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Jurnal Teknik Informatika C.I.T. Medicom
Published by Institute of Computer Science
ISSN : 23378646     EISSN : 2721561X     DOI : -
Core Subject : Science,
Computer Science & IT
The Jurnal Teknik Informatika C.I.T a scientific journal of Decision support sistem , expert system and artificial inteligens which includes scholarly writings on pure research and applied research in the field of information systems and information technology as well as a review-general review of the development of the theory, methods, and related applied sciences.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 5 Documents
 1 
Search results for , issue "Vol 14 No 2 (2022): September: Intelligent Decision Support System (IDSS)" : 5 Documents clear
Decision Support System SIM Card Provider Selection Using the Simple Additive Weighting Method Vanny Fitria Ramadanti
Jurnal Teknik Informatika C.I.T Medicom Vol 14 No 2 (2022): September: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Communication and information media is growing and continues to change over time. For example, in the past, letters were a medium for communicating, then they were replaced with pagers, public telephones, landlines, and now using mobile or cellular phones. Media information providers also continue to experience developments ranging from newspapers, magazines, television, and the internet. However, currently there are tools that can cover both functions, namely smartphones that can be used to communicate as well as access information. To support smoothness and convenience in communicating and accessing information via the internet, a Subscriber Identity Module Card or SIM card or starter pack is required. However, some consumers still find it difficult to determine which SIM card provider to use, even though this is of course very important to consider considering that the selection of this SIM card provider will determine the level of comfort and smoothness of communicating and surfing the internet without having to worry about billing costs and quotas. which is drained. This research was conducted with the aim of knowing which SIM cards are the most widely used today, providing information to users to be more familiar with the various types and brands of SIM cards issued by several providers, determining the best SIM card based on certain criteria to be a recommendation to consumers. users, and provide input to the provider company about what criteria are taken into consideration by users when choosing a SIM card. The study was conducted by using the weighted summation of the Simple Additive Weighting method to determine the best SIM card provider. The final result of the study obtained a value of 0.90 for SIM card provider Tri as a recommendation for the best SIM card provider.
Analysis of Risk Factors for Hypertension at Pustu Petuk Ketimpun Palangka Raya Hendra Budi
Jurnal Teknik Informatika C.I.T Medicom Vol 14 No 2 (2022): September: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Hypertension is an asymptomatic condition, where high blood pressure in the arteries causes an increased risk of cardiovascular-related diseases such as stroke, heart failure, heart attack, kidney damage. The prevalence of hypertension in Central Kalimantan Province in 2018 was 34.5% and in Palangka Raya City was 35.84%. The purpose of this study was to determine the factors associated with hypertension in Pustu Petuk Ketimpun Palangka Raya. This type of research uses a cross sectional design. The population is patients who seek treatment at Pustu Petuk Ketimpun Palangka Raya and the research sample is 218 patients. The sampling technique was chosen by simple random sampling. Data analysis using chi square statistical test. The results showed that age (p-value = 0.0003373), gender (p-value = 0.000002151), excessive sugar consumption (p-value = 0.0001199), excessive salt consumption (p-value = 0, 000001993), alcohol consumption (p-value = 0.01815) and smoking (p-value = 0.03175) are risk factors for hypertension in patients at Pustu Petuk Ketimpun Palangka Raya, Central Kalimantan.
Sentiment Analysis in Valorant Game Review Using Information Gain Rafif Milzam
Jurnal Teknik Informatika C.I.T Medicom Vol 14 No 2 (2022): September: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Video games are one of the entertainments that have developed rapidly compared to other forms of entertainment such as movies or books. because of the rapid development that makes many games need to be reviewed to determine whether they game is worth playing or not. In general, reviews are divided into 2 opinions, namely negative reviews, and positive reviews, but some reviews cannot be included in the positive or negative category by the computer because the review has ambiguous words. Therefore we need a method that can help the computer in determining the category of the review, one of the methods used is the sentiment analysis method. In this study, the authors researched the valorant game review dataset using the information gain method using several classifiers, namely SVM, and Multinomial Naive Bayes and produced the greatest accuracy for the Multinomial Naive Bayes classifier method with an accuracy of 85.90%.
Application of Gray Level Co-Occurrence Matrix and Histogram Feature Extraction Methods for Batik Image Classification Nani Sulistianingsih; Siti Agrippina Alodia Yusuf; Muhamad Irwan
Jurnal Teknik Informatika C.I.T Medicom Vol 14 No 2 (2022): September: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Batik is the art of integrating cultural elements like symbols and techniques into cotton and silk clothes. The Indonesian population has traditionally used batik in their daily lives. Each location has distinctive designs, patterns, and colors that reflect its meanings and philosophical perspectives. There are many different motifs on batik fabric, including geometric, geometrical, animal, and other designs. Batik motifs are frequently employed to convey social rank. The variety of batik designs and motifs is challenging for machine learning-based pattern detection and classification. This research applies the Gray Level Co-occurrence Matrix (GLCM) feature extraction method and Histogram feature extraction on batik images and the K-Nearest Neighbor (KNN) classifier. This study focuses on 4 batik patterns (motifs), namely Lereng, Nitik, Kawung, and Tambal. Dissimilarity, Correlation, Contrast, Homogeneity, and Energy from various angles and distances are the GLCM features employed, and their sum equals 1. Mean, standard deviation, smoothness, skewness, energy, and entropy are the histogram features employed. This work uses 120 batik image data—90 training data and 30 test data—. The findings indicate that at k=15 and k=17, accuracy attained using GLCM feature extraction is 77%, while Precision and Recall are 77%. Comparatively, the histogram feature extraction accuracy, Precision, and Recall are 53%, 54%, and 53%, respectively, with a value of k=27. This outcome demonstrates how feature extraction using GLCM can more accurately portray batik.
Integration of stochastic and robust optimization techniques into DEA model for more accurate and reliable efficiency estimation Hengki Tamando Sihotang; Patricius Michaud Felix; Aisyah Alesha; Joan De Mathew
Jurnal Teknik Informatika C.I.T Medicom Vol 14 No 2 (2022): September: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol14.2022.229.pp1-4

Abstract

Efficiency assessment is vital to assessing decision-making units (DMUs) in numerous sectors. DEA is a prominent non-parametric efficiency assessment tool. Traditional DEA models assume deterministic inputs and outputs, ignoring real-world uncertainties and variability. To improve efficiency estimation, stochastic and robust optimization approaches can be integrated into DEA models. To improve efficiency estimation, we present a stochastic and robust optimization framework incorporating DEA. Probabilistic inputs and outputs allow stochastic optimization to account for uncertainty. The model can capture data variability and create stochastic DMU efficiency scores by adding probability distributions. For data uncertainties and outliers, the DEA model uses robust optimization. Robust optimization considers worst-case scenarios and minimizes extreme observations on efficiency estimation. This makes efficiency scores more resilient to data outliers and noise.  DEA models benefit from stochastic and resilient optimization. First, considering data uncertainties and fluctuations improves DMU efficiency representation. Second, eliminating outliers and extreme observations improves efficiency estimation. Third, efficiency scores help decision-makers make better, more informed choices. A case study in a specific industry shows the framework's efficacy. We compare classic and integrated stochastic-robust DEA model outcomes. The integrated model provides more accurate and dependable efficiency estimates, helping decision-makers understand DMU performance. DEA models with stochastic and resilient optimization increase efficiency estimation. By considering uncertainties and outliers, this paradigm helps decision-makers evaluate DMUs in many sectors more accurately and reliably.

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