Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

2.826

P-Index

This Author published in this journals

All Journal Infotech Journal UNEJ e-Proceeding NUMERICAL (Jurnal Matematika dan Pendidikan Matematika) Jurnal Teknologi Informasi dan Multimedia International Journal of Economics, Business and Accounting Research (IJEBAR) Journal of Intelligent Decision Support System (IDSS) Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Infokes : Jurnal Ilmiah Rekam Medis dan Informasi Kesehatan Multicience INTELEKTIVA TIERS Information Technology Journal Journal of Dinda : Data Science, Information Technology, and Data Analytics International Journal Software Engineering and Computer Science (IJSECS) Duta.com : Jurnal Ilmiah Teknologi Informasi dan Komunikasi Proceeding of International Conference Health, Science And Technology (ICOHETECH) Prosiding Seminar Nasional Teknologi Informasi dan Bisnis

Sri Sumarlinda

DUTA BANGSA UNIVERSITY SURAKARTA

Author-ID : 7048475

Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary Other

Published : 32 Documents Claim Missing Document

Claim Missing Document

Articles

1 2 3 4

Application Of Mathematical Morphology Algorithm For Image Enhancement Of Breast Cancer Detection Wiji Lestari; Sri Sumarlinda
Proceeding of International Conference on Science, Health, And Technology Proceeding of the 1st International Conference Health, Science And Technology (ICOHETECH)
Publisher : LPPM Universitas Duta Bangsa Surakarta

This study aims to produce an image processing application using Mathematical Morphology to improve the quality of the digital image for breast cancer detection. Medical image is an image produced or used in the medical field. Improving medical image quality is very useful for diagnosis and advanced image processing. Breast healthy is important for women. Breast cancer is the main killer for women. Biomedical breast image data is secondary data. The next process is the initial processing, which is processing that is related to pixel size, gray scale, and so on. The improvement of medical image in this study uses the Mathematical Morphology method which consists of Dilation, Erosion, Opening (Erosion-Dilation) and Closing (Dilation-Erosion) processes. The expected results of this research are medical digital images that have improved their quality as a result of Dilation, Erosion, opening and closing processes.

Clinical Decision Support System in Computational Methods: a Review Study Sri Sumarlinda; AzizahBinti Rahmat; Zalizah Awang Long
Proceeding of International Conference on Science, Health, And Technology Proceeding of the 1st International Conference Health, Science And Technology (ICOHETECH)
Publisher : LPPM Universitas Duta Bangsa Surakarta

Clinical Decision Support Systems (CDSS) are computational models designed impact clinical decision making about individual patients at the point in time that these decision are made. Clinical Decision Support Systems (CDSS) form an important area of research. While traditional systematic literature surveys focus on analyzing literature using arbitrary results, visual surveys allow for the analysis of domains by using complex network-based analytical models. In this paper, we present a detailed visual survey of CDSS literature using important papers selected. The aim of this study is to review a number of articles related to CDSS for heart and stroke diseases. In this study several articles are comparable to the computational methods and rules used for data processing. From the analysis of several sources of literature, the computational methods and rules used in CDSS are Principle Component Analysis (PCA), Support Vector Machine (SVM), Naïve Bayes data mining algorithm, Case Based Recommendation Algorithm, Weighted Fuzzy Rules, Ontology Reasoning, TOPSIS Analysis, Genetic Algorithms, Fuzzy Neural network, Case-based reasoning (CBR), Weighted Fuzzy Rules and Decision Tree.

Clinical Decision Support System for Mapping of Blood Pressure and Heart Rate Sri Sumarlinda; Wiji Lestari
Proceeding of International Conference on Science, Health, And Technology 2021: Proceeding of the 2nd International Conference Health, Science And Technology (ICOHETECH)
Publisher : LPPM Universitas Duta Bangsa Surakarta

Blood pressure has influence on cardiovascular diseases. This study aims to develope clinical decision support system (CDSS) model which non rule based system. The model eas improved using data mining function, especially clustering. K-Means algorithm was used to clustering 120 data and 4 attributes{ age, obesity, sistolic, diastolic and heart rate The clustering process used 500 epoches and 3 cluster. The result of clustering produced 3 cluster. Cluster 1 is higher risk, cluster 2 is medium risk and cluster 3 is normal or lower risk.

