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All Journal Jurnal Manajemen dan Organisasi Jurnal Gaussian Epsilon: Jurnal Matematika Murni dan Terapan IJIBE (International Journal of Islamic Business Ethics) Jurnal Al-Qardh BAREKENG: Jurnal Ilmu Matematika dan Terapan Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Kajian Ilmiah Jurnal Abdimas Ekonomi dan Bisnis TIERS Information Technology Journal Jurnal Pengabdian Ilung (Inovasi Lahan Basah Unggul) VARIANSI: Journal of Statistics and Its Application on Teaching and Research International Journal of Multidisciplinary Sciences and Arts RAGAM: Journal of Statistics and Its Application
Selvi Annisa
Department Of Statistics, Faculty Of Mathematics And Natural Science, Universitas Lambung Mangkurat, Indonesia
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Journal : TIERS Information Technology Journal

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Resampling Techniques in Rainfall Classification of Banjarbaru using Decision Tree Method Selvi Annisa; Yeni Rahkmawati
TIERS Information Technology Journal Vol. 4 No. 2 (2023)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v4i2.5069

Abstract

Continuous heavy rains, such as in 2021, can cause flood emergencies in various areas of Banjarbaru. Therefore, classification modeling is needed to predict rainfall classes based on climate parameters. The problem faced in the classification case is the unbalanced class distribution. Class imbalance occurs when the minority class is much smaller than the majority class. This research aims to compare three resampling techniques in handling imbalanced rainfall data in Banjarbaru using the Decision Tree model. The comparison methods used were sensitivity, specificity, and G-Mean values. In this research, the method used is a decision tree model with Random undersampling, Random Oversampling, and SMOTE. The result shows that the best model is the Decision tree model with the Random Undersampling technique because it provides the highest G-Mean value and sensitivity and specificity values above 70%. Based on this model, the variables that can separate the Rainy and Cloudy classes are Minimum temperature, Maximum temperature, and Sunshine duration, with the best separator being Maximum Temperature.
Clustering Time Series Using Dynamic Time Warping Distance in Provinces in Indonesia Based on Rice Prices Yeni Rahkmawati; Selvi Annisa
TIERS Information Technology Journal Vol. 4 No. 2 (2023)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v4i2.5081

Abstract

Rice is a food commodity that is a basic need for Indonesian people. Since the end of 2022, average rice prices in Indonesia have been increasing, breaking the record for the highest price from August to October 2023. The price of rice in each province in Indonesia is different. This can happen because rice center provinces will distribute their rice production to other regions to meet rice needs. The grouping of provinces in Indonesia based on rice prices over time is an interesting thing to research. The analysis method used to group similar objects into groups for time series data is called clustering time series. The distance that can be used to measure the closeness of two-time series is the Dynamic Time Warping (DTW) distance. The clustering analysis used is the single, complete, average, Ward, and median linkage method. The results of the analysis show that time series clustering in provinces in Indonesia based on rice prices is best using median linkage hierarchical clustering. The median linkage method has a cophenetic correlation coefficient value of 0.899064, meaning that clustering using the DTW distance with the median difference is very good. The resulting clusters contained 3 clusters which had different characteristics between the clusters. There are 2 clusters that can be of concern to the government, because there are clusters that have rice prices that have always been high in the last period and there are provincial clusters that have rice prices that are very diverse or can be said to be unstable.
Co-Authors Adzim, Muhammad Fauzan Al Fajrin, Muhammad Agha Putra Ananda, Saira Aulia Anwaril Hamidy Azizah, Rahma Dina Nur Dewi Anggraini Dewi Anggraini Dewi Sri Susanti Fuad Muhajirin Farid Fuad Muhajirin Farid Genardi, Angelina Ivanna Halisa, Novia Nour Hamda, Tazkiratul Hardianti Hafid Irawan, Siti Fatimah Marliany Jonathan Adi Winata Khairani, Diva Ghefira Mahardika Ma’rifa, Aulia Ma’rifah, Nurul Muhammad Azhar Nabilah, Dwi Anisatun Norhidayati, Annisa Novia Nour Halisa Nur Salam Oktaviani, Viona Perdana, Muhammad Akmal Putri, Dwi Cahyaning Sembiring, Rinawati Sukmawaty, Yuana Suwindi, Akhmad Tanjung, Winda Adinda Utami, Radias Kartika Widawati Annisa Putri Yeni Rahkmawati Yuana Sukmawaty