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Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika)
Published by Sekolah Tinggi Ilmu Komputer Tunas Bangsa
ISSN : 25275771     EISSN : 25497839     DOI : 10.30645
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
JURASIK adalah jurnal yang diterbitkan oleh LPPM STIKOM Tunas Bangsa Pematangsiantar yang bertujuan untuk mewadahi penelitian di bidang Sistem Informasi dan Teknik Informatika. JURASIK (Jurnal Riset Sistem Informasi dan Teknik Informatika) adalah jurnal ilmiah dalam ilmu komputer dan informasi yang mengandung literatur ilmiah pada studi murni dan penelitian terapan dalam ilmu komputer dan informasi dan ulasan publik pengembangan teori, metode dan ilmu terapan yang berkaitan dengan subjek. Jurnal ini pertama kali mendapat ISSN dengan nomor 2527-5771 pada tahun 2016 untuk terbitan cetak dan mulai 2017 beralih ke terbitan elektronik dengan nomor ISSN 2549-7839. Pengiriman artikel tidak dipungut biaya, kemudian artikel yang diterima akan diterbitkan secara online dan dapat diakses secara gratis. JURASIK (Jurnal Riset Sistem Informasi dan Teknik Informatika) adalah sebuah jurnal peer-review secara online yang diterbitkan bertujuan sebagai sebuah forum penerbitan tingkat nasional di Indonesia bagi para peneliti, profesionaldan praktisi dari industri dalam bidang Ilmu Kecerdasan Buatan. JURASIK (Jurnal Riset Sistem Informasi dan Teknik Informatika) menerbitkan hasil karya asli dari penelitian terunggul dan termaju pada semua topik yang berkaitan dengan ilmu komputer. JURASIK (Jurnal Riset Sistem Informasi dan Teknik Informatika) terbit 1 (satu) nomor dalam setahun. Artikel yang telah dinyatakan diterima akan diterbitkan dalam nomor In-Press sebelum nomor regular terbit. JURASIK (Jurnal Riset Sistem Informasi dan Teknik Informatika) telah terindeks Google Scholar, Garuda, Crossref dan terus akan diupdate mengikuti perkembangan. Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) telah melakukan perubahan jumlah terbitan dari 1 x setahun (Juli) menjadi 2 x setahun (Februari dan Agustus) dan telah melakukan perubahan data administrasi pada laman LIPI dengan url: http://u.lipi.go.id/1480905139. Topik dari jurasik adalah sebagai berikut (namun tidak terbatas pada topik berikut) : Artificial Intelligence, Digital Signal Processing, Human-Computer Interaction, IT Governance, Networking Technology, Optical Communication Technology, New Media Technology, Information Search Engine, Multimedia, Computer Vision, Information System, Business Intelligence, Information Retrieval, Intelligent System, Distributed Computing System, Mobile Processing, Computer Network Security, Natural Language Processing, Business Process, Cognitive Systems, Software Engineering, Programming Methodology and Paradigm, Data Engineering, Information Management, Knowledge-Based Management System, Game Technology.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 403 Documents
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Penjadwalan Roster Kuliah Menggunakan Metode Welch-Powel Zulfa, Ira; Septima, Richasanty; Syaputra, Hendri; Eliyin, E; Salim, S
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 2 (2024): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i2.824

Abstract

Optimal lecture scheduling is an important challenge in higher education institutions, including the Faculty of Engineering, Gajah Putih University. Manually done scheduling often leads to schedule clashes that hinder learning effectiveness. This study aims to overcome this problem by implementing the Welch-Powel graph coloring method in the scheduling system. This method sorts courses by priority and provides coloring to avoid schedule clashes. A literature study was conducted to identify the problem, followed by data collection using questionnaires and interviews. The data obtained is processed in the form of a matrix and represented as a graph. Implementation is carried out in the form of software that is tested to ensure its accuracy and effectiveness. The results show that the Welch-Powel method is effective in producing an optimal lecture schedule and reducing conflicts. The conclusion of this study suggests the use of graph-based scheduling systems to improve scheduling efficiency in the faculty
Perancangan UI/UX Sistem Informasi Perpanjangan Surat Tanda Nomor Kendaraan Menggunakan Metode Design Thinking (Kasus Samsat Kota Kendari) Pamula, Bonifasis; Bangkalang, Dwi Hosanna
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 2 (2024): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i2.791