Expert System Detecting Symptoms of Game Addiction with The Forward Chaining Method and Certainty Factor Muhammad Mujib Al Khafid; Sri Sumarlinda; Rina Arum Prastyanti
Proceeding of International Conference on Science, Health, And Technology 2021: Proceeding of the 2nd International Conference Health, Science And Technology (ICOHETECH)
Publisher : LPPM Universitas Duta Bangsa Surakarta

Games are fun playing activities. In the past, most children and adolescents played games with physical activities, but nowadays children and adolescents play games with their gadgets. Excessive gaming activity can lead to addiction. Game addiction can cause mental illness, even physical illness. This study aims to help gamers as well as the general public to better understand the symptoms of game addiction and early solutions to game addiction. This study uses forward chaining as a plot, namely by collecting symptoms to find the level of addiction and certainty factors as a calculation by calculating the level of trust and distrust of symptoms. In this study, game addiction resulted in 3 levels, low level game addiction, medium level game addiction and high level game addiction.

ALGORITMA K-MEANS CLUSTERING UNTUK SEGMENTASI PELANGGAN (STUDI KASUS : FASHION VIRAL SOLO) Rifal Bayu Ardi; Faulinda Ely Nastiti; Sri Sumarlinda
INFOTECH journal Vol. 9 No. 1 (2023)
Publisher : Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/infotech.v9i1.5214

Fashion Viral Solo merupakan salah satu distributor perlengkapan fashion di Surakarta yang belum memanfaatkan data yang dimiliki untuk melakukan segmentasi dan mengelompokkan pelanggan berdasarkan kemiripannya. Segmentasi adalah proses untuk mencari tahu karakteristik dari pelanggan berdasarkan kesamaan tertentu, sehingga memudahkan pengumpulan informasi tentang pelanggan yang memberikan profit bagi perusahaan. Segmentasi menjadi salah satu strategi untuk menghadapi persaingan usaha, untuk mempertahankan pelanggan, dan untuk membantu manajemen dalam menyusun strategi promosi untuk meningkatkan penjualan. Tujuan dari penelitian ini adalah melakukan segmentasi pelanggan yang pernah bertransaksi di Fashion Viral Solo berdasarkan karakteristiknya. Pada penelitian ini, peneliti menggunakan algoritma K-Means untuk melakukan clustering dan penerapan metode Recency, Frequency dan Monetary. K-Means adalah algoritma sederhana, mudah diimplementasikan, tidak lambat, mudah disesuaikan, dan sering digunakan dalam proses data mining khususnya clustering. Nilai atribut Recency menunjukkan waktu terakhir transaksi, Frequency menunjukkan jumlah transaksi, dan Monetary menunjukkan total nominal transaksi. Dengan menggunakan K-Means dan metode Recency, Frequency dan Monetary, peneliti dapat melakukan segmentasi pelanggan Fashion Viral Solo. Dari penelitian ini, diperoleh hasil 2 cluster pelanggan. Cluster 1 dengan jumlah anggota terbanyak, yakni 343 pelanggan dan cluster 2 dengan jumlah anggota 8 pelanggan. Untuk menentukan jumlah cluster yang paling optimal, peneliti menggunakan metode Silhouette Scores dan diperoleh hasil jika membagi pelanggan menjadi 2 cluster adalah yang paling optimal.

