the public who have made transactions in online shops. Data analysis using SEM (Structural Equation Modeling) theory. The results showed that satisfaction and trust will influence consumers in shaping.
Perancangan Website Layanan Administrasi berbasis UI/UX Di RW 013 Cipinang Melayu Jakarta Timur Nurfalah, Ridan; Mayangky, Nissa Almira; Hadianti, Sri; Kusumayudha, Mochammad Rizky
Jurnal Sosial & Abdimas Vol 6 No 1 (2024): Jurnal Sosial & Abdimas
Publisher : LPPM Universitas Adhirajasa Reswara Sanjaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51977/jsa.v6i1.1554

Abstract

Dalam era digitalisasi, peran teknologi informasi menjadi krusial dalam meningkatkan efisiensi administrasi masyarakat. Penelitian ini merupakan hasil kegiatan pengabdian masyarakat yang dilakukan oleh dosen dari Universitas Nusa Mandiri di wilayah RW 013 Cipinang Melayu Jakarta Timur. Fokus utama pada penelitian ini adalah perancangan website layanan administrasi berbasis desain UI-UX yang bertujuan untuk meningkatkan efektivitas pengelolaan administrasi dan keterlibatan masyarakat dalam proses lokal. Metode penelitian yang dilakukan melibatkan partisipasi aktif dosen dan masyarakat setempat dalam proses perancangan website. Analisis data menggunakan pendekatan kualitatif untuk menggali kebutuhan masyarakat dan memastikan bahwa website yang dihasilkan sesuai dengan konteks local. Penelitian ini diharapkan memberikan pandangan yang mendalam tentang perancangan website administrasi di tingkat RW, menggabungkan konsep-konsep UI-UX terkini dan menawarkan solusi inovatif untuk meningkatkan kualitas hidup dan partisipasi masyarakat. Dengan melibatkan dosen dan masyarakat setempat, diharapkan implementasi website ini dapat memberikan dampak positif yang signifikan dalam pengelolaan administrasi lokal di RW 013 Cipinang Melayu Jakarta Timur.
Glaucoma Detection in Fundus Eye Images using Convolutional Neural Network Method with Visual Geometric Group 16 and Residual Network 50 Architecture Nugraha, Chandra; Hadianti, Sri
Journal Medical Informatics Technology Volume 1 No. 2, June 2023
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v1i2.7

Abstract

Glaucoma is an eye disease usually caused by abnormal eye pressure. One of the causes of abnormal eye pressure is blockage of fluid flow, which if detected too late can lead to blindness. Glaucoma can be identified by examining specific areas on the retina fundus image. The aim of this study is to detect positive and negative glaucoma in fundus images. The image data was obtained from the glaucoma_detection dataset, consisting of 520 images, including 134 glaucoma-infected images and 386 normal images. This study uses the Convolutional Neural Network (CNN) method with Visual Geometric Group-16 (VGG-16) and Residual Network-50 (ResNet-50) architectures. The research and testing results using the VGG-16 architecture obtained an accuracy rate of 78%, while using the ResNet-50 architecture obtained an accuracy rate of 80%.
Optimization of The Machine Learning Approach using Optuna in Heart Disease Prediction Hadianti, Sri; Kodri, Wan Ahmad Gazali
Journal Medical Informatics Technology Volume 1 No. 3, September 2023
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v1i3.15

Abstract

Heart disease prediction is a critical area in healthcare, as early identification and accurate assessment of cardiovascular risks can lead to improved patient outcomes. This study explores the application of machine learning techniques for predicting heart disease. Various data attributes, including medical history, clinical measurements, and lifestyle factors, are utilized to develop predictive models. A comprehensive analysis of different machine learning algorithms is conducted to determine their efficacy in classification tasks. The dataset used for experimentation is sourced from a diverse patient population, enhancing the generalizability of the findings. Through rigorous evaluation and validation, the study aims to identify the most suitable machine learning approach for effectively predicting heart disease. The results highlight the potential of machine learning as a valuable tool in assisting healthcare professionals in making informed decisions and providing personalized care to individuals at risk of heart disease
Relevance of e-Health Needs and Usage in Indonesia Chairul, Yasrizal; Aziz, Faruq; Hadianti, Sri
Journal Medical Informatics Technology Volume 1 No. 4, December 2023
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v1i4.20

