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Aiti: Jurnal Teknologi Informasi
Published by Universitas Kristen Satya Wacana
ISSN : 16938348     EISSN : 26157128     DOI : https://doi.org/10.24246/aiti
Core Subject : Science,
Computer Science & IT
AITI: Jurnal Teknologi Informasi is a peer-review journal focusing on information system and technology issues. AITI invites academics and researchers who do original research in information system and technology, including but not limited to: Cryptography Networking Internet of Things Big Data Data Science Software Engineering Information System Web Programming Mobile Application Service System Artificial Intelligence Digital Image Processing Machine Learning Deep Learning Geographic Information System Context Aware System Management Information System Software-defined Network
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 10 Documents
 1 
Search results for , issue "Vol 21 No 1 (2024)" : 10 Documents clear
Implementasi Rapid Application Development dalam membangun sistem pengelolaan keuangan Homestay Linia berbasis web Julians, Adhe Ronny; Iriani, Ade; Sembiring, Irwan
AITI Vol 21 No 1 (2024)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v21i1.1-13

Abstract

In running a business, the ease of managing financial data is essential because it is closely related to how income and expenditure data can be managed properly. The absence of an efficient system for managing financial data is a problem encountered in the object of this research, namely Homestay Linia, wherein managing the financial data in question, there are still certain complications, which result in financial data being inaccurate and irregular, related to these problems, it is necessary to build a financial management system. In developing the system, researchers use the Rapid Application Development method and will conduct system testing using the Black Box Testing method and User Satisfaction Survey through Online Questionnaires. The results showed that the system that has been built gets 100% positive reviews given by respondents. It shows that the system can help business activities effectively and efficiently.
Sistem pendukung keputusan kelayakan dalam menentukan posisi jabatan pada PT SCI dengan metode FAHP Leonardo, Leonardo
AITI Vol 21 No 1 (2024)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v21i1.29-43

Abstract

Making decisions in giving positions to employees is important because it can affect the company's progress; the assignment itself has several types, one of which is the provision of promotions and demotions to employees. In this study, a decision support system was developed to determine employee positions by providing demotions or promotions to employees working at PT SCI using the web-based Fuzzy AHP (FAHP) method. The results are that employees in the top four ranks will get promotions, and employees with high positions but not in the top four will be demoted. The data collected is PT SCI's employee data. The results of this research are decision-making applications using the FAHP methods, which can help simplify and speed up the determination of employee demotions and promotions.
Perancangan UI/UX pada website Arttrash menggunakan metode Design Thinking Agnestisia, Amelliandha Evifania; Wenas, Michael Bezaleel; Pratiwi, Peni
AITI Vol 21 No 1 (2024)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v21i1.14-28

Abstract

Appearance covid-19 influenced Arttrash, one of the Salatiga MSMEs engaged in selling miniature waste recycling, because it caused Arttrash to reduce its production capacity so that people worried that Arttrash would be forgotten. This study discusses designing a UI/UX-based website as a promotional medium for Arttrash to expand its business share. UI/UX was designed using the method of design thinking, which realizes the value of environmental preservation based on the use of raw materials from waste—using a qualitative approach to get the problem faced. The result UI/UX was evaluated using the method of usability testing. The result is that design thinking maximizes the design of the UI/UX website Arttrash for help in understanding the target user so that users feel comfortable and easily explore the website Arttrash.
Analisis dan perancangan sistem informasi layanan RT RW Net MR WiFi berbasis web Asferand, Arsel Tirta; Chernovita, Hanna Prillysca
AITI Vol 21 No 1 (2024)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v21i1.117-139