Perancangan Sistem Pakar Diagnosis Penyakit Flu Kucing Dan Feline Lower Urinary Tract Disease Pada Kucing Ras Persia Menggunakan Metode Certainty Factor Faiz Mu’ammar Hadi; Moh Muhtarom; Sri Sumarlinda
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2023
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Kucing merupakan salah satu hewan yang populer dan disukai di kalangan masyarakat, karena tingkah laku maupun fisiknya yang lucu serta mudah dalam pemeliharaannya menjadi alasan yang membuat banyak orang menyukai untuk memelihara hewan peliharaan ini. Jika tidak diimbangi dengan pengetahuan dalam pemeliharaan dan perawatannya, kucing rentan terhadap suatu penyakit, penyakit yang sering kali terjadi disebabkan oleh virus, parasit, dan bakteri yang berkembang dalam tubuh kucing tanpa sepengetahuan pemilik kucing. Metode certainty factor memiliki kemampuan menentukan tingkat akurasi dan metode ini cocok dalam proses penentuan identifikasi hama dan penyakit, dan hasil dari penerapan metode ini adalah persentase. Dengan adanya sistem pakar diagnosis penyakit flu kucing dan feline lower urinary tract disease pada kucing ras persia diharap dapat membantu untuk mendiagnosis penyakit yang menyerang kucing kesayangannya sedini mungkin serta dapat memberi solusi cara pengobatan dan pencegahannya dengan bantuan dokter hewan. Hasil perhitungan manual yang dilakukan pada penelitian ini sebesar 82.39%.

THE USER SATISFACTION LEVEL OF ELEARNING FOR BUSINESS AND MANAGEMENT SUBJECTS BASED ON TECHNOLOGY ACCEPTANCE MODEL Indra Hastuti; Wijiyanto Wijiyanto; Wiji Lestari; Sri Sumarlinda
International Journal of Economics, Business and Accounting Research (IJEBAR) Vol 3, No 03 (2019): IJEBAR, VOL. 03 ISSUE 03, SEPTEMBER 2019
Publisher : LPPM ITB AAS INDONESIA (d.h STIE AAS Surakarta)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijebar.v3i03.491

Elearning is the implementation of information technology in learning. Elearning was used in courses in Introduction to Business and Management, Business Process Management and Ebusiness. This study aims to use the Technology Acceptance model (TAM) to measure the level of user satisfaction. TAM method is used to determine the relationship between content, accuracy, format, ease of use, timelines, organizational support, user attitudes towards the information system (user attitude towards information). system) and perceived attitude of top management on the level of satisfaction of using e-learning on learning business courses and management at the Faculty of Computer Science, Duta Bangsa University Surakarta. This research is a descriptive study using the modified End User Computing Satisfaction (EUCS) approach method. The results of the evaluation study show that the 5 variables (content), the level of accuracy of the system, format, easy of use, and timeliness significantly influence user satisfaction. While organizational support variables have a significant effect on user satifaction but variable usser attitude toward information system and perceived attitude of top management has an effect but not significant to the support organization. Key words : elearning, user satisfaction, technology acceptance model, end user computing satisfaction.

Marvel Movie Recommendation System Using Hybrid Item-Based and Content-Based Filtering Methods Daffa Rizki Putra Noordi; Herliyani Hasanah; Sri Sumarlinda
TIERS Information Technology Journal Vol. 5 No. 1 (2024)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v5i1.5209

Currently, there are so many movie genres available to the general public, making it difficult for viewers to choose a movie. One of the most popular movies is the “Marvel Movies” or MCU (Marvel Cinematic Universe), which has become the highest grossing franchise of all time with 90 movies released. The large number of movie titles makes it difficult for people to choose which movie to watch. Therefore, a Marvel movie recommendation system is needed using a hybrid item-based and content-based filtering method. The content-based method calculates the similarity between movies by identifying similar Marvel movies based on content such as genre, actor, director, and synopsis. Meanwhile, item-based completes content-based recommendations by considering user preferences. The reason for using the hybrid item-based and content-based filtering method is to be able to produce more accurate recommendations than a single method. The types and sources of data used are secondary data from journals and the internet (Imdb and Movielens), as well as datasets about Marvel movies. From the results of testing the hybrid model, the precision value is 0.8 or 80% which indicates that the model is accurate. In item-based filtering testing, the similarity result of 0.68 shows good item similarity. In the content-based filtering test, the highest similarity is 0.14 and the lowest similarity is 0.10 which shows that the similarity between the searched content and the generated content is relevant.

