Infact: International Journal of Computers

The The Role of the Billing Information System (SITAGI) in Improving the Efficiency of Invoice Monitoring (Case Study: Toko Manis Surakarta)

Ian Nugroho Kristanto — 2025-09-10

This study discusses the role of SITAGI in assisting with the monitoring of purchase invoices, using a case study at Toko Manis Surakarta. The main objective of this study is to improve the efficiency of invoice monitoring before the due date. SITAGI was developed using HTML, PHP, MySQL, CSS, and JavaScript programming languages. The purchase invoice data is taken from billing notes and stored in a MySQL database, utilizing the Advanced Encryption Standard (AES) encryption technique.

The results of the study show that the use of SITAGI enhances the efficiency of invoice monitoring and provides benefits for both the owner and suppliers. This information is presented in tables equipped with specific parameters. The owner of Toko Manis Surakarta stated that SITAGI is highly helpful in managing bills efficiently. The conclusion of the study is that the use of an appropriate information system can improve the efficiency of invoice monitoring and offer distinct advantages for the owner.

Design and Development of an IoT-Based Monitoring System for Solar Phone Charging Stations.

Anita Yuan — 2025-09-17

In recent decades, sustainability and renewable energy utilization have become major global concerns. Solar energy, harnessed through photovoltaic (PV) technology, is one of the most promising sources, with charging stations as a practical application. To ensure system efficiency and stability, a reliable real-time monitoring system is required. This study designed and implemented an IoT-based monitoring system for a Solar Phone Charging Station. The system employs an Arduino Mega 2560 as the main processor, NodeMCU ESP8266 for internet connectivity, and sensors including a 0–25 V voltage sensor, ACS712 current sensor, and DHT11 temperature and humidity sensor. Data are transmitted and visualized in real time using the ThingSpeak platform. Experimental results demonstrate that the system performs effectively in capturing and transmitting data. However, limitations remain, such as sensor reading errors, dependence on internet connectivity and solar-powered batteries, and relatively high error rates in current, temperature, and humidity measurements, indicating the need for improved calibration and validation.

A System Engineering Approach to Sustainability Decision Support System Based on the Global Reporting Invitiative

Muhammad Syaukani — 2025-08-01

Study this to develop a Sustainability Decision Support System (SDSS) based on the Global Reporting Initiative (GRI) at Insitut Teknologi Bisnis dan Bahasa Dian Cipta Cendikia (ITBA DCC) using a systems engineering approach. SDSS is designed to support decision-making sustainability data through a staged engineering system that includes analysis requirements, design, implementation, testing, application, and maintenance. This system integrates GRI indicators with campus data and produces visualizations as well as multi-criteria analysis, using increased transparency and accountability within institutions. The results show that SDSS is capable of facilitating comprehensive reporting in dimensions of social, economic, environmental, and governance. Research also confirms the importance of stakeholder collaboration in designing a responsive system to challenge sustainability in college high. The developed model is expected to be replicated in other institutions to strengthen digital governance? sustainability and standardization.

An IoT-powered smart helmet to avoid drowsiness and theft protection

Yogi Putra Prasetya — 2025-09-19

Helmets are mandatory equipment for motorcyclists, but current helmets only serve to reduce injuries during accidents. Accidents often occur due to human error, such as drowsiness while riding which endangers the rider and others. In addition, helmets are also vulnerable to theft if they are far from the owner. This research aims to reduce these problems by adding drowsiness warning and theft detection features to the helmet. The drowsiness warning feature uses MAX30102 sensor to detect heart rate as a parameter of drowsiness condition, while the theft detection feature uses magnetic reed switch sensor as a switch with magnet as a parameter of theft. Through IoT technology, riders can monitor their heart rate in real-time and receive notifications in case of theft. Tests show that the drowsiness warning feature has an error rate of 3.23% in detecting microsleep and the theft detection feature is able to send warning messages with an average time of 8 seconds.

Sentiment Analysis on Starbucks Reviews: Implementation of K-Nearest Neighbors and Support Vector Machine

Jasmine Nabila — 2025-09-15

This study conducts sentiment analysis on Starbucks customer reviews from the ConsumerAffairs website using the K-Nearest Neighbors (KNN) classification algorithm. The objective is to evaluate customer satisfaction and perceptions of service. Reviews are preprocessed with standard NLP techniques and labeled using TextBlob based on sentiment polarity: positive, neutral, or negative. The KNN algorithm is tested with different training and testing ratios: 60%:40%, 70%:30%, and 80%:20%. The best accuracy, 85%, is achieved with a 60%:40% split, indicating that a balanced dataset improves performance and reduces overfitting. Results show that most reviews reflect positive sentiment, with words like ‘awesome’, ‘sweet’, and ‘variety’. Nonetheless, some reviews mention negative experiences, especially health-related issues and in-store equipment problems. The KNN method proves effective for sentiment classification and provides meaningful insights that Starbucks can utilize to enhance product quality, service efficiency, and overall customer satisfaction.

Forensic Metadata Analysis in Detecting Digital Image Manipulation

Mario Anugraha — 2025-08-01

The development of the digital era has brought significant changes to various aspects of life, including the field of photography. Digital photos offer both advantages and disadvantages, one of which is the ease with which they can be modified using image editing software. This makes it increasingly difficult to distinguish between original and manipulated images. Edited photos can spread widely through social media, causing public concern and doubts about the authenticity of information. Individuals often manipulate images for personal gain or interests. The easy access to image editing software further facilitates this manipulation process. In the field of research, digital image forensics has emerged as a scientific method to verify the authenticity of images through accountable evidence. This study aims to detect forgery in digital photos using that approach. The method employed in this research is metadata analysis with the assistance of an offline tool called JPEGsnoop and online tool Forensically Beta. The results show differences in metadata between the original and manipulated images, indicating that modifications have been made to the image.