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All Journal AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Andrianto, Fiki
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Social Sciences

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Linear Kernel Optimization of Support Vector Machine Algorithm on Online Marketplace Sentiment Analysis Andrianto, Fiki; Fadlil, Abdul; Riadi, Imam
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 21, No 1 (2024): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v21i1.9266

Abstract

Twitter is a short message platform commonly used as a means of news information, commentary, and social interaction. One of the utilization of twitter is to analyze the sentiment of the online marketplace which can be used to determine the service, quality of goods, and delivery of goods on a product, service or application. This research aims to categorize the reviews or responses of the Indonesian people, especially to the online marketplace using the linear Support Vector Machine (SVM) algorithm. In order to make continuous improvements to the role of the Indonesian online marketplace in the future, sentiment analysis is needed. The analysis research tweets used were 4165 datasets using the python programming language. Sentiment analysis research stages include data collection, preprocessing, labeling, tf-idf weighting, split data, SVM model analysis and result evaluation. The data is then divided into 80% training data and 20% testing data, 50% training data and 50% testing data, 20% training data and 80% testing data. The results of the svm algorithm testing scenario obtained the highest optimization with an accuracy value of 97%, F1-score value on positive labels 88% and negative 98%, also obtained a positive recall value of 80% and negative 100% precision value on positive labels 98% and negative 97%, on 80% training data and 20% testing. It can be concluded that in this case, the linear svm algorithm is able to work to recognize models with a high level of accuracy so that in the future it can be used in similar cases.
Penggunaan Teknologi Tools Powerpoint dan Canva untuk Media Informasi Riadi, Imam; Fadlil, Abdul; Andrianto, Fiki; Elvina, Ade; Fanani, Galih; Nasution, Dewi Sahara
Aksiologiya: Jurnal Pengabdian Kepada Masyarakat Vol 6 No 2 (2022): Mei
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/aks.v6i2.11781

Abstract

Program pemberdayaan masyarakat ini bertujuan untuk menggunakan media Power Point dan Canva sebagai media penyampaian informasi yang inovatif dan meningkatkan soft skill desain. Pelatihan ini diikuti 15 mahasiswa baru program studi Sistem Informasi STIMIK Muhammadiyah Jakarta. Program ini melakukan 2 sesi pertemuan online melalui Zoom Meating karena Universitas mempraktikkan home learning, ada kebijakan tersebut terkait wabah Covid19. Pertemuan pertama memberikan materi tentang perkembangan teknologi dan media informasi sebagai tambahan wawasan. Pertemuan kedua memberikan tutorial tentang cara menggunakan Power Point dan tools Canva untuk mendesain informasi, yaitu desain sertifikat, desain undangan, desain animasi PPT, dan konten digital lainnya. Hasil tes pretest dan postest menunjukkan bahwa nilai presentase mahasiswa baru meningkat sebesar 13%. Hasil ini mengindikasikan adanya sedikit peningkatan dalam pengetahuan wawasan dan soft skill tentang teknologi media informasi. 
Co-Authors Abdul Fadlil Elvina, Ade Fanani, Galih Imam Riadi Nasution, Dewi Sahara