Judul: Application of the Two Step Cluster Method to Identify the Characteristics of Football Games in Asian Countries
Abstrak: Sepak bola termasuk salah satu cabang olahraga yang sangat populer. Tujuan permainan sepak bola adalah memasukkan bola sebanyak-banyaknya ke gawang lawan. Dalam permainan sepak bola, untuk mencapai sebuah kemenangan diperlukan formasi dan taktik yang tepat dengan berbagai pertimbangan salah satunya melihat karakteristik permainan tim lawan. Tim Nasional sepak bola Indonesia perlu mengetahui karakteristik permainan negara-negara di Asia sebagai gambaran atau acuan untuk menentukan taktik agar bisa bersaing di Piala Asia AFC. Berdasarkan data hasil pertandingan Piala Asia AFC 2019, karakteristik permainan sepak bola negara-negara di Asia bisa diidentifikasi dengan menggunakan analisis gerombol. Salah satu metode yang dapat digunakan untuk melakukan analisis gerombol pada data campuran yaitu metode Two Step Cluster. Penelitian ini menerapkan metode Two Step Cluster untuk mengidentifikasi karakteristik negaranegara di Asia berdasarkan data Piala Asia AFC 2019. Analisis Two Step Cluster ini menghasilkan 3 gerombol dengan koefisien Silhouette sebesar 0,3. Masingmasing gerombol memiliki anggota yang berbeda dan memiliki karakteristik tersendiri. Gerombol 1 beranggotakan 5 Tim Nasional dengan mayoritas menggunakan formasi 4-2-3-1. Gerombol ini memiliki karakteristik yang lebih baik dibandingkan gerombol lainnya terutama pada aspek menyerang. Gerombol 2 beranggotakan 11 Tim Nasional dengan mayoritas menggunakan formasi 4-3-3. Gerombol ini memiliki karakteristik yang cukup baik dalam menyerang maupun bertahan. Gerombol 3 beranggotakan 8 Tim Nasional dengan mayoritas menggunakan formasi 5-4-1. Gerombol ini memiliki karakteristik yang kurang baik dalam menyerang dan memiliki rata-rata kemasukan yang tinggi per sekali main., Football is one of the most popular sports. The game of football aims to put as many balls into the opponent’s goal. In the game of football, achieving a victory requires the right formation and tactics with various considerations, one of which is looking at the characteristic of the opposing team’s game. The Indonesian National Football Team needs to know the characteristic of the games of Asian countries as an illustration or reference for determining tactics so they can compete in the AFC Asian Cup. Based on the results of the 2019 AFC Asian Cup match data, the characteristics of Asian countries football games can be identified using cluster analysis. One method that can be used to perform cluster analysis on mixed data is the Two Step Cluster method. This research applied the Two Step Cluster method to identify the characteristics of countries in Asia based on the 2019 AFC Asian Cup data. This Two Step Cluster analysis produces 3 clusters with a Silhouette coefficient of 0,3. Each group has different members and has its characteristics. Cluster 1 consists of 5 National Teams, with the majority using 4-2-3-1 formation. This cluster has better characteristics than other clusters, especially in attack characteristics. Cluster 2 consists of 11 National Teams, with the majority using 4- 3-3 formation. This cluster has quite good characteristics in both attack and defense. Cluster 3 consists of 8 National Teams, with the majority using 5-4-1 formation. This cluster has poor attack characteristics and a high average number of goals conceded per game.