Abstract

The eHealth application can be used for healthcare, supervision, literature, education, and research. It is a cost-efficient and secure application based on information and communication technology for the health and medical fields. The use of Information and Communication Technology (ICT) as an infrastructure or medium that connects hospitals and health centers using the eHealth electronic health application is the key problem facing the implementation of eHealth on a worldwide scale. eHealth is an ICT-based application for the healthcare industry and one of the Action Plans of the World Summit on the Information Society (WSIS) Geneva 2003. The goal of using the eHealth app is to increase patient access, medical process efficiency, effectiveness, and process quality. This covers the administration of medical services provided by hospitals, clinics, health centers, medical professionals (including therapists and doctors), laboratories, pharmacies, and insurance
Identification of Potato Plant Pests Using the Convolutional Neural Network VGG16 Method Hadianti, Sri; Aziz, Faruq; Nur Sulistyowati, Daning; Riana, Dwiza; Saputra, Ridwan; Kurniawantoro
Journal Medical Informatics Technology Volume 2 No. 2, June 2024
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/medinftech.v2i2.37

Abstract

Pests are one of the main challenges in potato cultivation that can significantly reduce crop yields. Therefore, quick and accurate pest identification is crucial for effective pest control. This research aims to develop a pest identification system for potato plants using the Convolutional Neural Network (CNN) method with the VGG16 architecture. The dataset used consists of images of pests commonly found on potato plants. After the labeling process, these images were used to train the CNN VGG16 model. The research results show that the CNN VGG16 method can identify types of pests with an accuracy rate of 73%. The results serve as a reference to help farmers and agricultural practitioners detect the presence of pests earlier and take the necessary actions to reduce crop losses.
PENYELEKSIAN JURUSAN TERFAVORIT PADA SMK SIRAJUL FALAH DENGAN METODE SAW Nurlela, Siti; Akmaludin, Akmaludin; Hadianti, Sri; Yusuf, Lestari
Jurnal Pilar Nusa Mandiri Vol 15 No 1 (2019): Pilar Nusa Mandiri : Journal of Computing and Information System Periode Maret 2
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1096.159 KB) | DOI: 10.33480/pilar.v15i1.1

Abstract

SMK Sirajul Falah is a Vocational High School located in the Bogor area. However, the selection of the favorite majors in SMK Sirajul Falah is still qualitative so that the process of choosing the favorite majors become not accurate. This is what makes the need for a method that is able to manage the data of the selection of the favorite majors and generate a ranking of the calculation of the weight of the selection of the favorite majors. In the selection of these favorite majors, there is a method of Simple Additive Weighting (SAW) which can be used in quantitative problem-solving. The SAW method is used to compare each criterion with one another, so as to give the results of the favorite majors and provide an assessment of each department at the Sirajul Falah Vocational School.
PREDICTION OF SURVIVAL OF HEART FAILURE PATIENTS USING RANDOM FOREST Rahayu, Sri; Purnama, Jajang Jaya; Pohan, Achmad Baroqah; Nugraha, Fitra Septia; Nurdiani, Siti; Hadianti, Sri
Jurnal Pilar Nusa Mandiri Vol 16 No 2 (2020): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v16i2.1665

Abstract

Human survival, one of the roles that is controlled by the heart, makes the heart need to be guarded and be aware of its damage. Heart failure is the final stage of all heart disease. The medical record tool can measure symptoms, body features, and clinical laboratory test values, which can be used to perform biostatistical analyzes but to highlight patterns and correlations not detected by medical doctors. So technology assistance is needed to do this in order to predict the survival of heart failure patients. With data mining techniques used in the available history data, namely the Heart Failure Clinical Records dataset of 299 instances on 13 features used the Random Forest algorithm, Decision Tree, KNN, Support Vector Machine, Artificial Neural Network and Naïve Bayes with resample and SMOTE sampling techniques. The highest accuracy with the resample sampling technique in the random forest is 94.31% and the SMOTE technique used in the random forest produces an accuracy of 85.82% higher than other algorithms.