Abstract

RT RW Net merupakan sebuah penyedia jasa internet berskala mikro (dalam satu wilayah). MR Net merupakan salah satu penyedia jasa RT RW Net yang ada di daerah Bawen. Sampai saat ini MR Net mengelola data administratif dengan metode manual yang menyebabkan kegiatan proses bisnisnya terhambat, karena itu dirancanglah sistem informasi berbasis website dengan sistem yang saling terintegrasi. Sistem ini dirancang menggunakan metode waterfall dan data yang dibutuhkan oleh perancang didapatkan dengan observasi langsung dan wawancara. Sistem informasi yang terbentuk ialah halaman login, menu dashboard, menu user, menu ticketing, menu tagihan aktif, dan menu profile. Untuk pengguna dibagi menjadi dua role, admin dan user, yang masing-masing role memiliki fungsi tersendiri. Role admin memiliki fungsi mengelola data user, tiketing, dan tagihan. Role user memiliki fungsi melihat riwayat tagihan pribadi, pengajuan tiket, dan mengelola data pribadi. Keseluruhan data akan tersimpan pada database lokal yang diharapkan dapat menunjang proses bisnis administratif, serta meminimalisir terjadinya kesalahan dan kehilangan data.
Analisis harapan UMKM terhadap program e-commerce Dinas Koperasi dan UMKM DIY (Pendekatan studi kualitatif) Palangan, Citra Yayu'
AITI Vol 21 No 1 (2024)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v21i1.72-81

Abstract

This study examines the expectations of MSMEs regarding e-commerce programs implemented by Dinas Koperasi dan UMKM DIY. MSME expectations were analyzed using the open-coding method with the QDA Miner Lite software. In total, 59 data on expectations were analyzed and categorized into 14 expectation codes. Subsequently, the researcher selected the top three expectations from the analysis of the codes. The study's findings indicate that the three main expectations of MSMEs are training and mentorship programs, government support for marketing MSME products, and government funding support.
Klasifikasi kualitas mutu susu pasteurisasi menggunakan metode klasifikasi k-Nearest Neighbor Wakhidah, Nur; Rochmah, Shafira Nur
AITI Vol 21 No 1 (2024)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v21i1.58-71

Abstract

Milk is a product that is often consumed because it has many good benefits for the body. One of the benefits of milk is that it contains calcium, which is useful for the growth of bones and teeth. However, many consumers still choose dairy products based only on their appearance, even though milk quality is not based on its appearance but is found during milk processing. Pasteurization is the process of heating whole milk at a specific temperature and for a certain period to increase the milk's shelf life and maintain the milk's quality. Two types of pasteurization processes are Long Temperature Long Time and High Temperature Short Time. k-Nearest Neighbor or k-NN is a data mining method used to classify objects from the data, using distance calculations or Euclidean Distance to look for similarities between neighbors. So, based on this problem, milk quality classification is carried out. The research was carried out by classifying milk quality using the K-NN method. The public data used to classify is 1,059 pasteurized milk data, with seven regular or ordinary attributes and one special or class attribute. The K values ​​that will be used in this research are k=3, k=5, and k=7. From the analysis of calculation results using the k-NN method, the accuracy values ​​obtained are k=3 is 97%, k=5 is 89%, and k=7 is 87%.
Sistem penilaian kinerja pegawai di kantor Kementerian Agama Provinsi Papua Barat menggunakan metode Self Organizing Map (SOM) Jubita, Jubita; Suhendra, Christian Dwi; Sanglise, Marlinda
AITI Vol 21 No 1 (2024)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v21i1.96-116

Abstract

A government agency requires employees who have competence and good performance. Various factors affect performance between the abilities of other individuals and the agency environment, including the office of the Ministry of Religion in West Papua Province. However, the performance assessment process still needs to be better for making assessment decisions and is still subjectively based. Those things affect the employee's assessments. For example, employees cannot complete work according to predetermined targets and must be more careful in carrying out the work. So, to facilitate this assessment, an accurate calculation application is needed. A Self Organizing Map (SOM) is used to sort data in a group with similar data that are close to each other. Using the R (programming language) and R studio as the required application platform, we can calculate values and form them into three clusters: very good, quite good, and poor. Then, from the calculation results, 55 employees, with a percentage of 42%, match cluster with quite good performance, 29 employees, with a percentage of 22%, are in cluster with poor performance, and 48 employees, with a percentage of 36%, are in cluster with very good performance.
Uji kerentanan keamanan pada web Sistem Informasi Akademik Satya Wacana menggunakan metode Vulnerability Assessment Efendi, Rissal; Wahyono, Teguh; Widiasari, Indrastanti R.
AITI Vol 21 No 1 (2024)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v21i1.44-57

