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All Journal Jurnal Teknik Informatika STMIK Antar Bangsa Jurnal Infortech Computer Science (CO-SCIENCE)
Erawati, Wati
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Computer Science & IT Decision Sciences, Operations Research & Management Library & Information Science

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Implementasi Virtual Private Network (VPN) Menggunakan Protokol PPTP Mikrotikrouter pada Yayasan Muhamadiyah Parung Erawati, Wati; Heristian, Sujiliani
Jurnal Teknik Informatika Vol 4 No 1 (2018): JTI Periode Februari 2018
Publisher : LPPM STMIK ANTAR BANGSA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51998/jti.v4i1.185

Abstract

Abstract—In the modern era, many companies and institutions who have made computerized at every routine of office, issues that often occur on a computer network that is sufficiently broad in scope or have a branch to be very disturbing for office, for this in Muhamadiyah Parung Foundation mengrim Indonesia to process files for internal office use flasdisk and free service through email, which for the storage data is not stored properly and also unstructured good view. PPTP (Point to Point Tunneling Protocol) is a computer network that enables secure transfer of data from remote client to private server instances by creating a VPN through TCP / IP.Intisari— Pada era modern sekarang ini banyak perusahaan maupun instansi yang telah melakukan komputerisasi pada setiap rutinitas kantor, permasalahn yang sering terjadi pada jaringan komputer yang cukup luas cakupannya atau memiliki cabang menjadi sangat menggangu untuk aktivitas kantor, selama ini pada Yayasan MUhamadiyah Parung untuk proses mengrim file untuk internal kantor menggunakan flasdisk dan layanan gratis melalui email, dimana untuk penyimpanan datanya tidak tersimpan dengan baik dan juga tidak terstruktur dangan baik. PPTP (Point to Point Tunneling Protocol) merupakan jaringan komputer yang memungkinkan pengamanan transfer data dari remote client ke server pribadi instansi dengan membuat sebuah VPN melalui TCP/IP.Kata Kunci— Point to Point Tunneling Protovol, Virtual Private Network.
Analisis Sentimen Ulasan Pelanggan Menggunakan Algoritma Naive Bayes pada Aplikasi Gojek Heristian, Sujiliani; Napiah, Musriatun; Erawati, Wati
Computer Science (CO-SCIENCE) Vol. 5 No. 1 (2025): Januari 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v5i1.7775

Abstract

Transportation is a means that a person uses to move from one place to another. One mode of transportation that is popular among the public is online motorcycle taxis, such as Gojek. Gojek continues to innovate to meet customer needs more effectively, as well as expand the scope of its services. This research aims to identify the number of positive and negative sentiments in the user review dataset, evaluate the performance of the algorithm used, and measure the level of customer satisfaction with Gojek services. Analysis was carried out on 6,485 customer reviews, which resulted in 4,387 positive sentiments and 2,098 negative sentiments. The classification model used, namely Naive Bayes, shows an accuracy of 88.5%, precision of 88.1%, and recall of 89.0%. The results of this research indicate that the Naive Bayes method provides good performance in analyzing the sentiment of user reviews of Gojek services
Implementasi Algoritma C4.5 Untuk Klasifikasi Tingkat Kenaikan Jabatan Pada PT Siprama Cakrawala Depok Ningsih, Rahayu; Basunanda, Muhammad Devan; Erawati, Wati
Jurnal Infortech Vol 7, No 1 (2025): Juni 2025
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/infortech.v7i1.25469

Abstract

Abstrak  - Dalam era modern, kenaikan jabatan menjadi tantangan bagi perusahaan karena proses promosi yang sering kali dianggap subjektif. Penelitian ini bertujuan untuk membangun model klasifikasi kenaikan jabatan menggunakan Algoritma C4.5 guna meningkatkan objektivitas keputusan promosi karyawan. Data dikumpulkan dari database karyawan PT Siprama Cakrawala serta melalui kuesioner kepada manajer, supervisor, dan karyawan. Variabel yang digunakan mencakup kinerja, pengalaman kerja, tingkat pendidikan, sikap kerja, dan keterlibatan dalam proyek. Data dianalisis menggunakan RapidMiner dengan teknik Decision Tree, kemudian divalidasi menggunakan metode Cross Validation untuk mengukur akurasi model. Hasil penelitian menunjukkan bahwa model yang dihasilkan memiliki tingkat akurasi sebesar 88.91%, dengan classification error sebesar 11.09%. Variabel pengalaman kerja memiliki pengaruh paling dominan dengan nilai information gain tertinggi dan menjadi root node dalam pohon keputusan. Precision model menunjukkan bahwa algoritma C4.5 cukup andal dalam mengklasifikasikan karyawan yang layak dan belum layak mendapatkan promosi jabatan, dengan nilai precision kelayakan sebesar 91.11% dan precision belum layak sebesar 87.50%. Dengan hasil ini, model yang dikembangkan dapat digunakan sebagai alat bantu dalam proses pengambilan keputusan promosi karyawan,
Analisis Sentimen Ulasan Pelanggan Menggunakan Algoritma Naive Bayes pada Aplikasi Gojek Heristian, Sujiliani; Napiah, Musriatun; Erawati, Wati
Computer Science (CO-SCIENCE) Vol. 5 No. 1 (2025): Januari 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v5i1.7775

Abstract

Transportation is a means that a person uses to move from one place to another. One mode of transportation that is popular among the public is online motorcycle taxis, such as Gojek. Gojek continues to innovate to meet customer needs more effectively, as well as expand the scope of its services. This research aims to identify the number of positive and negative sentiments in the user review dataset, evaluate the performance of the algorithm used, and measure the level of customer satisfaction with Gojek services. Analysis was carried out on 6,485 customer reviews, which resulted in 4,387 positive sentiments and 2,098 negative sentiments. The classification model used, namely Naive Bayes, shows an accuracy of 88.5%, precision of 88.1%, and recall of 89.0%. The results of this research indicate that the Naive Bayes method provides good performance in analyzing the sentiment of user reviews of Gojek services
Co-Authors Basunanda, Muhammad Devan Heristian, Sujiliani Musriatun Napiah Rahayu Ningsih