Judul: Penerapan Model Regresi Logistik Biner dan Random Forest terhadap Prospek Atlet Muda pada Liga Basket DBL Tahun 2019
Abstrak: Prestasi olahraga merupakan suatu tolak ukur kesuksesan pembinaan suatu cabang olahraga. Hal tersebut dapat terwujud dengan sistem yang sah dan profesional seperti liga basket untuk kalangan pelajar. Kompetisi yang bagus akan mendukung perkembangan prospek atlet. Prospek atlet merupakan kemungkinan yang berdampak di masa mendatang akibat usaha yang dilakukan masa sekarang. Menurut Pedoman Program Indonesia Emas (PRIMA) yang ditetapkan oleh Komite Olahraga Nasional Indonesia ada 2015, atlet pratama merupakan kelompok untuk pembinaan tingkat nasional atau regional. Pemodelan klasifikasi prospek atlet berdasarkan sumber data statistik pertandingan Liga Basket DBL Tahun 2019 menggunakan metode regresi logistik biner dan random forest dengan penerapan teknik penanganan data tidak seimbang dan teknik validasi. Hasil penelitian ini menunjukkan bahwa semua model yang dibentuk memberikan kinerja yang baik serta dapat dikatakan bahwa peubah point yang merepresentasikan kemampuan mencetak angka dan assist yang merepresentasikan kemampuan olah bola merupakan peubah berpengaruh yang konsisten dalam memprediksi prospek atlet muda., Sports achievement is a measure of the success of coaching a sport. This can be realized with a legal and professional system such as a basketball league for students. Good competition will support the development of athlete prospects. The athlete's prospect is a possibility that will have an impact in the future due to the efforts made in the present. According to the Indonesia Gold Program Guidelines (PRIMA) established by the Indonesian National Sports Committee in 2015, pratama athletes are a group for national or regional level coaching. Modeling the classification of athlete prospects based on statistical data sources for the 2019 DBL Basketball League matches using binary logistic regression and random forest methods with the application of unbalanced data handling techniques and validation techniques. The results of this study indicate that all the models formed provide good performance and it can be said that the point variable which represents the ability to score points and assists which represents the ability to play the ball is a consistent influential variable in predicting the prospects of young athletes.
Keyword: basket, model, prospek, random forest, regresi logistik biner

Judul: Indonesian Basketball League 2022 Players Clustering Using K-Means and K-Medoid with t-SNE Dimensionality Reduction
Abstrak: Basket modern telah berkembang menjadi olahraga “position-less”. Posisi dan peran pemain tidak lagi ditentukan berdasarkan kriteria antropometri, melainkan karakteristik dan skill set yang dibuktikan oleh catatan statistik di lapangan. Perbedaan karakteristik dan skill set dapat diketahui dengan menggerombolkan pemain berdasarkan antropometri dan statistik pertandingan. Analisis gerombol tradisional, cenderung menghasilkan hasil kurang optimal jika diterapkan langsung pada data berdimensi tinggi karena adanya “curse of dimensionality”. Permasalahan tersebut dapat diatasi dengan reduksi dimensi. Penelitian ini bertujuan menggerombolkan pemain Indonesian Basketball League (IBL) 2022, berdasarkan antropometri dan statistik pertandingan menggunakan k-means dan k-medoid dengan reduksi dimensi t-SNE, serta menentukan metode penggerombolan terbaik. Metode penggerombolan terbaik ditentukan berdasarkan parameter optimal yang dievaluasi menggunakan koefisien Silhouette dan indeks S_Dbw. Berdasarkan hasil evaluasi, metode k-medoid pada t-SNE perplexity = 2 menghasilkan nilai evaluasi optimal, namun kedua hasil evaluasi menghasilkan banyak gerombol (k) optimal berbeda. Berdasarkan Silhouette, k-medoid pada t-SNE perplexity = 2 optimal pada k = 9, sedangkan berdasarkan indeks S_Dbw, k-medoid pada t-SNE perplexity = 2 optimal pada k = 10. Penentuan gerombol terbaik dilakukan secara eksploratif dengan radar chart dan Chernoff faces guna melihat perbedaan hasil optimal. Hasil penggerombolan terbaik yang diperoleh adalah k-medoid pada t-SNE perplexity = 2 dengan 10 gerombol optimal., Modern basketball has evolved into a “position-less” sport. Player positions and roles are no longer determined by anthropometric criteria, but rather based on their characteristics and skill sets, as indicated by statistical field performance. Grouping players based on anthropometry and match statistics allows for the identification of differences in their characteristics and skill sets. Traditional cluster analysis tends to produce less-optimal results when applied directly to high dimensional data because of the "curse of dimensionality". This issue can be addressed through dimensionality reduction techniques. This study aims to cluster Indonesian Basketball League (IBL) 2022 players, based on anthropometry and match statistics using k-means and k-medoid with t-SNE dimensionality reduction, and determine the best clustering method. The best clustering method is determined by evaluating the optimal parameters using Silhouette coefficient and S_Dbw index. Based on the evaluation results, the k-medoid with t-SNE perplexity = 2 yields optimal evaluation values, however the two evaluations indicate different optimal cluster sizes (k). Based on the Silhouette coefficient, k-medoid at t-SNE perplexity = 2 is optimal at k = 9, while based on the S_Dbw index, k-medoid at t-SNE perplexity = 2 is optimal at k = 10. To compare the optimal results, the determination of the best cluster is further explored using radar charts and the Chernoff faces. The best clustering results were obtained using the k-medoid with t-SNE perplexity = 2 and k = 10.
Keyword: chernoff faces, IBL 2022 match statistics, k-means, k-medoid, t-SNE

Judul: Karakteristik Carboxymethyl Chitosan Dengan Variasi Konsentrasi NaOH
Abstrak: Carboxymethyl chitosan is chitosan derivative product obtained from chemical modification. CMCh were made by alkalization process and carboxymethylation process. Factors that affect CMCh characteristics were excess sodium hydroxide in alkalization process, ratio between chitosan and monochloroacetic acid, and carboxymethylation temperature. The objectives of this research were to study the NaOH effect to CMCh characteristics, to learn process of making CMCh, to set the proper concentration of NaOH, and to analyze CMCh characteristics. CMCh yields were 110.72%-114.22%. CMCh pH value were 3.74-4.31. The optimum NaOH concentration to obtain the best CHCh was 10 M. Percentage of CMCh moisture content was 10.70%-11.42%. Ash content and nitrogen content of CMCh were 0.49%-0.50% and 4.52%-4.81%. CMCh viscousity was 8.25 cps. Percentage of CMCh solubility was 61.61%-91.50%. The different functional groups from chitosan which observed in CMCh were C=O group, CH group from alkene functional group, C−O group, and C−O−C group.
Keyword: solubility., functional group, CMCh characteristics, chitosan, carboxymethyl chitosan