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Journal : Contemporary Mathematics and Applications (ConMathA)

Determining Optimal Hierarchical Clustering by Combining Needleman Wunsch and Jukes Cantor Algorithms in Tuberculosis (TB) Disease Clustering Hildatul Anizah; Tony Yulianto; Kuzairi; Ira Yudistira; Amalia, Rica
Contemporary Mathematics and Applications (ConMathA) Vol. 7 No. 1 (2025)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v7i1.64172

Abstract

Tuberculosis (TBC) is an infectious disease affecting the respiratory system, caused by the bacterium Mycobacterium tuberculosis. Tuberculosis (TBC) remains a global concern, and to date, no country is completely free from TB. This disease continues to be one of the leading causes of mortality. Therefore, it is essential to categorize the spread of TBC. The percentage of identity in genetic codes will reveal the proportion of mutations. The percentage of identity in genetic codes will demonstrate that, although the symptoms caused by a disease may be quite similar, the protein sequences are not necessarily the same. In this study, the researchers employed the Hierarchical Clustering method, integrating the Needleman-Wunsch and Jukes-Cantor algorithms, resulting in two groups. The first group consists of 9 interconnected rows, while the second group consists of 7 interconnected rows.
Determining Optimal Hierarchical Clustering by Combining Needleman Wunsch and Jukes Cantor Algorithms in Tuberculosis (TB) Disease Clustering Hildatul Anizah; Tony Yulianto; Kuzairi; Ira Yudistira; Amalia, Rica
Contemporary Mathematics and Applications (ConMathA) Vol. 7 No. 1 (2025)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v7i1.64172

Abstract

Tuberculosis (TBC) is an infectious disease affecting the respiratory system, caused by the bacterium Mycobacterium tuberculosis. Tuberculosis (TBC) remains a global concern, and to date, no country is completely free from TB. This disease continues to be one of the leading causes of mortality. Therefore, it is essential to categorize the spread of TBC. The percentage of identity in genetic codes will reveal the proportion of mutations. The percentage of identity in genetic codes will demonstrate that, although the symptoms caused by a disease may be quite similar, the protein sequences are not necessarily the same. In this study, the researchers employed the Hierarchical Clustering method, integrating the Needleman-Wunsch and Jukes-Cantor algorithms, resulting in two groups. The first group consists of 9 interconnected rows, while the second group consists of 7 interconnected rows.
Comparison of Double Exponential Smoothing and Double Moving Average for Forecasting Lost Vehicle Registration Certificates in Pamekasan Ramadani, Nia; Faisol; Kuzairi; Amalia, Rica
Contemporary Mathematics and Applications (ConMathA) Vol. 7 No. 2 (2025)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v7i2.70201

Abstract

The government issues the Vehicle Registration Certificate (STNK), an official document that certifies a motorized vehicle's identity and authenticity. Pamekasan Regency is one of the regencies in East Java Province that frequently suffers losses associated with Vehicle Registration Certificates (STNK). Consequently, it is essential to predict the amount of car registration losses so that the Pamekasan regional administration can use the information to lower the losses. The Double Exponential Smoothing and Double Moving Average techniques were used in this study to forecast the amount of vehicle registration losses. According to the research findings, the smoothing parameters ? = 0.3 and ? = 0.025 had the lowest MAPE value from the Double Exponential Smoothing method, with a MAPE value of 49.4082%. The double moving average method's smallest MAPE, ? = 3, has a MAPE value of 31.53215%. The twofold moving average approach is the best way to forecast the loss of car registration in Pamekasan, according to the comparison's findings.
Dimensi Partisi pada Graf Hasil Operasi Korona Tingkat-k Amalia, Rica; Ummi Nur Yatun Hasanah; Faisol; Tony Yulianto; Kuzairi
Contemporary Mathematics and Applications (ConMathA) Vol. 6 No. 1 (2024)
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/conmatha.v6i1.54748

Abstract

Graph theory is one of the subjects in Discrete Mathematics that have long been known and are widely applied in various fields. The topics that are often discussed in graph theory include labeling, coloring, chromatic numbers, metric dimensions, and partition dimensions. Partition dimensions are obtained by grouping all the vertices on the graph into a number of partition classes, then determine the distance of all vertices to each partition class to get a representation. Partition class which representations have different coordinate vectors is called resolving partition. The minimum cardinality of resolving partition is called partition dimensions of the graph. The purpose of this study is to determine the partition dimensions of level corona operation graphs which are GʘkPm, GʘkCm and GʘkKm, where G, Pm, Cm and Km are connected non trivial graph, path graph, circle graph and complete graph respectively, and any integer k≥1.