Judul: Perbandingan Analisis Sentimen Menggunakan Naive Bayes,  Lexicon-Based, dan Hybrid pada Ulasan Pengguna Aplikasi Livin’ by Mandiri
Abstrak: Perkembangan teknologi mengalami peningkatan yang sangat pesat hampir di seluruh sektor kehidupan manusia, salah satunya peningkatan inovasi perbankan dalam menghadirkan akses layanan transaksi digital. Analisis sentimen digunakan untuk menganalisis serta mengklasifikasikan ulasan pengguna aplikasi yang bertujuan menentukan kebijakan atau evaluasi pada pengembangan aplikasi. Penelitian ini membandingkan performa analisis sentimen berbasis Naive Bayes, Lexicon-based, dan Hybrid dalam mengklasifikasikan sentimen ulasan pengguna aplikasi Livin’ by Mandiri pada Google Play Store. Hasil pada penelitian ini menunjukkan bahwa metode Naive Bayes menghasilkan model dengan performa terbaik dengan nilai akurasi dan macro avg F1-score sebesar 0,96. Model Naive Bayes menggunakan information gain sebagai seleksi kata dan stratified k-fold cross validation sebagai ukuran validasi. Mayoritas ulasan pada rentang waktu yang diamati pada penelitian ini memiliki sentimen positif. Keluhan utama dari pengguna aplikasi Livin’ by mandiri adalah frekuensi pembaruan yang terlalu sering serta memiliki rentang waktu yang berdekatan. Meskipun pada penelitian ini model Hybrid bukan merupakan model terbaik, namun model ini dapat menjadi model alternatif yang mudah dan cepat untuk menganalisis sentimen., Development of technology has advanced very rapidly in almost all sectors of human life, and one of them is the advancement of banking innovation, which provides access to digital transaction services. Sentiment analysis can be used to analyze and classify user reviews of applications, aiming to determine policies or evaluate application development. This study compared the performance of Naive Bayes-based, Lexicon-based, and Hybrid-based sentiment analysis to classify the sentiment of user reviews of the Livin' by Mandiri application on the Google Play Store. The results of this study showed that the Naive Bayes method produced the model with the best performance, achieving an accuracy and macro avg F1-score of 0.96. The Naive Bayes model used information gain as the basis for word selection and stratified k-fold cross validation as a validation measure. The majority of reviews during the study period showed positive sentiments. The main complaint from users of the Livin' by Mandiri application was the frequency of updates, which were considered too frequent and had a short time frame. Although the Hybrid model was not the best in this study, it could serve as an easy and fast alternative for analyzing sentiment.
Keyword: hybrid, lexicon-based, livin' by mandiri, naive bayes, sentiment analysis, analisis sentimen

Judul: Analisis Sentimen terhadap Ulasan Aplikasi BCA mobile pada  Google Play Store
Abstrak: BCA mobile ialah aplikasi yang digunakan oleh pelanggan Bank BCA untuk melakukan transaksi mobile. Sejak Maret 2023 terhitung ada lebih dari 10 juta pengguna yang mengunduh aplikasi ini. Banyak permintaan pengguna untuk meningkatkan kualitas aplikasi pada kolom ulasan aplikasi di Google Play Store. Penelitian bertujuan untuk mengidentifikasi sentimen dari ulasan yang ditulis pengguna untuk aplikasi BCA mobile. Analisis sentimen berguna untuk mengambil informasi subjektif dari teks dokumen. Sentimen pada ulasan akan dikategorikan menjadi sentimen negative, netral dan positif menggunakan algoritma K-Nearest Neighbor (KNN) dan Decision Tree. Ulasan pengguna dari tanggal 1 Januari - 28 Februari 2023 dijadikan sumber data pada penelitian ini. Hasil pemodelan menunjukkan bahwa Decision Tree lebih baik performanya dibandingkan KNN dengan rata-rata F1-score 0.637. Model belum cukup baik untuk mengklasifikasikan ulasan dengan sentimen netral. Penanganan data tidak seimbang tidak terlalu berpengaruh terhadap nilai precision sentimen netral., BCA mobile is an application that used for banking transaction specifically for BCA customers. Per March 2023 BCA mobile is downloaded by more than 10 million users. There is a higher demand for high-quality services due to many users of the application in the Google Play Store's review section. Thus, this study will observe the sentiments of BCA mobile user review on Google Play Store. Data is obtained from the results of scraping user reviews of BCA mobile application. Sentiment analysis is valuable to extract the useful subjective information out of text documents. The sentiment were classified into negative, neutral and positive opinions using K-Nearest Neighbor (KNN) and Decision Tree algorithm. The reviews from 1 January – 28 February 2023 will used for this study. The result showed that Decision Tree produces more good model with 0.637 average F1-score. Model is not good enough to classify reviews with neutral sentiment. Handling unbalanced data did not have much effect on precision value of neutral sentiment.
Keyword: bca mobile, Decision Tree, KNN, sentiment

Judul: Characterizations of low alloy steel sae 4422  plated with chromic acid (Cro3)
Abstrak: Characterizations of low alloy steel SAE 4422 plated with chromic acid (CrOrO3) was use Optical Microscopy (OM), Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD), RD),Energy Dispersive Analysis of X-Ray (EDAX), Hardness Test and Roughness Test. Microstructures analysis exhibits cracks and grain boundaries microcracks as a characteristics of chrome metal found at plating metal. Perlite and Ferrite as grains of steel found at base metal with grain boundaries around it. Phase analysis of plating metal appropriate to chrome metal with lattice constant (a) is 2.559 Å and phase analysis of base metal appropriate to iron ferrite with lattice constant (a) is 3.318 Å. Both plating and base metal have cubic system. Chemical analysis of plating metal at surface section exhibits that cracks area have highest value of carbon element compare with grains and grains boundaries area. While chemical analysis of base metal at cross section exhibits that perlite have highest value of carbon element compare with ferrite and grain boundaries. The hardness value of plating metal at surface section and cross section are 753 and 637 VHN. While, the hardness value of base metal and interface area at cross section are 205 and 373 VHN. The roughness value at measurement points of chrome surface for as received sample are 0.445 μm. Observation used Optical Microscopy and Scanning Electron Microscopy exhibits surface irregularities combine to form surface texture of plating metal at surface section.
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