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Journal of Computer Science and Informatics Engineering (J-Cosine)
Published by Universitas Mataram
ISSN : 25408895     EISSN : 25410806     DOI : -
Core Subject : Science,
Computer Science & IT
Journal of Computer Science and Informatics Engineering (J-Cosine) is a journal that is published by Informatics Engineering Dept., Faculty of Engineering, University of Mataram (Program Studi Teknik Informatika, Fakultas Teknik Universitas Mataram) under online and print ISSN: 2541-0806 and 2540-8895, respectively J-Cosine is also blind and peer-reviewed journal, which the reviewer processes are carried out by at least 2 reviewers who are decided by associate editor. The J-Cosine is published bi-annually.
Arjuna Subject : -
Articles 159 Documents
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Rancang Bangun Sistem Informasi Baitulmal “Masjid Jalan Cahaya” Berbasis Website Menggunakan Metode Service Oriented Architecture (SOA): Website-Based Design Of Baitulmal Information System “Masjid Jalan Cahaya” Using Service Oriented Architecture (SOA) Method Sekarsari Bintang Solehah; Noor Alamsyah; Sri Endang Anjarwani
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 8 No 1 (2024): Juni 2024
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v8i1.558

Abstract

Aside from being a center of worship, the mosque can also function as a place to carry out social muamalah worship. Based on the function, of course the mosque has an agenda or charity activities that are held at certain times. It is the same with the fundraising or crowdfunding system run by Baitulmal "Masjid Jalan Cahaya". In its application, the information distributed on social media has not been modified on one platform, there is overlap between program uploads with one another, this is of course an obstacle for donors to find out which mosque programs are running. To answer these needs, this research builds a website-based Baitulmal information system "Masjid Jalan Cahaya" using the Laravel framework which is expected to be a means for mosques to convey all information about costs or funds needed more broadly, quickly, safely, real-time and transparent. In its development, the Baitulmal information system "Masjid Jalan Cahaya" will be integrated with other mosque websites, such as mosque company profiles, Rumah Qur'an and Baitul muamalah mosques, so that continuous system development is needed that makes it easier for each field to carry out data transactions. Departing from this, this information system applies the Service Oriented Architecture (SOA) approach, where this approach develops software using services. In this study, 3 main services were obtained, namely Charity services, Reports, and Tags/Categories. As well as service users for admin, payment and management files which are additional to the baitulmal website. For scalability testing, the System Usability Testing method was used which obtained a result of 87% in the Best Imaginable category, indicating that this system has good quality to use..
Analisis Kebutuhan Dataset Algoritma Speech To Text Bahasa Sasak Menggunakan Perbandingan Data Suara Bahasa Inggris Pada Metode CNN: Analysis of Sasak Language Speech To Text Algorithm Dataset Requirements Using English Voice Data Comparison on CNN Method Widya Bayu Pratiwi; Arik Aranta; Gibran Satya Nugraha
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 7 No 2 (2023): Desember 2023
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v7i2.568

Abstract

Currently, there have been many studies on speech recognition or speech to text. Speech to text is a technology used to convert human speech or voice and translate it into written text. Some speech to text research that has been done, has obtained an accuracy rate of up to 95% with English datasets using the Mel Frequency Coefficient (MFCC) feature extraction method and the Convolutional Neural Network (CNN) classification method. This research will apply similar algorithms, namely MFCC and CNN by displaying the training process and the resulting accuracy in its processing with an analysis scenario using datasets in multiples of 50, 150, 250, and 350 voice data. The results obtained have achieved 95% accuracy on the training data of 350 English voice data. The analysis carried out is to find the best composition on the Sasak language dataset by comparing the accuracy of the test results with the accuracy of the previous training results on the English dataset. From the training and testing process that has been carried out, the results obtained show that the best dataset composition for Sasak language is with nine speakers. This illustrates that the Sasak language requires less human resources compared to the English dataset which involves more than 30 speakers in 50 words. This has a positive impact on saving resources and time required in the development of Sasak language speech recognition system.
Implementation of an Information System for Transaction Data Analysis Using the Holt-Winters Method Murpratiwi, Santi Ika; Rukmi Sari Hartati; Made Sudarma
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 7 No 2 (2023): Desember 2023
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v7i2.573

