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INDONESIA
Jurnal Informatika
Published by Universitas Ahmad Dahlan
ISSN : 19780524     EISSN : 25286374     DOI : 10.26555
Core Subject : Science,
Computer Science & IT
Arjuna Subject : -
Articles 5 Documents
 1 
Search results for , issue "Vol 16, No 1 (2022): January 2022" : 5 Documents clear
Missing Data Imputation using K-Nearest Neighbour for Software Project Effort Prediction Sri Handayaningsih; Ardiansyah Ardiansyah
Jurnal Informatika Vol 16, No 1 (2022): January 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jifo.v16i1.a23494

Abstract

The accurate of software development effort prediction plays an important role to estimate how much effort should be prepared during the works of a software project so that it can be completed on time and budget. Achieving good prediction accuracy is rely on the quality of data set. Unfortunately, missing data is one of big problem regards to the software effort data set, beside imbalance, noisy and irrelevant problem. Low quality of data set would decrease the performance of prediction model. This study aims to investigating the accuracy of software effort prediction with missing data set by using KNN missing data imputation and List Wise Deletion (LWD) techniques. It was continued by applying stepwise regression with backward elimination for feature selection and implementing two effort prediction methods of Multiple Linear Regression (MLR) and Analogy. The result shows that missing data imputation using KNN and listwise deletion with multiple linear regression approach outperforms the Analogy approach significantly (p>0.05).
RANDOM FOREST ALGORITM TO PREDICT LANDSLIDE BASED RAINFALL PARAMETERS A H Pratomo; Wilis Kaswidjanti; E T Paripurno; J D Peasetyo; O Y Siregar
Jurnal Informatika Vol 16, No 1 (2022): January 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jifo.v16i1.a25420

Abstract

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Spatial and topology feature extraction on batik pattern recognition: a review A A Kasim; M Bakri; A Hendra; A Septriani
Jurnal Informatika Vol 16, No 1 (2022): January 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jifo.v16i1.a25415

Abstract

Abstract. Batik is an Indonesian cultural heritage that has been recognized by UNESCO as an international cultural heritage on October 2, 2009. Patterns of batik produce geometric shapes unique, the number and name of the batik patterns make it difficult to recognize each motif. The objective classification of batik is split image into classes according to the pattern motif motive so easy to recognize in accordance with its feature. Batik can be classified based on the shape of the motive, namely geometric motifs, geometric motifs and motifs non specific. Spatial information is an important aspect of image processing such as computer vision and recognition structure / pattern in the context of modelling and resolution of the uncertainty caused by the ambiguity in the low-level features. Shortcomings inherent in combining two colours and spatial features are not adaptive pattern recognition process of the region across multiple images and histogram matching is not appropriate to capture the colours on the image content. This study discussed a model of spatial features and feature combinations topology with the aim to improve the validation batik image pattern recognition so that the level of the pattern recognition motif batik image could be better. Some of the features that have been used include colour features and spatial features. In addition, this paper discusses the possibility of combining the features in pattern recognition. This paper proposes a combination of features that will be able to improve the validation of image pattern recognition of batik.
Forecasting chicken meat and egg in indonesia using ARIMA and SARIMA M D Wisodewo; H A Rosyid; A R Taufani
Jurnal Informatika Vol 16, No 1 (2022): January 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jifo.v16i1.a25416

Abstract

Abstract. Chicken meat and eggs are part of the main commodities in Indonesia. Indonesian people's consumption of chicken meat per capita per year continues to increase. Indonesian government is trying to lure investments to help fund these growing needs. However, inflation has never been positively affected investments. Furthermore, the price of chicken meat and eggs in Indonesia are vulnerable to such a fluctuation. This price hike causes losses to society, due to higher costs, and to the country: inflation affects the future of investment. So, if ones can forecast both commodities, could help decision makers optimizing their policies. This research forecasts the price of chicken meat and egg using the ARIMA and SARIMA methods. Price forecasting is done on chicken meat and egg because they are interrelated, as seen from the Pearson Correlation Test of 0.92 in the datasets and 0.87 in the forecasting results. The selection of the best model is based on the smallest MSE, MAE, and MAPE. The best chicken meat price forecasting results using the ARIMA(3, 1, 2) with MAPE value of 2.31%, while the best chicken egg price forecasting results is the SARIMA[(2, 1, 1)(2, 0, 2, 0), n] with MAPE value of 3.44%.
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) a global pandemic and treatment strategies Atul Sharma; Swapnil Tiwari; Manas Kanti Deb; Jean Louis Marty
Jurnal Informatika Vol 16, No 1 (2022): January 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jifo.v16i1.a25417

Abstract

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