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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 Sentimen Pada Media Sosial Instagram Terhadap Akun Presiden Joko Widodo Menggunakan Metode Naïve Bayes Classifier Della Berliansyah; Ulya Anisatur; Habibatul Azizah Alfaruq
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 2 No. 2 (2024): JUNI : 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.v2i2.1895

Abstract

In the growing digital era, social media, especially Instagram, has become the main platform for people to communicate and express themselves. One of the most influential accounts is President Joko Widodo's official account, @jokowi, which is often in the spotlight with thousands of comments covering a wide range of sentiments, both positive and negative. In the midst of his popularity, sentiment analysis is key to understanding the public's views on Jokowi's leadership. This study aims to analyze public sentiment towards President Joko Widodo (Jokowi) through comments posted on his official Instagram account (@jokowi). By utilizing the Naïve Bayes Classifier method, this study collected data from 1000 comments which were then processed through various stages of the methodology, including data collection, preprocessing, weighting, k-fold cross validation, and method implementation. Through the preprocessing stage involving cleansing, stopword removal, stemming, and tokenizing, the comments were prepared for further analysis. Test results using k-fold cross validation show that the model has an average accuracy of 80.3%. In addition, evaluation using confusion matrix showed an accuracy of 84.1%, with a precision of 85.5% and recall of 92.4%. These results show that the Naïve Bayes Classifier method performs well in classifying positive and negative sentiments in the comments.
Klasifikasi Malware Menggunakan Metode Convolutional Neural Network (CNN) Berbasis Website Septian Dwi Chandra; Hardian Oktavianto; Ari Eko Wardoyo
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 2 No. 2 (2024): JUNI : 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.v2i2.1931

Abstract

This study aims to develop a web-based malware detection system using Convolutional Neural Network (CNN) utilizing the IoT23 dataset. Malware is malicious software that can exploit security vulnerabilities in computer systems, steal data, and degrade performance. The implementation of this detection system involves CNN, capable of extracting important features from both visual and textual data, applied to malware classification. The IoT23 dataset comprises 23 scenarios of IoT network traffic, including traffic from malware-infected devices. The study results show that the developed web application can detect malware attacks with accuracy, precision, recall, and F1-score of 99% on separate data scenarios. This CNN-based detection system has proven effective in identifying and classifying malware attacks, contributing to the enhancement of network and device security.
Analisis Perbandingan User Experience (UX) Pada Aplikasi Netflix Dengan Disney+ Hotstar Menggunakan Metode User Experience Questionnaire (UEQ) Adam Huda Nugraha
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 2 No. 2 (2024): JUNI : 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.v2i2.1944

Abstract

During the COVID-19 pandemic, the Indonesian government implemented measures to ensure that the people remained in their homes and did not leave without cause. This leads to dissatisfaction among the community. More and more of them spend their time using technology like games, TV, and the internet. Internet technology has significantly changed daily life, particularly in terms of information access. Online video streaming, such Netflix and Disney+ Hotstar, is becoming the primary choice for consumers. The purpose of this study is to compare user experience (user satisfaction) between the Netflix and Disney+ Hotstar apps using the User Experience Questionnaire method (UEQ). Data collection is carried out using Google Forms as a medium to get user feedback through provided questions. Data analysis is done using Data Analysis Tools (DAT). The research results show that 5 out of 6 scales (Attractiveness, Clarity, Efficiency, Accuracy, and Novelty) for the Netflix application received an assessment of ‘Above average,’ while the Stimulation and Efficiency scales received a rating of ‘Good.’ On the other hand, for the Disney+ Hotstar application, 4 out of 6 scales (Attractiveness, Clarity, Efficiency, Accuracy, and Novelty) received a rating of '.
Analisis Sentimen Masyarakat Berdasarkan Komentar Kerja Sama Tiktok Shop dan Tokopedia di Instagram Menggunakan Metode Naïve Bayes Classifier Zaenab Kurnia; Amalina Maryam Zakiyyah; Nur Qodariyah Fitriyah; Agus Milu Susetyo
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 2 No. 2 (2024): JUNI : 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.v2i2.1978

Abstract

The reopening of the Tiktok Shop and collaboration with Tokopedia has caught the public's attention. That's proven by a post on Instagram about their collaboration that received various responses. This research aims to conduct sentiment analysis to ascertain whether the public approves of the two's partnership. The Naïve Bayes Classifier method was used to analyze 641 comment data from the period 11 December 2023 to 11 February 2024. The results show the composition of positive, negative, neutral sentiment and unclassified data, as well as accuracy, precision and recall. Of the 641 data recorded, there were 269 neutral sentiment data, 194 negative sentiment data, 176 positive sentiment data, and 437 unclassified data. The Naïve Bayes Classifier model with oversampling techniques obtained an accuracy of 83%, precision of 81%, and recall of 93%.
Analisis Dan Perancangan Sistem Informasi Untuk Meningkatkan Efisiensi Pengelolaan Data Administrasi Yahfizham Yahfizham; Muhammad Daffa Fahreza
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 2 No. 2 (2024): JUNI : 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.v2i2.1983

Abstract

The application of information systems in the current era of digitalization is very important for data management in a company, both in the government and private sectors. This research aims to analyze and design information systems to improve the efficiency of administrative data management in the Office of the Governor of North Sumatra. With the lack of application of information systems in the Office of the Governor of North Sumatra, this research is important to support administrative processes and data processing efficiency. The research method includes interviews with related parties, observations, and direct surveys to the field to understand the administrative process of the obstacles faced. Furthermore, a website-based information system solution will be proposed that can improve the efficiency, speed and accuracy of administrative data management in the Office of the Governor of North Sumatra. The results of this research are expected to provide an in-depth description of how the implementation of the right information system can optimize administrative data management. The implementation of this solution is expected to provide significant benefits in improving administrative performance and opening up opportunities for further application of information technology in the local government environment.
Sistem Informasi Perpustakaan SMP HKBP Medan Berbasis Web Menggunakan Metode Framework For The Application System Thinking (FAST) Gusti Masari Pangaribuan; Nikita Br. Nababan; Bremi Br Ginting; Nita Syahputri
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 2 No. 2 (2024): JUNI : 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.v2i2.2044

