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UI/UX Design of Jepun Bali Store Product Ordering Application Using Design Thinking Method
Full text linkThe internet as a form of technological advancement continues to develop every year and has a great influence on human activities, including in terms of sales. The Jepun Bali Store, which sells products typical of Hinduism and Balinese customs, markets its products online with Instagram, Facebook, and WhatsApp. Instagram and Facebook are used to display the catalog, while WhatsApp is used for order communication. However, this system is considered less efficient because customers have to switch applications to view products, ask questions, and order. Stock and price information is not available in real-time, and the ordering process is still done manually, making it difficult for customers. From the manager's side, manual order recording risks creating errors, while admins are often overwhelmed with handling queries across multiple platforms, which impacts customer satisfaction. This research aims to simplify the transaction process, speed up services, and increase efficiency by applying the Design Thinking method. This method helps in understanding the needs of the user, structuring problems, and producing solutions through systematic stages. The results of the design test using the System Usability Scale (SUS) method with 30 respondents obtained a score of 88.5833 out of 100, included in category A (Excellent) and considered acceptable
Evaluating IT Service Capability of Palu BPS Website Using COBIT 5 Framework
Full text linkThis research assesses the IT service capability of the official website of the Palu City Central Bureau of Statistics (BPS) by applying the COBIT 5 framework. The assessment is centered on four key processes from the Deliver, Service, and Support (DSS) as well as Monitor, Evaluate, and Assess (MEA) domains—namely DSS01 (Manage Operations), DSS02 (Manage Service Requests and Incidents), DSS06 (Manage Business Process Controls), and MEA01 (Monitor, Evaluate, and Assess Performance and Conformance). Data were collected through structured interviews, observation sessions with website administrators, and an analysis of supporting documents to determine the current capability levels and compare them with the desired target level of 3. The results show that DSS01 and MEA01 have reached capability level 2, indicating that the processes are defined but not consistently standardized. Meanwhile, DSS02 and DSS06 remain at level 1, indicating reactive operations with limited documentation. The average capability level of 1.5 suggests that there is room for significant improvement in terms of documentation, process formalization, and the use of enabling technologies. Based on these findings, this study recommends targeted improvements to enhance the overall performance and reliability of digital public services, as well as to support better IT governance and e-government practices
Fine-Tuning GMM and Total Pixel-Based Drowsiness Detection: A Strategy for Detection Open and Closed Eye
Full text linkFatigue driving represents a substantial and often unrecognized risk in traffic accidents. A technique that may be employed involves the detection of open and closed eyes. The research on open and closed eye identification use approaches based on haar cascade and complete pixel analysis. Our proposed method employs an adaptive thresholding technique is implemented right before total pixel process. The processing steps involve the application of haar cascade, adaptive thresholding, fine-tuning of Gaussian Mixture Models (GMM), and the calculation of the total pixel count in the image that is utilized to identify the state of the eye using thresholding. The results from Fine-Tuning GMM thresholding for the left and right eyes are as follows: MSE values of 7.02 and 7.96, and PSNR values of 39.24 and 39.21, respectively. The results derived from fine-tuning are comparable to those obtained using Otsu's method
Data Center Information Security Analysis Based on ISO 27001:2022 Standard Using the FMEA Method at PT XYZ
Full text linkPT XYZ is an IT distribution company playing a crucial role in supplying technology products in Indonesia. As a company operating in the field of information technology, PT XYZ has a data center that stores various critical information. Ensuring the security of data within this data center is essential, and it must be protected with adequate security standards. Following the Information Technology Security and Decision Directives of PT XYZ, an evaluation of the information security within the company's data center was conducted to achieve ISO 27001 certification for information security. This research aims to assess and evaluate the level of information security in PT XYZ's data center using the SSE-CMM assessment index and to identify the Risk Priority Number (RPN) for each identified risk using the FMEA method. The findings indicate that the maturity level of information security in the data center is at Level 3 (defined process) in the SSE-CMM model. Additionally, risk assessment using the FMEA method identified that 14 risks are in the Very Low category, 2 risks are in the Low category, and 2 risks are in the High category. The overall evaluation suggests that PT XYZ's data center is sufficiently prepared to achieve ISO 27001 certification. One recommended improvement is to periodically update the Work Instructions (WI) related to information security policies and to regularly review these security policie
Control System Design Concept for Coconut Shell Charcoal Powder Processing Equipment as a Base Material for Herbal Toiletries Integrated with PV System
Full text linkVarious raw materials with enhanced benefits have been discovered for the toiletries industry. One promising material is coconut shell charcoal powder (Cocos nucifera), which can be used as a base ingredient in herbal toiletries formulations. However, its production process still faces challenges, particularly in terms of technology and operations, especially for small and medium enterprises. Therefore, this study aims to design a control system concept for a coconut shell charcoal powder processing unit integrated with a PV system.
