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Jurnal Penelitian Teknologi Informasi dan Sains
Published by INSTITUT TEKNOLOGI DAN BISNIS SEMARANG
ISSN : 29856280     EISSN : 29857635     DOI : 10.54066
Core Subject : Science,
Computer Science & IT
Ruang lingkup meliputi bidang Informatika, Teknik Mesin, Teknik Elektro,Teknik Sipil, Teknik Industri, Ilmu Komputer dan Sains.
Arjuna Subject : Ilmu Ekonomi, Ekonometrika dan Keuangan (semua kategori) - Ilmu Ekonomi, Ekonometrika dan Keuangan (Lain-Lain)
Articles 97 Documents
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Analisis Peminjaman Ruangan di Gedung Creative Center Sumedang Menggunakan Metode PIECES Dipa Arya Pangestu; Asep Saeppani
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 3 No. 1 (2025): JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v3i1.2998

Abstract

The utilization of information technology can provide benefits that are faster, more accurate, and more transparent. One application is in a room loan system that can avoid schedule clashes, increase user productivity, and make the administration process faster and more efficient. This research was conducted at the Sumedang Regency Tourism, Culture, Youth and Sports Office in the creative economy sector, which manages room loans at the Creative Center Sumedang Building. The current room loan system at the Creative Center Sumedang Building uses Google Form which experiences various obstacles, such as conflicting schedules and inefficient administrative processes. This study aims to evaluate and provide recommendations for a website-based system that is more structured and user-friendly to support room loan management. This research uses the PIECES (Performance, Information, Economy, Control, Efficiency, and Service) analysis method to evaluate the weaknesses of the current system and provide recommendations for website-based improvements with UI/UX design integration. Data was collected through observations and interviews with managers and users of room lending services. The results of the analysis show that a website-based system can improve the efficiency of room loan management, ensure a more organized schedule, and facilitate automatic data management. The proposed solution includes automatic room checking and a simpler interface design. With the implementation of an integrated and user-friendly system, room loan management is expected to become more effective and support optimal service.
Sistem Informasi Manajemen Klinik Universitas Jambi Guna Mendukung Operasional Klinik Fairuz Fairuz; Rizqa Raaiqa Bintana; Novita Sari
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 2 No. 4 (2024): Desember : JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v2i4.3040

Abstract

Generally, what is found in the clinic includes, registration, doctor consultation, procedure room, laboratory, and pharmacy. The same is true for the facilities available at the Jambi University clinic. All of these are managed by the Jambi University clinic and must be integrated so that all data is united into one information unit. Officers are required to be able to manage all data and manage the clinic well so that no data or information is lost, especially medical records and documents for each patient who is being treated. Therefore, the Information and Communication Technology Development Institute (LPTIK) as an institution at the University of Jambi that is tasked with carrying out information and communication technology development activities wants to help optimize clinic management activities through the development of a clinic application where this application is able to store and manage all data related to the clinic, especially patient data visiting the Jambi University clinic. Thus, the recording and recording of data in the clinic which is currently done manually, can slowly be abandoned towards electronic management activities based on applications. It is hoped that this application-based management activity can help and facilitate clinic officers in managing the clinic, reduce the risk of data loss due to human error or disaster, improve clinic performance, and integrate clinic data as a whole. The UNJA Clinic application was built to facilitate and facilitate all activities related to recording and recording data in the clinic digitally so that the data is fully integrated from several existing parts. The UNJA Clinic application that has been built is a website-based application.
Analisis Big Data untuk Prediksi Permintaan Produk dalam E-commerce Sumita Wardani; Saidan Sany Lubis; Rico Wijaya Dewantoro
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 3 No. 1 (2025): JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v3i1.3066

Abstract

The rapid development of e-commerce has generated huge volumes of data, opening up opportunities to analyze product demand patterns more accurately. This research aims to develop a product demand prediction model based on big data analysis. The data used includes sales transactions, product searches, customer reviews, and external factors such as seasons and promotions. The main methods used are machine learning techniques such as random forest regression and neural networks to build predictive models, with data extraction, transformation, and analysis processes carried out using big data platforms such as Hadoop and Spark. The resulting model is evaluated using accuracy metrics, such as mean absolute error (MAE) and root mean square error (RMSE), to measure prediction performance. The results show that the use of big data in product demand prediction can increase the accuracy of inventory planning and stock management by up to 25% compared to conventional methods. These findings make a significant contribution to the optimization of e-commerce operations, especially in more efficient and timely data-driven decision-making.
Implementasi Pengujian Kerentanan Windows 10 Menggunakan EternalBlue dan Phising Muhammad Naufal Hafizh; Isram Rasal
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 3 No. 1 (2025): JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v3i1.3119