Development of Sentiment Analysis System of Simple Pol Application on Google Play Store Using Naive Bayes Classifier Method and BERT Prediction Muhammad Dhito Maulidan; Sri Sumarlinda; Sopingi Sopingi
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 4 No 2 (2024): August
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/dinda.v4i2.1577

Digitalization in public services raises various sentiments that are very dynamic, one example is the Simpel Pol Health Test application made by PT Cipta Sari Arsonia (CSA). The research objective is to obtain useful information from accurate community review sentiments for service improvement and feedback for service providers and application developers. The method used is Naïve Bayes Classifier with Tf-idf weighting, Multinomial Naïve Bayes with review value indicators and review sentences predicted by the BERT method as a determinant of sentiment value whether positive or negative. Sentiment towards the application shows quite encouraging results, from 3000 data analyzed with 1772 positive reviews and 263 negative reviews with 80% training data and 20% test data, the naïve bayes classification model is able to provide a high level of accuracy, which is 88.7% with a precision of 88.5%, recall of 100% and f1-score of 93.9%. The data showed that most people gave a positive response to this application, with the dominant word being 'easy'. This system was developed using the local-based streamlit framework and proved to be quite reliable in developing systems for data processing and web-based data analysis even though the scraping process is slightly longer than the google colab service. Future research is expected to be able to predict data that is positive or negative with several parameters and several sentiment analysis methods at once and their comparison.

Sistem Informasi Persediaan Barang dengan Metode Perpetual pada Toko Mebel Sidarta Berbasis Web Rizqi Saputra; Sri Sumarlinda; Wijiyanto Wijiyanto
Jurnal Teknologi Informasi dan Multimedia Vol. 6 No. 2 (2024): August
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v6i2.544

Inventory of goods is an important component in company operations, especially for companies that sell finished goods such as furniture and household electronics. The aim of this research project is to create a goods management website using the Perpetual method at the Sidarta Furniture Store. Previously, this shop used manual recording through physical bookkeeping which was considered inefficient, prone to errors, and could hinder sales. To optimize inventory management, an in-tegrated system is needed. This system development uses the waterfall method, which consists of five stages, namely needs analysis, design, implementation, testing and maintenance. During the requirements analysis step, functional and non-functional system requirements are defined. System design involves developing use case diagrams, database design, and user interface design. The system is implemented using PHP as a programming language, CodeIgniter as a framework, and MySQL for database management. The black box testing method is used to carry out the system testing process, which ensures that all functionality operates according to predetermined speci-fications. The results of the tests carried out show that all system functionality functions in ac-cordance with the designed specifications. System maintenance, which is the final stage of the development cycle, is carried out periodically for the long-term sustainability of system opera-tions. This developed system allows the Sidarta Furniture Store to manage inventory data more efficiently and effectively by utilizing the perpetual method. This system is equipped with various features, including an inventory data management interface, supplier data management interface, purchase transaction recording interface, sales transaction recording interface, and the ability to produce comprehensive inventory recapitulation reports. Implementation of this system facili-tates the process of managing and updating inventory data more efficiently and accurately.

Co-Authors Aditya Prasetyo Wibowo Afu Ichsan Pradana Agustina Srirahayu AzizahBinti Rahmat Bintang Pratama Yuarna Saputra Daffa Rizki Putra Noordi Desi Mandasari Dewangga Ranggi Wiku Faiz Mu’ammar Hadi Faulinda Ely Nastiti Hasanah, Herliyani Indra Hastuti INDRA HASTUTI Intan Oktaviani Joko Endriyanto Moh Muhtarom Muhammad Dhito Maulidan Muhammad Mujib Al Khafid Nafaria Rohmandani Nurmalitasari Nurmalitasari Permatasari, Hanifah Puput Yulianto Rifal Bayu Ardi Rina Arum Prastyanti Rina Arum Prastyantia Rizqi Saputra Robby Gusti Nugroho Sopingi Sopingi Sopingi Wiji Lestari Wiji Lestari Wijiyanto Zalizah Awang Long

Title

Found 32 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 32 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 32 Documents
Search