Abstract

One of the key components that helps the school's teaching and learning process is the library information system. The objective of this study is to apply the Framework for the Application of Systems Techniques (FAST) approach to the design and development of an online library information system for SMP HKBP Medan. This system is expected to increase efficiency in managing book data, borrowing and returning books as well as making it easier to access information for students and school staff. The use of the FAST method in developing this system involves several stages, including feasibility studies, needs analysis, system design, implementation, and evaluation. The result of this research is a web-based library information system that is user-friendly and able to improve the performance of the HKBP Medan Junior High School library.
Deteksi Tingkat Kematangan Buah Tomat Dengan Transformasi Ruang Warna HSI Supiyandi Supiyandi; Arizka Anggraini; Warda Hamidah; Nazwa Alya Faradita; Adisty Maysandra
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 2 No. 2 (2024): JUNI : 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.v2i2.2095

Abstract

Among the vegetables most commonly consumed by people around the world are tomatoes. One of the potential vegetable commodities to be developed is tomato plants. This plant can thrive in rice fields, dry land, and highlands. Use of Technology Digital images are images that can be processed by computers directly. A matrix with M columns and N rows can be used to describe a digital image. The smallest element in an image is called a pixel or image element, and is the intersection between columns and rows. image processing is the process of processing an image numerically; in this case, each pixel or point in the image is treated. One method of image processing is to use computer software to process each pixel in the image. It is easier for object recognition applications in image processing to identify objects based on differences in hue values when the hue values of objects are limited to a certain value. The color space system that mimics the capabilities of the human eye is called the HSI color space model. HSI incorporates the grayscale or color components of an image. The test image of Tomato fruit with a value of H = 32 S = 0.675 I = 83 can be considered ripe, according to the range of fruit reference values that have been established through the use of the HSI method.
Vocabulary Learning Strategies in Learning New Words for EFL Learners Based on Gender Differences Novia Putri Riyantika; Hanafi Hanafi; Kristi Nur Aini
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 2 No. 3 (2024): SEPTEMBER : 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.v2i3.2147

Abstract

This study investigates vocabulary learning strategies (VLS) among male and female EFL learners at Muhammadiyah University Jember. Using questionnaires and interviews, the research explores gender differences in discovering and consolidating new vocabulary. The findings reveal that both genders primarily use dictionaries for discovery, with males preferring visual aids and females relying on social interactions. For consolidation, males favor spaced repetition and word lists, while females use mnemonics and narrative techniques. These insights highlight the need for differentiated instruction to accommodate diverse learning preferences.
The Effect of English Podcast on ESL Students Listening Comprehension Skills Asasi Syifa; Yeni Mardiyana; Widya Oktarini
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 2 No. 3 (2024): SEPTEMBER : 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.v2i3.2148

Abstract

This study aims to evaluate the effect of using English podcasts on the listening comprehension skills of ESL (English as a Second Language) students using a pre-experimental one-group pretest post-test design. The sample consisted of 35 ESL students. The students were given a listening comprehension test before the intervention (pretest) to measure their initial skills. During a four-week period, the students were regularly exposed to English podcasts selected based on difficulty level and relevance to the curriculum. After the intervention period, the same listening comprehension test was administered as a post-test to measure changes in listening skills. The collected data were analyzed using a paired t-test to determine the significance of the difference between pretest and post-test scores. The results showed a significant increase in students' listening comprehension scores after the podcast intervention (p < 0.05). These findings indicate that regular use of English podcasts can improve ESL students' listening comprehension skills. This study suggests that podcasts can be an effective tool in language learning, particularly in enhancing listening skills. The practical implication of this research is to encourage educators to integrate podcasts into their teaching methods. Further research is recommended to address the limitations of this study design and explore other factors that may influence the results.
Integrasi Artificial Intelegent Berbasis Sistem Operasi Android pada Smart Home Rakhmadi Rahman; Achmad Haikal Fikri; Kelsia Nelsia
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 2 No. 2 (2024): JUNI : 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.v2i2.2198

Abstract

This study explores the integration of Artificial Intelligence (AI) into smart home systems using the Android operating system to enhance security, privacy, efficiency, and user comfort. Key security measures include data encryption, robust authentication methods, sandboxing, and AI integration, specifically leveraging Google Assistant for improved privacy controls. Maintenance strategies for smart homes emphasize energy management, device condition monitoring, and enhanced safety features. AI adaptation to user habits enhances productivity and situational awareness, while Android's role in connecting various IoT devices facilitates remote control and energy-efficient recommendations. Methods such as Eco Android, Greensource, byte-code transformations, and automated energy diagnosis tools aid in optimizing energy use. The comparison between smart and non-smart homes highlights the efficiency and convenience of smart homes despite higher installation costs and potential network issues. The development and deployment of an Android-based application, SafeHause, exemplifies practical implementation, emphasizing end-to-end testing, security updates, and user education. The findings affirm that AI integration with Android significantly improves the smart home experience by enhancing energy optimization, data security, and personalized user interaction. Furthermore, the study discusses future trends in smart home technology, such as the potential for more advanced AI algorithms and machine learning techniques to provide even greater personalization and automation. The importance of regular software updates and the role of user feedback in refining smart home systems are also highlighted, ensuring that these technologies continue to evolve and meet user needs effectively.

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