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Journal : Mathematics and Applications (MAp) Journal

APPLICATION OF FUZZY PRINCIPAL COMPONENT ANALYSIS FOR THE BEST ALTERNATIVE TOURIST ATTRACTION IN YOGYAKARTA Aditya Rizq Herlandy Karjawan; Muhammad Muhajir
MAp (Mathematics and Applications) Journal Vol 5, No 1 (2023)
Publisher : Universitas Islam Negeri Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/map.v5i1.6046

Abstract

One of the regions in Indonesia that depends on the tourism sector is the Special Region of Yogyakarta Province. The Province of the Special Region of Yogyakarta itself every year becomes a tourist destination province for vacations, many tourists do not know which places are the best choices for tourists. Therefore, this research aims to make it easier for tourists to obtain information on the best tourist spots in the Province of the Special Region of Yogyakarta. Based on the data obtained from the results of distributing online questionnaires during June 2022 – July 2022. The results of the study using the Fuzzy Principal Component Analysis method, it was found that the best tourist attraction is the Prambanan Temple tourist attraction with a PCA score of 0.677057 which means that Prambanan Temple becomes a tourist attraction. The most sought after by tourist visitors, followed by the Malioboro Street Area with a PCA score of 0.48146 and Parangtirtis Beach with a PCA score of 0.369162. The results of this study are expected to help tourists determine
COMPARISON OF ACCURACY BETWEEN NEURAL NETWORK AND REGRESSION MODELS IN FORECASTING Hermansah Hermansah; Muhammad Muhajir
MAp (Mathematics and Applications) Journal Vol 5, No 1 (2023)
Publisher : Universitas Islam Negeri Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/map.v5i1.5949

Abstract

This research discusses the forecasting of the median value of owner occupied homes (MEDV) using all the other continuous variables available in the Boston dataset. The Boston dataset is a collection of data about housing values in the suburbs of Boston. The used method is Feed Forward Neural Network (FFNN) and the multiple linear regression method as a comparison. The result of the research indicates that the FFNN method is better than multiple linear regression in forecasting the median value of owner occupied homes (MEDV) using all the other continuous variables available in the Boston dataset. It is proven that the MSE and MAPE value of using the FFNN method is 15.7518 and 0.14563, whereas the value of multiple linear regression is 31.2630 and 0.21040. Based on this result, the research can be concluded that the FFNN method has the smaller MSE value, the result of the forecasting is more accurate.
PENGELOMPOKAN STUNTING MENGGUNAKAN METODE K-MEDOIDS DI DAERAH ISTIMEWA YOGYAKARTA (DIY) Cahyani, Amalia Rizki; Muhajir, Muhammad; Puspita, Ersa Riga; Pratiwi, Lathifah Aliya
MAp (Mathematics and Applications) Journal Vol 6, No 1 (2024)
Publisher : Universitas Islam Negeri Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/map.v6i1.8523

Abstract

Stunting, or the condition of short stature in toddlers, is a problem caused by prolonged insufficient nutrition intake. This issue arises from inadequate feeding practices that do not meet the nutritional needs of a toddler. Stunting can begin during fetal development and becomes apparent around the age of two. Several factors contribute to stunting, including high-risk levels, lack of adequate housing, lack of proper sanitation facilities, lack of access to safe drinking water, and inadequate family income. This study employs k-medoids cluster analysis to identify the grouping of sub-districts in the Yogyakarta Special Region (DIY Province) based on stunting risk factors. The research findings indicate that Cluster 1 has the highest rates of stunting and lack of family income, Cluster 4 has the highest instances of inadequate access to safe drinking water and housing, and Cluster 5 has the highest rates of inadequate sanitation facilities.