Abstract

SAMSAT (One-Stop Administration System) is one of the services with a series of services in activities aimed at identification to registration of motor vehicles. Through the service of extending the Motor Vehicle Number Certificate (STNK) provided both in offices and vehicles operating around, several obstacles were found related to the service process carried out, such as: the lack of information related to the completeness of files in extending STNK which makes visitors' time when managing STNK renewal erratic, causing queues. Based on these obstacles, the author conducted research on the topic of UI / UX Design of Motor Vehicle Number Extension Information System at SAMSAT Kendari City with the aim of designing a UI / UX Information System for Extension of Motor Vehicle Number Certificate Online. This design process requires a survey related to users to focus the problem so as to be able to define new ideas based on the solutions obtained, therefore this research will use the Design Thinking method. The stages in carrying out the Design Thinking method consist of 5 stages, namely: Empathize, Define, Ideate, Prototype, and Testing so as to assist the author in conducting research starting from the first stage of distributing questionnaires, finding and identifying problems, providing solution ideas, making prototype designs, to simulating prototypes using Single Ease Questions (SEQ) consisting of values 1 to 7 as an assessment tool from the user's point of view in running.  interact with the system. The conclusion of this study obtained an average score on prototype testing between 5.32 to 6.66 from 50 related respondents. It can be stated that the resulting design can be accessed easily and answer the needs of the user.
Comparative Analysis of Machine Learning Models for Predicting Electric Vehicle Range Airlangga, Gregorius
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 1 (2024): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i1.740

Abstract

This research presents a comprehensive analysis of various machine learning models to predict the electric range of electric vehicles (EVs). In the context of growing environmental concerns and the push for sustainable transportation, accurate prediction of EV range is crucial for consumer trust and wider adoption. We evaluated five different models: Linear Regression, Ridge Regression, Lasso Regression, Random Forest Regressor, and Gradient Boosting Regressor, using a dataset that included a diverse array of EV attributes. The primary evaluation metric was the Mean Squared Error (MSE), applied both in cross-validation and on a test set. Our findings revealed significant differences in performance between linear models and ensemble methods. Linear models, while computationally efficient and interpretable, showed modest predictive capabilities, likely limited by their inability to capture complex, non-linear relationships in the data. Notably, Lasso Regression exhibited the highest error rates, possibly due to its feature exclusion in regularization. In contrast, ensemble methods, particularly the Random Forest Regressor and Gradient Boosting Regressor, demonstrated superior performance, effectively modeling non-linear relationships and intricate feature interactions. This study underscores the importance of model selection in predictive tasks, highlighting that more complex models, such as ensemble methods, are often more suitable for datasets with multifaceted interactions and non-linearities. The results of this research contribute to the evolving field of electric vehicle technology, providing insights that can guide future developments in EV range prediction, a key factor in the advancement of sustainable transportation. This research aids in understanding the application of machine learning in EV range prediction and lays the groundwork for future exploration, potentially incorporating real-time data and external factors for enhanced accuracy.
Penerapan Metode Least Square Dalam Memprediksi Penjualan Mie Instan Siregar, Dodi; Irwanda, Fikri Dio; Dafitri, Haida
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 8, No 2 (2023): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v8i2.708

Abstract

Instant noodles are a food product made from wheat flour or wheat flour with or without the addition of other permitted food ingredients and additives. Instant noodles are popular because they taste delicious, are a practical way to cook and also have an affordable price. Instant noodles are one of the products that are often sold at Elvi stores. In fact, sales of instant noodle products at Elvi stores are erratic. This is because instant noodles are often an alternative food when people are reluctant to cook. The problem with Elvi's shop is that it cannot determine the stock of instant noodles to store which will then be sold more to the public. To minimize losses and maximize profits, a prediction system for instant noodle sales in the coming months is needed. The method used is the Least Square method which is processed based on sales trends. Based on the instant noodle prediction results using the Least Square method on sales data for the period January 2022 to August 2022, the prediction results achieved the highest accuracy of 99% and the lowest accuracy of 85%.
Advanced Deep Learning Models For Emotion Detection In Speech: Applying The Ravdess Dataset Aryono, Gagah Dwiki Putra; Ferawati, Dede; Auliana, Sigit
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 2 (2024): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i2.815

Abstract

This study introduces a comprehensive approach to emotion recognition in speech using the Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS). The method integrates several state-of-the-art deep learning models known for their proficiency in pattern recognition and audio processing. The RAVDESS dataset comprises diverse audio files featuring emotional expressions by professional actors, meticulously categorized by modality, emotion, intensity, and other attributes. These data are utilized to train and evaluate various deep learning architectures including AlexNet, ResNet, InceptionNet, VGG16, and VGG19, as well as recurrent neural network (RNN) models such as LSTM and the latest transformer models. The analysis results indicate that the Transformer model excels with higher accuracy, precision, recall, and F1 score in emotion classification tasks compared to other models. This study not only enhances understanding of subtle emotional nuances in spoken language but also establishes new benchmarks in applying diverse neural network types for emotion recognition from audio. By providing detailed comparisons among models, this research advances the technology of emotion recognition, enhancing its applications in human-computer interaction, psychotherapy, entertainment industry, and paving the way for further development in multimodal emotion recognition systems.
Analisis Perbandingan Compute Engine dan Cloud Run sebagai lingkungan Pengembangan Aplikasi Web di Google Cloud Platform Kejora, Cahyo Bintang; Susetyo, Yeremia Alfa
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 1 (2024): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i1.756

