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Journal : Journal of Computation Science And Artificial Intelligence

IMPLEMENTASI JARINGAN VPN METODE L2TP SEBAGAI JARINGAN PENUNJANG PEKERJA LAPANGAN PT ALBANY CORONA LESTARI CABANG CIREBON Apan Apriyadi; Faisal Akbar; Mukidin
Journal of Computation Science and Artificial Intelligence (JCSAI) Vol. 2 No. 1 (2025): Journal of Computation Science And Artificial Intelligence (JSCAI)
Publisher : PT. Berkah Digital Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58468/sws42642

Abstract

PT Albany Corona Lestari merupakan anak perusahaan dari PT Indomarco Prismatama yang berfokus pada support toko Indomaret dalam hal kelistrikan, jaringan, perangkat keras, dan pelatihan karyawan toko. PT Albany Corona Lestari memiliki pekerja di kantor dan lapangan. Dalam bekerja, pekerja lapangan berpatokan pada website Complaint Online untuk memeriksa daftar komplain yang masuk, dan ESS (Employe Self Service) untuk absen, input izin, dan cuti. Permasalahan dalam akses ke website Complain Online dan ESS menjadi penghambat dalam bekerja, karena website hanya tersedia dalam jaringan lokal kantor dan jaringan lokal toko Indomaret, sehingga tidak dapat diakses melalui jaringan publik (internet). Masalah tersebut dapat diatasi dengan menggunakan VPN (Virtual Private Network) agar perangkat pekerja lapangan seperti laptop dan smartphone dapat mengaksesjaringan lokal kantor dan membuka website Complaint Online dan ESS (Employe Self Service) dari mana saja dan kapan saja. VPN yang digunakan pada penelitian ini adalah L2TP (Layer 2 Tunneling Protocol) dengan ditambah IPSec (Internet Protocol Security) sebagai keamanan tambahan. Jaringan VPN L2TP yang telah terpasang dianalisa dengan parameter Quality of Service (Qos) untuk menilai Throuhput, Delay, Jitter, dan Packet Loss. Hasil dari penelitian ini adalah koneksi VPN yang stabil dan aman serta mendapatkan nilai Quality of Service yang baik. ABSTRACT PT Albany Corona Lestari is a subsidiary of PT Indomarco Prismatama which focuses on Indomaret store support in terms of electricity, network, hardware, and store employees. PT Albany Corona Lestari has workers in the office and field. In working, field workers rely on the Complaint Online website to check the list of incoming complaints, and ESS (Employe Self Service) for absences, input permits, and leave. Problems in accessing the Complain Online and ESS websites are an obstacle in working, because the website is only available in the local office network and the local Indomaret store network, so it cannot be accessed via the public network (internet). This problem can be overcome by using a VPN (Virtual Private Network) so that field worker devices such as laptops and smartphones can access the local office network and open the Complaint Online and ESS (Employe Self Service) websites from anywhere and anytime. The VPN used in this study is L2TP (Layer 2 Tunneling Protocol) with the addition of IPSec (Internet Protocol Security) as additional security. The installed L2TP VPN network is analyzed with Quality of Service (Qos) parameters to assess Throuhput, Delay, Jitter, and Packet Loss. The results of this study are a stable and secure VPN connection and get a good Quality of Service value.
IMPLEMENTASI METODE CASE-BASED REASONING UNTUK MENGETAHUI JENIS  GANGGUAN INDIHOME PADA PELANGGAN TELKOM WITEL CIREBON Ade Suryadi; Faisal Akbar; Sergi Roseli; Badrudin Hadibrata
Journal of Computation Science and Artificial Intelligence (JCSAI) Vol. 2 No. 2 (2025): Journal of Computation Science and Artificial Intelligence (JCSAI)
Publisher : PT. Berkah Digital Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58468/jcsai.v2i2.22

Abstract

Gangguan layanan IndiHome sering terjadi dan memerlukan penanganan cepat. Namun, keterbatasan akses langsung ke teknisi menyebabkan pelanggan mengalami keterlambatan dalam mendapatkan solusi. Sistem pakar berbasis Case-Based Reasoning (CBR) dapat menjadi solusi untuk membantu pelanggan mengidentifikasi jenis gangguan secara mandiri. Penelitian ini bertujuan membangun sistem pakar diagnosis gangguan IndiHome menggunakan metode CBR yang mampu merekomendasikan solusi berdasarkan kemiripan kasus sebelumnya.  Sistem dirancang menggunakan pendekatan CBR dengan empat tahapan utama: Retrieve, Reuse, Revise, dan Retain. Penghitungan kemiripan (similarity) dilakukan menggunakan metrik Jaccard Coefficient, dengan bobot atribut berdasarkan kepentingan gejala. Sistem diimplementasikan berbasis web menggunakan PHP dan MySQL. Validasi dilakukan melalui pengujian terhadap 50 kasus gangguan nyata dari Witel Cirebon.  Hasil pengujian menunjukkan sistem mampu mengidentifikasi jenis gangguan dengan akurasi rata-rata 86%. Kasus dengan nilai similarity tertinggi digunakan sebagai dasar rekomendasi solusi, seperti pemeriksaan kabel fiber, restart modem, atau kontak ke 147. Sistem pakar berbasis CBR terbukti efektif sebagai alat bantu diagnosis awal gangguan IndiHome, memberikan solusi cepat dan akurat bagi pelanggan, serta mengurangi beban layanan pelanggan. Abstract IndiHome service disruptions frequently occur and require prompt handling. However, limited direct access to technicians causes customers to experience delays in obtaining solutions. A Case-Based Reasoning (CBR) expert system can be a solution to help customers independently identify the type of disruption. This study aims to build an expert system for diagnosing IndiHome disruptions using the CBR method that is able to recommend solutions based on the similarity of previous cases. The system is designed using the CBR approach with four main stages: Retrieve, Reuse, Revise, and Retain. Similarity calculations are performed using the Jaccard Coefficient metric, with attribute weights based on the importance of symptoms. The system is implemented web-based using PHP and MySQL. Validation was carried out through testing on 50 real disruption cases from Witel Cirebon. The test results showed the system was able to identify the type of disruption with an average accuracy of 86%. Cases with the highest similarity value were used as the basis for solution recommendations, such as checking the fiber cable, restarting the modem, or contacting 147. The CBR-based expert system has proven effective as an early diagnosis tool for IndiHome disruptions, providing fast and accurate solutions for customers, and reducing the burden on customer service..