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AUDIT SISTEM INFORMASI PENJUALAN PADA TOKO KELONTONG KARYA MEDAN MENGGUNAKAN FRAMEWORK COBIT 5 Nadifa Syachdini; Lala Anjelir; Hafiza Manik; Dwi Apriliana
Syntax : Journal of Software Engineering, Computer Science and Information Technology Vol 5, No 2 (2024): Desember 2024
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/syntax.v5i2.5418

Abstract

Toko Kelontong Karya merupakan sebuah toko kelontong yang terletak di Medan dan melayani kebutuhan sehari-hari masyarakat dengan menyediakan berbagai produk makanan dan kebutuhan rumah tangga. Seiring dengan perkembangan bisnis, sistem informasi penjualan yang digunakan oleh toko ini memerlukan evaluasi untuk memastikan operasional yang efisien dan aman. Penelitian ini bertujuan untuk melakukan audit terhadap sistem informasi penjualan di Toko Kelontong Karya menggunakan framework COBIT 5. Metodologi yang digunakan meliputi wawancara dengan pengelola toko, observasi langsung, dan analisis dokumen terkait. Audit difokuskan pada domain Deliver, Service, and Support (DSS) serta Monitor, Evaluate, and Assess (MEA). Hasil menunjukkan tingkat kematangan sistem berada pada level 1 hingga 2 (Initial dan Repeatable), dengan kelemahan utama berupa kurangnya prosedur standar operasional, keamanan data yang belum memadai, dan pengelolaan layanan pelanggan yang terbatas. Berdasarkan temuan tersebut, penelitian ini merekomendasikan penerapan prosedur operasional standar (SOP), sistem autentikasi untuk pengamanan data, serta pengelolaan data penjualan yang terintegrasi. Penelitian ini diharapkan menjadi panduan bagi Toko Kelontong Karya dalam meningkatkan sistem informasi penjualannya, serta menjadi referensi bagi toko kelontong lain yang ingin mengadopsi teknologi informasi secara optimal. Kata Kunci: Audit Sistem Informasi, Framework COBIT 5, DSS, MEA, Tingkat Kematangan.  ABSTRACT Toko Kelontong Karya is a grocery store located in Medan that serves the daily needs of the local community by providing various food products and household necessities. As the business grows, the sales information system used by the store requires evaluation to ensure efficient and secure operations. This study aims to audit the sales information system at Toko Kelontong Karya using the COBIT 5 framework. The methodology employed includes interviews with store managers, direct observation, and analysis of relevant operational documents. The audit focuses on the Deliver, Service, and Support (DSS) and Monitor, Evaluate, and Assess (MEA) domains. The results indicate that the maturity level of the current system is between levels 1 and 2 (Initial and Repeatable), with key weaknesses such as a lack of standard operating procedures (SOPs), insufficient data security, and limited customer service management. Based on these findings, the study recommends the implementation of SOPs, authentication systems to enhance data security, and integrated sales data management. This research is expected to provide guidance for Toko Kelontong Karya in improving its sales information system and serve as a reference for other grocery stores aiming to optimize the use of information technology in their operations. Keywords: Information System Audit,  Framework COBIT 5, DSS, MEA, Maturity Level.
Sentiment Analysis of Mikie Holiday Funland Visitor Reviews Using the Naïve Bayes Algorithm Lala Anjelir; Relita Buaton; Muammar Khadapi
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 6 No. 1 (2026): October 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v6i1.2592

Abstract

Mikie Holiday Funland is one of the tourist destinations in North Sumatra that receives numerous visitor reviews through digital platforms such as Google Maps and TikTok. The large number of available reviews makes manual analysis less effective, creating the need for sentiment analysis to identify visitors' perceptions of the facilities and services provided. This study aims to classify visitor reviews of Mikie Holiday Funland into positive, negative, and neutral sentiment categories using the Naïve Bayes method. This research adopted the CRISP-DM framework, with data processing stages including text preprocessing, lexicon-based sentiment labeling, TF-IDF weighting, and classification using the Naïve Bayes algorithm. The data used in this study were collected from Google Maps reviews and TikTok comments from February 2025 to February 2026, totaling 4,876 reviews. Model evaluation was conducted using a confusion matrix and classification report. The results showed that the Naïve Bayes method achieved an accuracy of 73% in classifying review sentiments. Of the 4,876 reviews analyzed, 849 reviews (17.4%) were classified as positive, 1,466 reviews (30.1%) as negative, and 2,561 reviews (52.5%) as neutral. The dominance of neutral sentiment indicates that most reviews were informative and did not express strong opinions. Furthermore, the analysis results were successfully implemented in a Streamlit-based application to provide interactive sentiment visualizations. These findings are expected to serve as evaluation material for improving the quality of tourism facilities and services, as well as a source of information for prospective visitors in making decisions about visiting Mikie Holiday Funland.