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All Journal Ekonomi Bisnis Jurnal Psikologi Majalah Ilmiah Ekonomi Komputer Jurnal Algoritma Jurnal Wacana Ekonomi Khazanah Sosial Khazanah Akademia Jurnal Algoritma
Abdusy Syakur Amin
Universitas Pasundan
Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Social Sciences

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Journal : Jurnal Algoritma

 1 
Implementasi Customer Relationship Management pada Sistem Penjualan Tiket Wisata di Karacak Valley Berbasis Website Amin, Abdusy Syakur; Septiana, Yosep; Rahayu, Sri; Farhan, Muhammad
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1458

Abstract

Customer Relationship Management technology is used as a strategy to build relationships with tourists and provide better services for tourists. where Customer Relationship Management technology is a modern marketing tool for tourist attractions, one of which is the Karcak Valley tourist attraction in Garut Regency. Apart from that, many regional and non-regional tourists visit, but currently the tourism management in Karcak Valley still uses a manual system in selling tourist tickets and the majority of tourists still lack information regarding the facilities, promos, blogs and galleries at Karcak Valley tourism. This research aims to overcome this problem, by implementing Customer Relationship Management in the website-based tourist ticket sales system in Karcak Valley to make it easier for tourists to find information about facilities, promos, blogs, galleries and order tourist tickets in Karcak Valley online. The methodology used in the process of creating this system is Rational Unified Process using Unified Modeling Language modeling. The results of this research will be a tourist ticket sales system that includes features such as information about tourist destinations in the Karacak Valley, facilities, promos, blogs, galleries, ticket prices, tourist locations and can increase trust in tourists, both new and retaining tourists. old tourists who have visited the Karcak Valley tourist attraction and make it easier for tourists to order tourist tickets in the Karcak Valley via a website-based online system.
Analisis Sentimen Pengguna Twitter dalam Pemilihan Presiden (PILPRES) 2024 dengan Menggunakan Algoritma K-Means Amin, Abdusy Syakur; Kurniadi, Dede; Nurzaman, Muhammad Zein; Nurfadillah, Rifa Sri; Khoerunisa, Sarah; Khaerunisa, Nisrina; Ajiz, Rafi Nurkholiq; Jembar, Tegar Hanafi; Faisal, Ridwan Nur
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1596

Abstract

One form of upholding democracy carried out by the Unitary State of the Republic of Indonesia is through holding presidential elections or often known as presidential elections. which is held every five years to elect the next President. Apart from that, in this digital era, people are increasingly actively using social media to convey their views, opinions and sentiments regarding the presidential election. Ahead of the 2024 presidential election, many groups such as political parties, success teams, buzzers and supporters are using social media as a campaign medium to increase the popularity and electability of their prospective candidates. One of the social media that is widely used in political party promotion media is Twitter. Which is used by people to post various comments that can be positive or negative regarding the election. Sometimes, people also express hoax opinions before or during the election. Considering that comments on Twitter are currently difficult to categorize as positive or negative, sentiment analysis is needed to understand public attitudes towards the presidential election. This research aims to evaluate text documents and determine whether the documents have a positive or negative sentiment orientation. Apart from that, the method used is K-Means to cluster the data. The results of this weighting are in the form of positive and negative sentiment. Data taken from Twitter regarding the 2024 presidential election (pilpres) totaling 1015 tweet data.
Co-Authors Abdullah Ramdhani Ai Khoerunisa Ai Khoerunisa Ajiz, Rafi Nurkholiq Dede Kurniadi Deni Sahroni Devi Apriani Enung Jamilah Euis Badrotul Mukaromah Faisal, Ridwan Nur Hilmi Aulawi Ijudin Jembar, Tegar Hanafi Khaerunisa, Nisrina Khoerunisa, Sarah Latifah, Hanny Masripah Masripah Muhammad Ali Ramdhani Muhammad Farhan Neng Khoerunisa Sri Mulya Nurfadillah, Rifa Sri Nurzaman, Muhammad Zein Rida Zuraida SRI RAHAYU Yosep Septiana