Keyword: AFC Asian Cup, Football, Two Step Cluster

Judul: Optimization of Provincial Clustering Based on Sustainable Development Goals with Hierarchical Clustering, K-Medoids, and DBSCAN
Abstrak: Analisis gerombol merupakan teknik statistika untuk mengidentifikasi gerombol bermakna dari objek data multivariat berdasarkan ukuran kemiripan. Selain memilih ukuran kemiripan, ketepatan dalam menerapkan metode pembentukan gerombol juga menjadi hal fundamental. Karakteristik data dapat memengaruhi performa analisis gerombol. Data multidimensional dengan jumlah dimensi yang besar memiliki tantangan adanya curse of dimensionality. Salah satu cara mengatasi masalah tersebut adalah dengan melakukan reduksi dimensi. Penelitian ini mengevaluasi performa metode reduksi dimensi analisis komponen utama dan t-SNE, serta membandingkan tiga metode penggerombolan yaitu metode hierarki, metode partisi dengan algoritma K-Medoids, dan metode berbasis kepekatan dengan algoritma Density-Based Spatial Clustering of Applications with Noise (DBSCAN) pada data multidimensi, studi kasus penggerombolan provinsi berdasarkan tujuan pembangunan berkelanjutan (TPB). Evaluasi kinerja hasil penggerombolan didasarkan pada tiga indeks validitas. Hasil penelitian menunjukkan bahwa kombinasi t-SNE dengan algoritma hierarki pautan tunggal atau dengan DBSCAN menghasilkan gerombol paling optimal dengan nilai Silhouette tertinggi (0,56), indeks Davies-Bouldin terendah (0,47), dan indeks Calinski-Harabasz tertinggi (75,04) dibandingkan hasil penggerombolan algoritma lainnya. Penggerombolan optimal tersebut menghasilkan tujuh gerombol provinsi dengan karakteristik pencapaian TPB yang berbeda. Terdapat dua gerombol yang menunjukkan pencapaian TPB rendah, sehingga memerlukan perhatian ekstra sesuai dengan karakteristiknya masing-masing. Gerombol-gerombol tersebut terdiri atas provinsi di wilayah timur Indonesia., Cluster analysis is a statistical technique used to identify meaningful clusters from multivariate data objects based on similarity measures. In addition to choosing the right similarity measures, the accuracy in applying clustering methods is also fundamental. The characteristics of the data can influence the performance of cluster analysis. Multidimensional data with many dimensions face the challenge known as the curse of dimensionality. Dimensionality reduction helps address this issue. This study evaluates the performance of two dimensionality reduction methods, principal component analysis and t-SNE, and compares three clustering methods: hierarchical clustering, K-Medoids, and Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The study focuses on clustering provinces based on sustainable development goals (SDGs). Clustering performance is evaluated using three validity indices. Results indicate that combining t-SNE with the single-linkage hierarchical algorithm or DBSCAN produces the most optimal clusters. These methods achieve the highest Silhouette score (0.56), the lowest Davies-Bouldin index (0.47), and the highest Calinski-Harabasz index (75.04) compared to other algorithms. The optimal clustering results in seven distinct clusters of provinces with different SDGs achievement characteristics. Two clusters, comprising provinces in eastern Indonesia, show low SDGs achievement and require extra attention based on their specific characteristics.
Keyword: cluster analysis, DBSCAN, principal component analysis, sustainable development goals, t-SNE

Judul: Optimasi sintesis monolaurin menggunakan katalis enzim lipase imobil pada circulated packed bed reaktor
Abstrak: Monolaurin is a special food grade monogliceride, which has a function beside as emulsifier and food preservative, also has an ability to destroy Herpes and HIV-1 virus. It was reported that monolaurin had the greatest antimicrobial activity among monoglycerides. Novozyme® 435 catalyze the esterification of lauric acid and glycerol in organic solvent. The purpose of this research were : 1) to obtain optimum condition to synthesis monolaurin using Novozyme® 435; 2) to analyze the stability of Novozyme® Continuous circulated packed bed reactor had residence time of 23,57 minute, glycerol/ oil molar ratio of 5:1, solvent/substrate ratio of 8,8:1, and the process produced MAG up to 80%. Optimization of synthesis MAG obtained quadratic equation which was Y= - 61,700 + 6,088 x 435 in continuous system. Continuous Esterification was employed in circulated packed bed reactor. This research was using Response Surface Methods (RSM) as experimental design and temperature and time reaction were as variables. 1+3,259 x2 – 0,065 x12 + 0,017 x1x2 – 1,792 x22 with R2 = 0,5408, optimum temperature and time reaction of 46,92oC and 1,1 hour, respectively. The product yield was 81,09% and contained MAG of 83,15%. The product had acid value of 1,78±0,08 %, peroxide value of 0,49 ± 0,14 meq O2/kg MAG, free glycerol content of 0,26%, and melting point 53-53,5o C. The enzyme remain stable during 10 reaction cycles and up to 70% produced of MAG at each cycle
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