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All Journal JURNAL AKUNTANSI, EKONOMI dan MANAJEMEN BISNIS Jurnal Mantik
Novianti Madhona Faizah
Universitas Tama Jagakarsa
Computer Science & IT Economics, Econometrics & Finance Languange, Linguistic, Communication & Media

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Aturan Asosiasi Antar Item Terjual pada Data Penjualan Minimarket Milik Komunitas di Hari Besar Tertentu Menggunakan Algoritma Apriori Luky Fabrianto; Novianti Madhona Faizah; Johan Hendri Prasetyo; Bobby Suryo Prakoso; Gani Wiharso
JURNAL AKUNTANSI, EKONOMI dan MANAJEMEN BISNIS Vol 9 No 2 (2021): Jurnal Akuntansi, Ekonomi dan Manajemen Bisnis - Desember 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaemb.v9i2.3621

Abstract

The popular data mining methods to find the relationship between an item and another item is the association rule method using A Priori algorithm, this method is precise to generate a pattern of relationship rules between the types of items sold based on sales data. Support values ​​on frequent items and confidence in the rules obtained can be an actionable insight that can be follow up by minimarket managers, cooperatives and etc. The categorization of product types in minimarkets is much while the total number of transactions in one year is also very large, but the number of types of items sold in a transaction is very few, thus the threshold value cannot be high. In this study, the association rule method was carried out per event or certain period related to Muslim holidays, the highest rule was obtained is Makanan ringan => Sembako with 46% confidence and 16% support which occurred in the month of Ramadan.
Narrative Inquiry Dalam Desain Naratif Game Widyat Nurcahyo; Novianti Madhona Faizah; Luky Fabrianto
Jurnal Mantik Vol. 6 No. 2 (2022): August: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v6i2.2506

Abstract

Storytelling is a part of human life long before writing. In the digital era, where images, audio, video, and text are used together, it unlocks new possibilities in delivering narratives, for instance, games. Narrative-based games have a long history. With increasingly sophisticated graphics technology, making it more and more popular. This study demonstrates a unique approach to game narrative design using the narrative inquiry method. Narrative Inquiry captures and analyzes life stories, then documents life events in their quintessence. The game tells the story of young entrepreneurs' journey in building their business, focuses on the elements of entrepreneurial skills required, and aims to motivate the entrepreneurial intention of the players. This research was conducted in three stages: narrative collection, narrative analysis, and scenario creation. Interviews were conducted with four young entrepreneurs from various businesses to collect narratives. Narrative analysis was carried out using a thematic approach. The narratives were transcribed, categorized, and cross-referenced among stories. The results were compiled as a game plot, then developed into a complete scenario with attention to the original narrative text. This example will provide a fresh perspective to designing game narratives from real life stories.
Natural Language Processing Analysis Of Frequently Used Words On Indonesia Website Names Novianti Madhona Faizah; Luky Fabrianto; Widyat Nurcahyo; Herlina Trisnawati
Jurnal Mantik Vol. 6 No. 3 (2022): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

The increasing of internet use time after time is makes an impact addition of websites, the name of a website must be unique, eye catching and attractive, and in naming a website it should not use spaces, therefore it is often found that the website name consists of several words which are combined. This study aims to determine the most frequently used words on websites in Indonesia. The stages of this research briefly begin with the collection of 10,960 website names, word separation on each website name consisting of several words using Wordninja (one of packages available in Python programming language). The word separation process is carried out in several stages, starting from words containing at least 3 letters to 9 letters. Furthermore, from the word separation stage, ten words that appear most often are sorted. It was found that the word "Indonesia" most often appears at each stage of word separation, which is 139 times. Conclusion of this study is prove that Wordninja were very effective, as evidenced by an accuracy of 97.2%.
Sentiment Analysis of Non-Fungible Token (NFT) on Twitter Social Media Using Support Vector Machine Method Suci Br Kembaren; Siti Saidah; Arifin Nur Rahmad; Luky Fabrianto; Novianti Madhona Faizah
Jurnal Mantik Vol. 6 No. 3 (2022): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v6i3.3334

Abstract

Social media Twitter is used as an expression of opinion for the global community, especially in Indonesia. Non-Fungible Token (NFT) also has public opinion, sentiment from opinion can be classified into two classes, negative sentiment and positive sentiment. Using the keyword "NFT Indonesia" in API from Twitter, search for tweets data obtained 2204 tweets, through the manual labeling and pre-processing stages, 1462 tweets were obtained. After tweets/data has through cleansing stage, data are separated into training data and test data and then Support Vector Machine method is used to form a model that can classify positive or negative sentiment. The results of the sentiment analysis are visualized using a pie chart. The results obtained from opinion of Indonesian netizen regarding that Non-Fungible Token (NFT) have a positive trend with a percentage of 95.90% and for negative sentiment is 4.10% with an accuracy of success in this sentiment analysis is 86%.
Co-Authors Arifin Nur Rahmad Bobby Suryo Prakoso Gani Wiharso Herlina Trisnawati Johan Hendri Prasetyo Luky Fabrianto Siti Saidah Suci Br Kembaren Widyat Nurcahyo