Abstract

Vulnerability assessment is a process to look for system security gaps that can cause information technology process system failure. In carrying out a vulnerability assessment there are three main stages, namely information collection, assessment and exploit using the Greybone Openvas tool with a Full Scan template on the object and several credentials provided by a website. From the vulnerability assessment process, five vulnerabilities were found on assets, namely critical risk with a few 0, high risk with a few 2, medium risk with a few 2, and low risk with a few 1. Based on the conclusions from the vulnerability analysis the website and the results of identity verification, it was concluded that the website had a few weaknesses and vulnerabilities that needed to be fixed to maintain the security and quality of the website. Corrective actions on website configuration need to be taken such as setting cookies, SSL, HTTP headers, and others. SSL/TLS services do not accurately limit the renegotiation stage of the system, making it easier for attackers to carry out Denial of Service attacks by carrying out many renegotiations in one connection.
Using the Support Vector Machine method with the HOG feature for classification of orchid types Andayani, Sri; Kusneti, Leni
AITI Vol 21 No 1 (2024)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v21i1.82-95

Abstract

Orchids are the most species-rich flowering plants, with approximately 750 genera and 43,000 types of orchids in the world, of which about 5,000 species have been recorded in several provinces in Indonesia. Orchids have beautiful flowers with attractive colors, making them ornamental plants that many people like. From plant morphology, orchid plants can be differentiated based on the morphology of flowers, leaves, fruit, stems, and roots. The leaves of orchid plants have their characteristics for each type of orchid, such as long, round, or lanceolate. All orchids have veins that run parallel to their leaves. The individual shapes of orchid leaves can be classified using a Support Vector Machine (SVM) and Histogram of Gradient (HOG). In this research, five types of orchids that are popular among orchid lovers were used, namely Dendrobium, Cattleya, Oncidium, Phalaenopsis, and Vanda orchids, which were taken from public data. The accuracy of this method in classifying orchid species based on leaf morphology can be measured using a confusion matrix that measures precision, recall, and accuracy. From five tests, the Oncidium orchid had the highest average accuracy with a value of 98%, the Vanda orchid had the highest average precision of 99.80%, and the Cattleya orchid had the highest average recall of 100%.
A comparative study on classification models for stock rating prediction Yap, Justin; Wiradinata, Trianggoro
AITI Vol 21 No 1 (2024)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v21i1.140-151

Abstract

The digital transformation in the stockbroker industry has led to a significant increase in retail investors, who often lack the expertise to analyse stocks thoroughly. This research addresses the challenge by proposing a classification model to predict stock ratings such as "Reduce", "Hold", "Moderate Buy", and "Buy”, allowing retail investors to make informed decisions. The data analysed is collected from the S&P 500 index through web scraping using Beautiful Soup, resulting in a dataset used for training and testing the classification model. Popular stock indicators are used as attributes in predicting the rating of the stock, which includes the Exchange, Price, Volume, Market Cap, ROE, ROA, P/E Ratio, EPS, Annual Sales, Net Income, Net Margins, and PB Ratio of the stock. The models selected for classification include K-Nearest Neighbors (k-NN), Gaussian Naive Bayes, Support Vector Machine (SVM), Decision Tree, and Random Forest. GridSearch is employed to maximize each algorithm's parameters for optimal performance. Results indicate that the k-NN model outperforms others, achieving the highest accuracy (0.618644) and weighted F1-score (0.605011). However, all models exhibit relatively low accuracy, suggesting the complexity of predicting stock ratings due to external factors not considered in the study.

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