Abstract

Attacks on Windows can be carried out in various ways, one of which is exploiting SMBv1 vulnerabilities and phishing. Exploitation is an attack technique that takes advantage of system weaknesses. Windows 10 itself has vulnerabilities that can be exploited for hacking, which may include data theft, user data deletion, credential theft, and even damaging the Windows 10 system itself. A possible solution is to conduct penetration testing on the Windows 10 operating system. The testing is carried out based on the Cyber Kill Chain model, utilizing appropriate tools and following the stages outlined in the model. The test results indicate that Windows 10 vulnerabilities can be exploited, particularly through direct system attacks via SMBv1 with CVE-2017, codenamed EternalBlue, and phishing techniques that allow attackers to gain administrator privileges directly or inject malware into the target Windows 10 system.
TOWR Stock Forecasting From 2021-2025 Using Machine Learning Andy Hermawan; Angga Sukma Budi Darmawan; Muhammad Iqbal; Mochammad Rivan Akhsa; Nila Rusiardi Jayanti; Zidan Amukti Rajendra
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 3 No. 1 (2025): JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v3i1.3136

Abstract

Accurate stock price forecasting is a crucial yet challenging task due to the complex and dynamic nature of financial markets. This study employs the Prophet model to predict the stock prices of PT Sarana Menara Nusantara Tbk (TOWR) from 2021 to 2025. The research leverages historical stock data, incorporating dividend distribution dates and Annual General Meeting (AGM) events as external regressors to enhance predictive accuracy. The model was developed using machine learning-based time series forecasting, with hyperparameter tuning applied to optimize performance. The evaluation metrics indicate a Mean Absolute Error (MAE) of Rp49.92 and a Mean Absolute Percentage Error (MAPE) of 6.47%, demonstrating the model’s robustness in capturing long-term stock price trends. The findings suggest that stock prices exhibit significant movements around dividend announcement periods and AGM events, highlighting the impact of corporate actions on market behavior. This study reinforces the importance of incorporating fundamental financial indicators into forecasting models to improve decision-making for investors and financial analysts. The results offer practical implications for investment strategy formulation, risk management, and market trend analysis.
Implementasi Metode Multifactor Evaluation Process Pemilihan Guru Terbaik Pada SMP Darul Ulum Waru Berbasis Web Kapindho Febriyanto; Muhammad Fatkhur Rizal; Chamdan Mashuri; Didiek Rusdyanto
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 3 No. 1 (2025): JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v3i1.3143

Abstract

The decision support system for determining the best teachers at SMP Darul Ulum Waru aims to facilitate the selection and assessment of teacher performance. Currently, the selection of the best teachers still involves negotiations or discussions and has not yet been systematic in determining the best teachers. this process results in outcomes that appear subjective, as teacher evaluations are conducted every year in the even semester to boost the work spirit of each teacher in educating their students and to reward them for their achieved performance. To improve efficiency and accuracy, a system for selecting the best teachers is needed using the MFEP (Multifactor Evaluation Process) method, which is more flexible in determining the weight of criteria. In this method, more prioritized criteria receive greater weight and are easier to apply, making data processing faster. In the MFEP process, calculations are made using predetermined criteria, including politeness, work accuracy, orderliness, compliance, and work enthusiasm. Calculations will be conducted for each teacher based on the specified criteria and weighting, which will ultimately result in recommendations for the best teachers.In the MFEP system, the selection of the best teachers that has been created was tested 20 times manually with an accuracy of 85.88%.
Multi-Criteria Decision Support System for Web-Based Credit Approval: A Study of TOPSIS, MABAC, WASPAS, and MAUT Methods Kadek Indah Permataa; Desy Purnami Singgih Putria; Gusti Made Arya Sasmitab
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 3 No. 1 (2025): JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v3i1.3152

Abstract

The decision-making process in granting credit involves analyzing a series of alternatives using certain criteria.. The goal is to find the best alternative that meets these criteria. One method that can be used in the decision making process is Multi-Criteria Decision Making (MCDM) or Multi-Criteria Decision Analysis (MCDA). There are many MCDM or MCDA methods that can be used for decision making. This research aims to test the MCDM methods, namely TOPSIS, MABAC, WASPAS and MAUT in making decisions regarding credit acceptance. The dataset used in this research is data regarding credit acceptance with 5 criteria and 100 attributes. The method study was carried out by ranking all alternatives based on the best alternative and then comparing the ranking results of the four methods using Spearman and Kendall Tau rank correlations. And carry out sensitivity tests on the four methods to find the most sensitive method. The results of the comparison of the four methods show that there is a strong correlation between the MABAC and WASPAS methods. The sensitivity test results show that the TOPSIS method is the most sensitive method. Based on the correlation results, it can be concluded that the MABAC and WASPAS methods are the methods that produce the most similar rankings. Meanwhile, the most sensitive method is obtained by the TOPSIS method.

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