Abstract

Cloud computing has become a significant issue in the world of Information and Communication Technology. A leading retail company in Indonesia, PT XYZ, faces challenges in choosing cloud computing services for their application development and operations. The company is faced with a choice between Compute Engine and Cloud Run on Google Cloud Platform. This research aims to analyze the comparison between the two services. By designing a web application which will then be deployed on the two cloud services, a comparative analysis of the applications deployed on the two services will then be made. Based on the test results and analysis carried out in this research, Cloud Run stands out in various aspects. From a cost perspective, the setup and performance of Cloud Run offers significant advantages compared to Compute Engine. Thus, this research concludes that Cloud Run is a more optimal choice for PT XYZ in the context of web application development, providing an efficient and economical solution.
Rancangan Bangun CRM Operasional Penerimaan Mahasiswa Pada Prodi Kesehatan Di Kampus STIKES Hakli Aprilla, Kartika Trisya; Suhari, Yohanes
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 2 (2024): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i2.838

Abstract

In the era of globalization, the use of information technology has become increasingly important, especially in higher education. STIKES Hakli faces the need to enhance its new student admission process to address intense competition and high expectations from prospective students regarding access and information. Implementing a Customer Relationship Management (CRM) system is considered an effective solution. This study aims to design and implement an operational CRM system to improve the efficiency and effectiveness of the new student admission process at the Health Study Program of STIKES Hakli. Utilizing Extreme Programming (XP) methods and a qualitative approach, the research designs a CRM subsystem that includes Login for secure access, digital Registration with validation, automated Selection with real-time dashboards, and Data Verification for accuracy. The system also features transparent Announcement of selection results, secure Data Management, and Communication and Support with FAQs and support channels. The study's results indicate that the implementation of the operational CRM system enhances efficiency by accelerating data processing and accuracy, simplifies data management, improves interactions between prospective students and the institution, and increases satisfaction with the services provided, thereby positively contributing to the new student admission process.
Perancangan Aplikasi Mobile Sig Untuk Pemantauan Sebaran Penyakit Di Kabupaten Cianjur Somantri, S; Hermanto, H; Darmawan, Muhammad Rifqi
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 2 (2024): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i2.806

Abstract

Cianjur Regency is one of the districts with the largest population in West Java. Therefore, this research proposes designing a Geographic Information System (GIS) mobile application in an effort to increase the effectiveness of monitoring the spread of disease in Cianjur Regency. This research uses a waterfall-based software development methodology which includes analysis, design, implementation, testing and maintenance stages. At the analysis stage, overall system requirements are determined, including by determining software and hardware requirements. The design stage involves creating data flow diagrams and user interface design. The implementation was carried out using Android-based mobile development technology using Kotlin Jetpack Compose and Laravel. This application is equipped with main features such as an attractive display, an interactive map that displays the distribution of disease cases along with education about each disease. Application testing is carried out using the Black Box and Posman testing methods to ensure that each function runs according to predetermined specifications. Test results show that this application can facilitate monitoring the spread of disease quite well. Apart from that, it is hoped that this application will help the government and health workers to take appropriate action to prevent the further spread of disease and for local communities to be able to find out what phenomena are occurring in their area along with education about the disease.
Evaluasi Responsivitas dan Akurasi: Perbandingan Kinerja ChatGPT dan Google BARD dalam Menjawab Pertanyaan seputar Python Heryanto, Yayan; Fauziah, F; Farahdinna, Frenda; Wijanarko, Sigit
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 1 (2024): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i1.731

Abstract

This reseach aims to evaluate the responsiveness and accuracy of two natural language processing systems, namely ChatGPT and Google BARD, in answering questions related to the Python programming language. The evaluation is conducted using the Bleu Score metric as an indicator of the accuracy of answers generated by both systems. This research involves experiments with various Python-related questions to measure the level of alignment with expected reference answers. The results indicate that the average Bleu Score for ChatGPT is 0.0088, while the average Bleu Score for Google BARD is 0.0073. Additionally, the response time for ChatGPT is recorded at 12.05 seconds, whereas Google BARD has a response time of 18.38 seconds. Although there is a small difference in accuracy, ChatGPT shows a slightly higher Bleu Score and faster response time compared to Google BARD. The conclusion of this research states that, in the context of answering questions related to the Python programming language, ChatGPT performs slightly better than Google BARD, measured in terms of answer accuracy and response time.
Implementasi QoS dengan Kombinasi Queue tree dan Dynamic Queue Untuk Meningkatkan Kualitas Jaringan (Kasus Balai Desa Sera, Kab. MBD) Aitiameru, Hendra; Christianto, Erwien
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 2 (2024): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i2.796

Abstract

This study delves into the implementation of Quality of Service (QoS) through the synergistic integration of Queue tree and Dynamic Queue mechanisms aimed at enhancing network quality. QoS plays a pivotal role in ensuring optimal network performance by effectively managing and prioritizing various types of network traffic. The Queue tree method offers a hierarchical approach to traffic management, while the Dynamic Queue method enables adaptive allocation of network resources based on real-time network conditions. Through comprehensive implementation and testing within a simulated network environment, this research demonstrates the efficacy of combining Queue tree and Dynamic Queue techniques in bolstering network performance. The results underscore the significance of this integrated approach in providing tailored prioritization of diverse service types and dynamically adjusting resource allocation, thereby substantiating its viability as a solution for augmenting network quality.

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