The manager or related supervisor performs employee performance assessments to measure the performance and competency of the company's employees. The results of employee assessments can be used to make decisions. Three problems arise in the performance assessment process for PT Tibeta Logistik Indonesia's current employees. The first is that the assessment process is carried out conventionally. So it takes longer, the assessment results can be more objective, and managers or superiors cannot monitor employee performance evaluation results. Based on the literature review, it is known that the Decision Support System is a method that performs assessments more quickly and objectively. Simple Additive Weighting (SAW) is the Decision Support System method for performance assessment. The decision support system will be implemented on a website-based system designed with a prototype model. This research produces a website-based decision support system that can contribute to companies in evaluating employee performance. Before implementation, the decision support system was tested using the User Acceptance Test (UAT) method and obtained very good average results. Then in the comparison between before and after using the system, the results of employee assessments when using the system get superior results in 3 aspects: Integration, security, and ranking. Kata kunci: DSS, Prototipe, SAW, UAT, website.

Breast cancer is a prominent global health concern, as the data from the International Agency for Research on Cancer (IARC) shows that breast cancer is the leading cancer type with new cases in 2020 and among the Top 5 cancer types with the most deaths. To help improve the current breast cancer comorbidity identification by medical personnel and ultimately, lower the number of death cases from breast cancer comorbidity, this research aims to discover the breast cancer comorbidity community, do modularity and similarity-based evaluation, suggest the best semantic similarity measurement and threshold value, and validate the data of breast cancer comorbidities with several data from research papers. The Wang algorithm, with a threshold value of 0.5, is chosen to build the network. Leiden, Louvain, RBER Pots, RB Pots, and Walktrap are the best five community detection algorithms. Similarity measurements with the best three fitness functions (edges inside, scaled density, and size) suggest that the Leiden–Louvain algorithm and RBER Pots-RB Pots algorithm are two pairs of algorithms with similar results. Other similarity measurements with the V-measure heatmap suggest that Louvain–Leiden (0.99), RB Pots–Leiden (0.97), and RB Pots–RBER Pots (0.96) results are similar. Comorbidity is then evaluated using the best five community detection algorithms and four centrality algorithms. As a result, fourteen diseases are agreed upon by the best five community detection algorithms, five diseases are agreed by four algorithms, two diseases are agreed by three algorithms, a disease is agreed by two algorithms, and ten diseases are agreed by an algorithm.

Pertumbuhan Twitter selalu meningkat seiring berjalannya waktu, namun masih banyak kekurangan yang ditemukan, seperti sumber daya manusia yang masih belum berkembang. Metode yang digunakan dalam penelitian ini adalah metode Naïve Bayes Classifier (NBC) untuk dilakukan analisis sentimen. Untuk proses penentuan kalimat opini positif, netral atau negatif diambil dari Twitter. Penentuan ini sebagai proses pengklasifikasian. Dengan menggunakan Aplikasi Python 3.77, langkah awal adalah pengambilan data atau disebut crawling lalu di proses menggunakan Bahasa alami yang biasa disebut Natural Languange Processing (NLP) menggunakan library textblob dilanjutkan tahap preprocessing lalu menghitung Probabilitas kata. Sentimen ini untuk mengklasifikasi data tweet menggunakan library TextBlob sebanyak 100 data menghasilkan 58% positif, 37% netral, dan 4% negatif.

Meningkatnya minat para remaja di Indonesia terhadap fashion brand lokal menjadi sebuah kesempatan untuk membawa industry fashion Indonesia kepasar internasional, hal tersebut memicu keinginan masyarakat untuk menjadi seorang fashion designer. Perkembangan fashion inilah yang membuat banyak para remaja untuk dapat mengekspresikan hobinya, salah satunya yaitu di jalan umum tepatnya di kawasan sudirman, atau lebih sering disebut Citayam Fashion Week (CFW). CFW sangatlah menjadi sebuah fenomena pada pertengahan tahun 2022, tetapi banyak sekali masyarakat memiliki pandangan yang berbeda, ada yang menyikapinya dengan positif, adapula yang malah mengkritik, dari sinilah penelitian ini perlu dilakukan untuk dapat menganalisa sentiment yang ada pada media sosial yaitu twitter, langkah penelitian terbagi menjadi beberapa fase yaitu, pengambilan data, preprocesing, klasifikasi data, dan Kesimpulan serta saran lalu metode yang diimplementasikan yaitu naïve bayes classifier dengan evaluasi menggunakan confusion matrix, dengan hasil akurasi sebesar 84%. Penelitian ini bermanfaat untuk mengekstraksi opini – opini dari media social twitter terkait CFW dengan hasil lebih banyak respon positif terhadap CFW