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All Journal Jurnal Informatika Indonesian Journal on Software Engineering (IJSE) Jurnal Teknik Komputer AMIK BSI Jurnal Khatulistiwa Informatika Jurnal Pilar Nusa Mandiri Jurnal Teknik Informatika STMIK Antar Bangsa JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jurnal Infortech Abditeknika - Jurnal Pengabdian Kepada Masyarakat Computer Science (CO-SCIENCE) IMTechno: Journal of Industrial Management and Technology Conten : Computer and Network Technology Info Abdi Cendekia AnoaTIK: Jurnal Teknologi Informasi dan Komputer Jurnal Komputer Antartika
Wahyudin Wahyudin
[Scopus id: 57220178626] Universitas Bina Sarana Informatika
Religion Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Health Professions Industrial & Manufacturing Engineering Library & Information Science Social Sciences

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Journal : Jurnal Komputer Antartika

 1 
Analisis Sentimen Pada Ulasan Aplikasi Home Credit Dengan Metode SVM dan K-NN Arman Adiansyah; Wahyudin
Jurnal Komputer Antartika Vol. 1 No. 4 (2023): Desember 2023
Publisher : Antartika Media Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Dalam era teknologi, mencari pembiayaan finansial semakin mudah melalui aplikasi mobile seperti Home Credit. Aplikasi ini telah diunduh oleh lebih dari 10 juta pengguna Android dengan peringkat keseluruhan 4,4 di Google Play Store. Untuk membantu meninjau aplikasi, pengguna dapat memberikan ulasan dan penilaian di Google Play Store. Namun, dengan banyaknya ulasan, diperlukan analisis sentimen untuk mempermudah pemaha man. Dalam penelitian ini, dilakukan analisis sentimen menggunakan metode Support Vector Machine (SVM) dan K-Nearest Neighbor (KNN) pada data ulasan dari Google Play Store. Data yang diambil berjumlah 2.845 dengan informasi tentang skor dan komentar. Sentimen positif dan negatif ditentukan berdasarkan skor, dengan skor 4 dan 5 untuk sentimen positif, serta skor 1, 2, dan 3 untuk sentimen negatif. Setelah tahap preprocessing dan penghitungan tf-idf, dilakukan perhitungan menggunakan algoritma SVM dan KNN. Hasilnya menunjukkan bahwa metode SVM memiliki presisi 89%, recall 86%, F1-score 87%, dan akurasi 88%. Sementara metode KNN memiliki presisi 79%, recall 80%, F1-score 79%, dan akurasi 79%. Berdasarkan hasil tersebut, dapat disimpulkan bahwa metode Support Vector Machine lebih baik dalam melakukan analisis sentimen dalam penelitian ini.   In the age of technology, finding finance has never been easier through mobile apps like Home Credit. The app has been downloaded by over 10 million Android users with an overall rating of 4.4 on the Google Play Store. To help review the app, users can leave reviews and ratings on the Google Play Store. However, with so many reviews, sentiment analysis is needed to facilitate understanding. In this study, sentiment analysis using the Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) methods was conducted on review data from the Google Play Store. The data taken amounted to 2,845 with information about scores and comments. Positive and negative sentiments are determined based on scores, with scores of 4 and 5 for positive sentiments, and scores of 1, 2, and 3 for negative sentiments. After the preprocessing stage and tf-idf calculation, calculations are performed using the SVM and KNN algorithms. The results show that the SVM method has 89% precision, 86% recall, 87% F1-score, and 88% accuracy. While the KNN method has 79% precision, 80% recall, 79% F1-score, and 79% accuracy. Based on these results, it can be concluded that the Support Vector Machine method is better at performing sentiment analysis in this study.
Analisis Kualitas Layanan Website SILADU Terhadap Kepuasan Pengguna Dengan Metode Webqual 4.0 Ramadhani, Putri Kurnia; Wahyudin, Wahyudin
Jurnal Komputer Antartika Vol. 2 No. 1 (2024): Maret 2024
Publisher : Antartika Media Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70052/jka.v2i1.62

Abstract

SILADU (Sistem Layanan dan Pengaduan) merupakan salah satu website pelayanan yang digunakan untuk dapat melakukan pelayanan kepada masyarakat yang digunakan oleh Pusdatin Kesos. SILADU digunakan untuk pengecekkan data bantuan sosial yangmana bantuan tersebut disalurkan oleh pemerintah kepada masyarakat DKI Jakarta salah satunya di wilayah Kelurahan Duri Kosambi. Berdasarkan hal tersebut maka dilakukan penelitian dengan menggunakan teknik webqual 4.0 yang terdiri dari 3 dimensi yaitu kualitas kegunaan, kualitas informasi, kualitas layanan interaksi untuk mengukur kualitas layanan website siladu.jakarta.go.id yang mana dilihat dari segi kepuasan pengguna. Data didapatkan dengan menyebarkan kuesioner yang dibagikan kepada warga Kelurahan Duri Kosambi dengan kritera usia 15-54 tahun dengan jumlah sampel 100 orang dan menggunakan teknik purposive sampling. Data diolah menggunakan SPSS Statistic 26. Didatpkan hasil dari uji simultan (uji f) ketiga dimensi Webqual 4.0 berpengaruh secara simultan terhadap kepuasan pengguna dengan fhitung sebesar 22,949 dan ftabel 2,699. Maka dapat disimpulkan penelitian ini berpengaruh terhadap user satisfaction (kepuasan pengguna).   SILADU (Service and Complaints System) is one of the service websites used to provide services to the community which is used by the Social Welfare Data and Data Center. SILADU is used to check data on social assistance which is distributed by the government to the people of DKI Jakarta, one of which is in the Duri Kosambi sub-district area. Based on this, research was conducted using the webqual 4.0 technique which consists of 3 dimensions, namely usability quality, information quality, interaction service quality to measure the service quality of the siladu.jakarta.go.id website which is seen in terms of user satisfaction. Data was obtained by distributing questionnaires which were distributed to residents of Duri Kosambi Village with criteria aged 15-54 years with a sample size of 100 people and using a purposive sampling technique. The data was processed using SPSS Statistics 26. It was found that the results of the simultaneous test (f test) of the three dimensions of Webqual 4.0 had a simultaneous effect on user satisfaction with an fcount of 22.949 and a ftable of 2.699. So it can be concluded that this research has an effect on user satisfaction.
Co-Authors Abdul Aziz Agus Junaidi Agustiani, Sarifah Ahmad Yani Ahmad Yani Andi Saryoko Arivion, Pelagia Arman Adiansyah Cahyaning, Narish Fahlepi Roma Doni Ferry Kristiyanto Hardiyan Hardiyan Heri Kuswara Irfansyah Irfansyah Lia Nurmalia Maruloh Maruloh Mochamad Nandi Susila Mochammad Iqbal Rifa’i Muhammad Darussalam Muhammad Rifqi Adli Noer Azni Septiani, Noer Azni Nur Ali Farabi Prawikas, Amanda Rachmat Hidayat Rahmat Hidayat Ramadhani, Putri Kurnia Resti Resti Santoso Setiawan Sinta Bela Sopiyan Dalis Syamsul Bahri Syamsul Bahri Syarif Hidayatulloh Titik Misriati Umi Kulsum