The methods used include a literature review and a descriptive study through interviews with practitioners and academics specializing in charcoal powder production systems and herbal toiletries formulation. The result of this study is a conceptual design of a control system equipped with a remote monitoring system to oversee and regulate the coconut shell charcoal powder production process more efficiently
Analysis and Design of Food Price Data Processing Information System
Full text linkFood prices have an important role in maintaining economic stability and public welfare, as price fluctuations can have a direct impact on purchasing power and inflation. The manual process of recording and reporting food price data at the Department of Agriculture and Food Security of Palu City leads to inefficiencies, data inaccuracies, and difficulties in tracking historical information. These limitations highlight the need for a structured system that can support accurate and efficient data management. This study applies a prototyping method to develop a web-based information system tailored to the needs of the institution. The development process involves continuous interaction between users and developers to ensure the system meets practical requirements. Data were collected through interviews, observations, and documentation. System functionality was tested using black box testing, while usability was assessed using the System Usability Scale (SUS) questionnaire. The results indicate that the system's features, including daily price input, automatic average calculations, report submission, and approval workflows, function correctly. Users are able to interact with the system efficiently, and the SUS results show that the system falls into the acceptable usability category, indicating that it is easy to use. In conclusion, the development of this web-based information system improves the efficiency and accuracy of food price data processing and reporting. It provides a reliable tool for managing information within the department and supports better operational performance
Systematic Literature Review: The Use of the K-Nearest Neighbor Algorithm in Data Classification for Government Policy Optimization
Full text linkAlong with the rapid advancement of technology and the progress of the digital era, the volume of data across various sectors has significantly increased, making it necessary to process this data to support policy optimization. Data processing is essential for simplifying complex data by grouping it according to specific characteristics. K-Nearest Neighbor (KNN) is a widely used classification algorithm in data mining implementation, applying the principle of class determination based on the proximity between data points, calculated using the Euclidean distance metric. In the governmental sector, this algorithm has been utilized to improve the efficiency of public policies and data-driven decision support systems. This study employs a Systematic Literature Review (SLR) to examine the use of the K-Nearest Neighbor algorithm in previous research for classifying government-related data as a foundation for formulating more effective and efficient policies. The information is gathered by collecting references from relevant journals and studies to provide a detailed understanding of the effectiveness of data processing as a means for optimizing government policies and offering well-targeted decision-making recommendations
Use of Residual Network (ResNet) for Disease Classification in Potato Leaves: Penggunaan Residual Network (ResNet) untuk Klasifikasi Penyakit pada Daun Kentang
No full textDiseases in potato plants can have serious impacts on crop yield and overall plant health, threatening the sustainability of agricultural production. To enhance the accuracy and efficiency of potato leaf disease detection, this study proposes a new approach utilizing Residual Network architecture, a promising technique in image analysis. The dataset used is sourced from the public Kaggle repository, providing the necessary diversity to effectively train the model. The process of splitting the dataset into training and testing data is essential to optimize the performance of the Residual Network algorithm, ensuring that the model can generalize disease patterns well. The research findings highlight that Scenario 1, which adopts a training-to-testing data ratio of 90:10, emerges as the most optimal choice. In testing, this scenario demonstrated superior performance compared to other scenarios, achieving the highest accuracy rate of 76%, indicating its promising performance in classifying data with high accuracy. These results suggest significant potential for this approach in practical applications for effective and efficient potato leaf disease detection, thereby enhancing agricultural productivity and ensuring food security
Prediksi Transaksi Minat Pembelian Online Menggunakan Kombinasi CNN Conv1D dan BiLSTM
Full text linkThe rapid development of information technology has transformed consumer shopping behavior, particularly through e-commerce platforms. Online shopping has become a primary trend due to its convenience and the growing penetration of the internet. Understanding online purchase intention is therefore crucial for businesses in devising effective marketing strategies. Purchase intention is influenced by factors such as product quality, price, customer reviews, and platform usability. However, predicting purchase intention poses a significant challenge due to the large and complex nature of consumer data. Smote used for imbalance data. This study aims to combine CNN (Conv1D) and BiLSTM for high-accuracy purchase intention prediction. The research focuses on analyzing model accuracy and the effectiveness of the algorithms in handling imbalanced data. The results indicate that the combined CNN(Conv1D) + BiLSTM model achieves 97% accuracy with balanced evaluation metrics, although the True class recall (96%) is slightly lower than that of the False class (95%). Further optimization is needed to enhance overall model performance
Video Blended Learning Sebagai Penunjang Mata Pelajaran Bahasa Indonesia Pada SMP Gandasari
Full text linkKesuksesan masa depan anak bangsa sangat bergantung pada pendidikan, karena dapat memberikan pengetahuan, membentuk keterampilan, sikap dan pemahaman yang sangat diperlukan dalam menghadapi tantangan yang ada di masyarakat. Keberhasilan siswa sangat bergantung pada metode dan media pembelajaran yang digunakan. Masalah yang di hadapi SMP Gandasari adalah metode pembelajaran Bahasa Indonesia sebelumnya dianggap kurang efektif, karena hanya berfokus pada penyampaian materi oleh Guru di kelas dan pemberian tugas untuk evaluasi pembelajaran. Sekolah memerlukan pengembangan media pembelajaran baru, seperti blended learning berbasis video. Blended learning merupakan kombinasi pembelajaran tatap muka dan online. Metode ini akan menggabungkan berbagai model pengajaran dan gaya belajar untuk memungkinkan interaksi antara pendidik dan siswa. Media ini dibuat dengan tujuan untuk membantu Guru dalam mengajar Bahasa Indonesia agar lebih menarik dan mudah dipahami, karena terdapat visual, animasi dan audio. Metode penelitiannya yaitu pengumpulan data, observasi, studi Pustaka dan analisis PIECES. Software yang digunakan yaitu, Filmora X dan Corel DRAW X7 serta Konsep Produksi Media. Dengan video Blended Learning ini dapat membantu proses belajar mengajar siswa/i kelas VII SMP Gandasari, dalam mata pelajaran Bahasa Indonesia, dengan lebih efisien