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All Journal JURNAL DERIVAT: JURNAL MATEMATIKA DAN PENDIDIKAN MATEMATIKA Jurnal Teknologi Dharma Bakti Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Jurnal Statistika Industri dan Komputasi
Jatipaningrum, Maria Titah
Jurusan Statistika Institut Sains & Teknologi Akprind Yogyakarta
Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Public Health Social Sciences Other

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Journal : JURNAL DERIVAT: JURNAL MATEMATIKA DAN PENDIDIKAN MATEMATIKA

 1 
Prediksi Kurs Rupiah Terhadap Dolar Dengan FTS-Markov Chain Dan Hidden Markov Model Jatipaningrum, Maria Titah; Suryowati, Kris; Un, Libertania Maria Melania Esti
Jurnal Derivat: Jurnal Matematika dan Pendidikan Matematika Vol 6, No 1 (2019): Jurnal Derivat (Juli 2019)
Publisher : Pendidikan Matematika Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (825.215 KB) | DOI: 10.31316/j.derivat.v6i1.334

Abstract

Hidden Markov model is a development of the Markov chain where the state cannot be observed directly (hidden), but can only be observed, a set of other observations and combination of fuzzy logic and Markov chain to predict Rupiah exchange rate against the Dollar. The exchange rate of purchasing and exchange rate of saling is divided into four states, namely down large, down small, small rise, and large rise are symbolized respectively S1, S2, S3, and S4. Probability of sequences of observation for 3 days later is computed by forwarding and Backward Algorithm, determine the hidden state sequence using the viterbi algorithm and estimate the HMM parameters using the Baum Welch algorithm. The MAPE result exchange rate of purchase of FTS-Markov Chain is 1,355% and the exchange rate of sale of FTS-Markov Chain is 1,317%. The sequences of observation which optimized within exchange rate of  purchase is X* = {S3,S3,S3}, within exchange rate of sale is also X* = {S3,S3,S3}. Keywords: Exchange rate, FTS-Markov Chain, Hidden Markov Model
Pengelompokan Kabupaten Dan Kota Di Provinsi Jawa Timur Berdasarkan Tingkat Kesejahteraan Dengan Metode K-Means Dan Density-Based Spatial Clustering Of Applications With Noise Maria Titah Jatipaningrum; Suci Eka Azhari; Kris Suryowati
Jurnal Derivat: Jurnal Matematika dan Pendidikan Matematika Vol. 9 No. 1 (2022): Jurnal Derivat (Juli 2022)
Publisher : Pendidikan Matematika Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1100.708 KB) | DOI: 10.31316/j.derivat.v9i1.2832

Abstract

East Java Province has an uneven welfare condition. The uneven welfare conditions are indicated by a large number of poor people in East Java and the rate of economic growth which has decreased in 2020, reaching -2.39% due to the impact of the pandemic. Welfare can be measured through several indicators, while the indicators used to classify districts and cities in East Java among others include population density, labor force, labor force participation rate, and open unemployment rate. Thus, to find out the grouping of regencies and cities in East Java Province based on the level of welfare, grouping was carried out using the K-Means and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) methods. For each of the two methods, distance calculations are performed using the Euclidean and Manhattan distances. Each distance was tested for validity using the Davies-Bouldin Index (DBI), C-Index, and Dunn Index. This study concludes that the best method is the DBSCAN method using Manhattan distance with MinPts = 2 and eps = 4 which has the smallest DBI value of 0.284, with 2 clusters formed and 5 noise. Cluster 1 consists of 26 regencies, cluster 2 consists of 7 cities, and noise consist of 5 regencies and cities. Keywords: Welfare, K-Means, DBSCAN, Euclidean Distance, Manhattan Distance.
Co-Authors Alfiah Izat Dwi Sukmawati, Paramita Kartiko Kartiko Kris Suryowati, Kris Rokhana Dwi Bekti Suci Eka Azhari Un, Libertania Maria Melania Esti Yuli Purwanto