Perkembangan aplikasi e-commerce mengalami kemajuan pesat dalam beberapa tahun terakhir. Aplikasi e-commerce memberikan pengalaman belanja yang lebih mudah, nyaman, dan personal bagi pengguna. Fitur-fitur seperti pencarian produk yang efisien, ulasan pelanggan, rekomendasi produk dan keamanan pembayaran. Shopee adalah salah satu platform ecommerce yang populer di Indonesia dan memberikan pengguna akses yang mudah untuk berbelanja secara online dengan berbagai pilihan produk dan penawaran menarik. Tujuan penelitian ini untuk mengetahui analisis sentimen pengguna aplikasi Shopee berdasarkan data ulasan yang di dapat dari situs website google play menggunakan metode Naive Bayes Classifier dan K-Nearest Neighbour (K-NN) untuk mengklasifikasikan ulasan berdasarkan komentar sentimen positif, sentimen negatif dan sentiment netral. Hasil penelitian dengan menerapkan metode Naive Bayes Classifier di dapat nilai akurasi sebesar 75.97%, dengan prediksi komentar positif sebesar 742, komentar negative 519 dan komentar netral sebesar 86. Dan metode K-Nearest Neighbor nilai akurasi sebesar 16.69%, dengan prediksi komentar positif sebesar 154, komentar negative 80 dan komentar netral sebesar 62. Analisis Sentimen aplikasi shopee berdasarkan komentar pengguna google play store menunjukkan tingkat kepuasan konsumen baik di lihat dari besarnya nilai respon komentar positif berdasarkan hasil perhitungan machine learning yang sudah dilakukan.
The phenomenon of technological development can transform systems in various sectors to provide efficiency and convenience at a lower cost, including the financial sector. Flip is a financial service application that makes it easy to transfer money between banks without administrative fees. By the end of 2021, the Flip will have a 4.9 rating on the Google Play Store. The purpose of this study was to analyze user sentiment towards the Flip app to see if flip user ratings were as positive as the ratings received. This study uses a set of text mining processes on the user rating data of the Flip app on the Google Play Store, using the classification algorithm K-Nearest Neighbor with TF-IDF weighting. The results show that 77.67% of the test data are correctly classified as positive evaluation classes, with high accuracy and recall rates of 82.67% and 86.92%, respectively. In addition, from the results of applying the Flip user rating data classification method, the comparison between training data and test data is 80%:20%, and the classification accuracy using the K-Nearest Neighbor algorithm is 76.68%. User reviews of the Flip app have shown positive results, as well as the ratings obtained in the Google Play Store and the K-Nearest Neighbor algorithm, TF-IDF weighting process used to analyze user sentiment towards the Flip app.
New student data Information systems can be used as a supporting tool to support decisions. Janabadra University is one of the universities in Yogyakarta, the information system for recording transactional data for students is still done simply in the form of text and numbers. The purpose of this research is to design and build a dashboard application for data visualization of prospective students at Janabadra University for new student admissions (PMB). The method used is a business intelligence roadmap with six stages, the stages are (1) justification, (2) planning, (3) business case, (4) design, (5) construction, and (6) deployment which is a reference in the design and construction of a data warehouse using Metabase. The results of this study can build 7 (seven) visualization dashboards are (1) Dashboard of information students grouped based on the total number of PMB registrants, (2) Dashboard of the number of registrants based on the academic year, (3) Dashboard of income from PMB registration based on the payment date, (4) Dashboard of the number of students based on the academic year of each study program, (5) Dashboard of the number of registrants by class, (6) Dashboard of the number of PMB registrants by semester and (7) Dashboard of the number of PMB registrants by study program and class.
<p><strong><em>Abstract.</em></strong> <em>The chili plant is an agricultural commodity that has the highest attractiveness in Indonesia. This is a challenge for farmers to cultivate chili. Sanggrahan Kidul Hamlet is a hamlet located in Bendungan Village, Wates District, Kulon Progo Regency, Special Region of Yogyakarta. One-third of the Sanggrahan Kidul Hamlet area is agricultural land, so most of the residents of Sanggrahan Kidul work as farmers. In order to control, repel, attract, or eradicate pests in their crops, farmers need pesticides. The many kinds and types of pesticides circulating in the market and the various advantages offered by pesticide products to farmers make farmers have to be careful and careful in choosing the right pesticides. The specific purpose of this activity is to educate the farmers of Dusun Sanggrahan Kidul regarding the criteria for selecting the right pesticide product by designing a system for determining the selection of pesticides for chili plants. Based on the results of the analysis of the community service program, it can be concluded that technically the application of decision support for the selection of pesticides on chili plants is categorized as suitable for use by users with a percentage value of 78%. Meanwhile, in terms of benefits, the chili farmers in Sanggrahan Kidul Hamlet are greatly helped by the existence of educational activities with this pesticide selection support system. Farmers can choose suitable pesticides according to the desired criteria.</em></p><p> </p><p><strong>Abstrak.</strong> Tanaman cabai merupakan suatu komoditas pertanian yang mempunyai daya tarik paling tinggi di Indoneisa. Hal ini menjadi tantangan tersendiri bagi petani untuk melakukan budidaya cabai. Dusun Sanggrahan Kidul merupakan dusun yang berada di Desa Bendungan, Kecamatan Wates, Kabupaten Kulon Progo, Daerah Istimewa Yogyakarta. Sepertiga wilayah Dusun Sanggrahan Kidul adalah lahan pertanian, sehingga sebagian warga Sanggrahan Kidul berprofesi sebagai petani. Guna mengendalikan, menolak, memikat, atau membasmi organisme penggangu pada hasil panen, petani memerlukan pestisida. Banyaknya macam dan jenis pestisida yang beredar di pasaran dan beragamnya keunggulan-keunggulan yang ditawarkan produk pestisida kepada petani membuat para petani harus teliti dan cermat dalam memilih pestisida yang tepat. Tujuan khusus dari kegiatan ini adalah mengedukasi para petani Dusun Sanggrahan Kidul mengenai kriteria pemilihan produk pestisida yang tepat dengan merancang sistem penentuan pemilihan pestisida untuk tanaman cabai. Berdasarkan hasil analisa program pengabdian masyarakat tentang dapat disimpulkan bahwa secara teknis aplikasi pendukung keputusan pemilihan pestisida pada tanaman cabe dikategorikan layak di gunakan oleh user dengan nilai persentase 78%. Sedangkan dari segi manfaat, para petani cabai Dusun Sanggrahan Kidul sangat terbantu dengan adanya kegiatan edukasi dengan sistem pendukung pemilihan pestisida ini. Para petani dapat memilih pestisida yang cocok sesuai dengan kriteria yang diinginkan.</p><p> </p>
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