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Wahyudin Wahyudin
Universitas Bina Sarana Informatika
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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.
SISTEM PENDUKUNG KEPUTUSAN PEMILAHAN KARYAWAN TETAP MENGGUNAKAN METODE AHP DAN TOPSIS Arivion, Pelagia; Wahyudin
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 1 No 2 (2023): Desember 2023
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v1i2.7

Abstract

Karyawan merupakan motor penggerak agar proses bisnis dalam sebuah perusahan dapat berjalan dengan lancar. Dalam meningkatkan kualitas dan kompetensi karyawan salah satu upaya yang dilakukan adalah pengangkatan karyawan menjadi karyawan tetap untuk menciptakan sumber daya manusia yang baru.Seleksi pengangkatan karyawan tetap pada PT. Pana Indo Alkestama seringkali terjadi kekeliruan, salah satunya adalah pemilihan tenaga kerja yang masih tidak obyektif atau masih tergantung atasannya. Berdasarkan hal tersebut, perlu Sistem Pendukung Keputusan (SPK). solusi hal tersebut yaitu menerapkan metode pengambilan keputusan yaitu AHP dan TOPSIS. Data yang diperoleh dalam penelitian ini diperoleh dari kuesioner yang dibagikan kepada responden diantaranya: manager HRD, Staf HRD, dan Administrasi. Kemudian data tersebut diolah menggunakan Microsoft Excel.Hasil pada metode AHP dan TOPSIS dengan alternatif terpilih sama yaitu Bapak Syaiful. Dapat diketahui bahwa metode AHP dan TOPSIS relevan untuk pemilihan karyawan tetap di PT Pana Indo Alkestama.
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.
SELECTION OF EXTRACURRICULAR ACTIVITIES IN SMK INSAN AQILAH 4 JAKARTA USING PROFILE MATCHING METHOD Wahyudin, Wahyudin; Saryoko, Andi; Aziz, Abdul; Nurmalia, Lia
Jurnal Pilar Nusa Mandiri Vol 16 No 1 (2020): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (798.516 KB) | DOI: 10.33480/pilar.v16i1.913

Abstract

This research is based on the observations and experiences of researchers, because the many extracurricular activities in schools make it difficult for students to determine extracurricular activities that can develop their personality, talents, and abilities outside the academic field, therefore the system is created to select extracurricular activities. The aim is to help students deal with extracurricular selection problems. The application of the Profile Matching method in the decision support system for the selection of extracurricular activities is expected to help provide recommendations for extracurricular activities to overcome the problem of selecting extracurricular activities and can facilitate students in selecting extracurricular activities.
Metode Vulnerability Assesment Dalam Pengujian Kinerja Sistem Keamanan Website Points of Sales Wahyudin, Wahyudin; Kuswara, Heri; Resti, Resti; Dalis, Sopiyan
Computer Science (CO-SCIENCE) Vol. 4 No. 1 (2024): Januari 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v4i1.2978

Abstract

The development of electronic commerce through point of sales based websites is closely related to the growth rate of the internet, because electronic commerce runs through networks and Internet connections. However, the more point of sale based websites that are built, the greater the possibility of cyber attacks that could harm the website. Therefore, website security is very important to pay attention to. One method that can be used to maintain website security is to carry out a Vulnerability Assessment. Vulnerability Assessment is a process of searching for security gaps in an information system or computer network with the aim of identifying potential security vulnerabilities and taking preventative steps before an attack occurs. The vulnerability assessment technique used is using a weakness scanner application to identify security gaps in systems and applications such as Nikto, Nmap, Zenmap and Owasp ZAP. Based on testing with the Owasp ZAP tool, the results of scanning carried out on the sakupos.com website, which is a points of sales based website, show that there is a vulnerability on the website. The test results show the Level of Vulnerability (Risk Assessment) as well as recommended solutions that can be used to prevent it. There were 10 vulnerabilities detected, 7 vulnerabilities were found with a Medium risk level, 2 vulnerabilities with a Low risk level, and 1 other vulnerabilities at the Informational risk level.
Co-Authors Abdul Aziz Agus Junaidi Ahmad Yani Andi Saryoko Arivion, Pelagia Arman Adiansyah Cahyaning, Narish Fahlepi Roma Doni Hardiyan Hardiyan Heri Kuswara Lia Nurmalia Maruloh Maruloh Mochamad Nandi Susila Mochammad Iqbal Rifa’i Muhammad Darussalam Noer Azni Septiani, Noer Azni Nur Ali Farabi Rachmat Hidayat Ramadhani, Putri Kurnia Resti Resti Sinta Bela Sopiyan Dalis Syamsul Bahri Umi Kulsum