Abstract

Decision-making errors are fatal in company operations and often result in reduced profits. In making the right decisions, in-depth internal and external data analysis is required. One effort to increase decision-making accuracy is to apply a forecasting algorithm for existing transaction data. This research uses data mining and Forecasting for car repair companies. The information system being built is expected to be able to display a list of satisfied customer data, group transaction data based on the level of damage, and provide forecasts for the number of panels, number of units, and total revenue for the next period. From this data, it will be easier for management to determine the number of workers, additional tools, and stock of materials for the vehicle repair process. This information system was built by applying three algorithms, namely C4.5, K-Means, and Holt Winter Multivariate. The C4.5 algorithm will help group customer types, K-Means will help cluster vehicle damage levels, and Holt-Winters will be used for experience. The tests carried out included testing the accuracy of each algorithm, the black box system, and the system time so that the accuracy results were 100% for the C4.5 classification algorithm and 92.28% for the accuracy of K-Means which was tested with the purity measure. Meanwhile, the MAPE value for forecast testing was between 9 – 11% for each forecast.
User Requirement Analysis dalam penerapan metode User Centered Design sebagai pendukung kebutuhan UI/UX dalam aplikasi NTB Mall Agitha, Nadiyasari; Ario Yudo Husodo; Fitri Bimantoro
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 7 No 2 (2023): Desember 2023
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v7i2.576

Abstract

User requirement analysis merupakan satu hal yang penting dilakukan dalam pembuatan sebuah user interface/user experience (UI/UX) menggunakan metode User Centered Design (UCD). Hal ini dikarenakan pada tahapan ini terdapat identifikasi dan dokumentasi kebutuhan pengguna. NTB mall adalah e-commerce pertama milik pemerintah daerah NTB dengan tujuan menjual produk unggulan daerah dari Usaha Mikro, Kecil Menengah (UMKM), Pedagang Kaki Lima (PKL) dan dibantu dengan pemantauan oleh Kelompok Sadar Wisata (Pokdarwis). Dalam pembuatan UI/UX NTBMall, diperlukan user requirement analysis yang kuat untuk mendapatkan penggunaan NTBMall yang sesuai dengan kebutuhan pengguna. User requirement analysis dibagi menjadi beberapa tahapan secara berurutan. Penggunaan user requirement analysis telah terbukti menghasilkan UI/UX yang menarik, dibuktikan dengan hasil pengujian SUS bernilai 72.82 yang mengartikan bahwa user telah puas dengan aplikasi NTBMall.
Implementasi GNU Privacy Guard (GPG) Hybrid Encryption untuk Meningkatkan Keamanan Informasi pada Layanan Electronic Signature (E-Sign) Universitas Mataram Mardiansyah, Ahmad Zafrullah; Zubaidi, Ariyan; Jatmika, Andy Hidayat; Huwae, Raphael Bianco
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 8 No 1 (2024): Juni 2024
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v8i1.593

Abstract

Electronic signatures have been widely used for administrative purposes since 2020, especially when activities from home are a priority. University of Mataram is one of the state universities that provides electronic signature facilities (E-Sign) for its academic community. The ease of using E-Sign has its own obstacles, one of which is in terms of security protection. Protection in the information security system has a role to take preventive action if the worst scenario occurs to the information system, such as unauthorized access by hackers. Naturally, each signature has been given information related to several things, namely who signed, when it was signed, information for signature purposes, and hash values that can be used to ensure the integrity of the data from the signature. When unauthorized access occurs, hackers can create an identity using the identity of a particular person. This makes E-Sign validation difficult and potentially misused. In this study, a scheme for securing user identity is proposed using GNU Privacy Guard (GPG) to encrypt E-Sign data. The encryption process is carried out with two layers of public-private key cryptography combined with the PGP Key Server.
Studi Pengembangan Sistem Pengenalan Individu Sapi Berbasis Biometrik Muzzle Menggunakan Model Mobilenetv2: Study on the Development of Cattle Individual Recognition System from Muzzle Images Based on MobileNetV2 Model Giri Wahyu Wiriasto; Misbahuddin; Rachman, A. Sjamjiar; Iqbal, Muhamad Syamsu; Budiman, Djul Fikry; Akbar, Lalu Ahmad Syamsul Irfan; Hartawan, Bagi; Wicaksono, Eko Prasetyo
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 8 No 1 (2024): Juni 2024
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v8i1.594

Abstract

In general, in cattle farming, individual identification is often done using text numbers on the cattle's ears, which is considered efficient. However, field observations reveal limitations of this technique, particularly in terms of data redundancy and new registration validation. Sometimes, errors can occur when cattle identity numbers are exchanged between the farm and the livestock market. Therefore, an intelligent biometric identification system attached to each cattle, such as the pattern on the muzzle, similar to human fingerprints, is needed. In this study, we collected and published primary cattle muzzle data as a dataset in a cloud repository. We also implemented the use of muzzle image data with a convolutional neural network algorithm in TensorFlow as a step for further development. The recognition implementation using the MobileNetV2 architecture resulted in an 83% accuracy rate for 30 individual cattle classes out of a total of 210 primary dataset divided into training and testing data.
Metoda Kombinasi Modulasi Pergeseran Tingkat Lebar Pulsa dengan Variabel Frekuensi Pembawa Pada Inverter Model Jembatan: Combination Method Of Level Shift Pulse Width Modulation With Carrier Frequency Variables On A Bridge Model Inverter Wiryajati, I Ketut; I Nyoman Wahyu Satiawan; Ida Bagus Fery Citarsa; I Made Budi Suksmadana; Supriono
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 8 No 1 (2024): Juni 2024
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v8i1.595

Abstract

Switching is very important in energy conversion systems. The conversion process requires a good and reliable method. This research identifies methods or techniques for pulse width modulation. This technique proposes a new model of modulation technique, namely by combining level shifted modulation techniques, and adjusting the frequency in such a way that it produces a signal that suits the inverter's needs. The inverter tested in this research is an inverter with a bridge model configuration. The proposed research and methods were verified using MATLAB and Simulink software. The results obtained are the ratio of total harmonic distortion (THD) are 25.07%, 76, 66% and 9.183%, respectively
Sentiment Analysis on the Impelementation of the 2024 Presidential Election on X Application Using Naive Bayes and Support Vector Machine (SVM) Methods Dewa, I Dewa Made Aditya Prasantasya; Ida Bagus Ketut Widiartha; Santi Ika Murpratiwi
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 8 No 1 (2024): Juni 2024
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v8i1.597

Abstract

This article discusses sentiment analysis of the 2024 Presidential Election through data collected from platform X, this research aims to identify and classify positive, negative, and neutral sentiments in X related to the election. This research uses scoring and textblob methods. Where the scoring method is the process of deeply analyzing sentiment and then giving the sentiment value of each data comment and accumulating it. While the textblob method is a tool used specifically for text processing that can provide sentiment for each comment. The results of the analysis provide in-depth understanding of the responses and views of the community manifested in digital space. Sentiment analysis can serve as a guide to understanding the dynamics of public opinion during the election process and its potential to influence public participation and trust in the democratic system. The practical implications of this research include the development of more effective political communication strategies based on an understanding of the sentiments that develop on X.
Analysis of Android Malware "Undangan Pernikahan.Apk" Using Static and Dynamic Methods Muhammad Syafa Asgani; Raphael Bianco Huwae; Andy Hidayat Jatmika
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 8 No 1 (2024): Juni 2024
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v8i1.599

Abstract

This research aims to analyze Android malware "UndanganPernikahan.apk" using static methods with reverse engineering techniques and dynamic analysis. The analysis process uses several tools to understand the characteristics, behavior, and impact of the malware after installation on an Android device. The research shows that this malware covertly steals user credentials through several vulnerabilities. The "UndanganPernikahan" malware is a type of spyware disguised as a wedding invitation and runs in the background without the user's knowledge. To avoid similar malware infections, it is recommended to always update the system and applications, only download applications from trusted sources, and conduct digital security training.
Comparison of ARIMA and Machine Learning Methods for Predicting Urban Land Surface Temperature in Jakarta Suhendi, Brigitta Aurelia Putri; Pratiwi, Pratiwi; Prayoga, Suhendra Widi; Kartiasih, Fitri
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 8 No 2 (2024): Desember 2024
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v8i2.579

Abstract

Climate change is a global challenge that requires serious attention from various parties, including the government. The existence of surface temperature and various other parameters is certainly closely related to climate change. In this context, this study was conducted to identify the best model in predicting urban land surface temperature in the Jakarta area, as one of the steps to understand and deal with the impacts of climate change. The research data used comes from MERRA-2, NASA, which provides datasets for various climate analyses. A comparison of ARIMA, SVR, LSTM, and ANN methods was conducted to evaluate the performance of each model in forecasting land surface temperature. The results show that the Long-Short Term Memory (LSTM) model provides the best performance with MAPE and values of 0.8381 and 0.8628. This model has an advantage over other models because it can remember various information that has been stored for a long period of time and can delete irrelevant information. This shows that LSTM is effective in capturing the pattern and variability of the Earth's surface temperature in the Jakarta area. Based on these findings, the government is expected to take concrete steps to address the impacts of climate change, especially issues related to increasing urban land temperature in Jakarta, such as reducing the use of private vehicles and switching to public transportation, expanding green open space, and relocating residents to reduce density.

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