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Jurnal Computer Science and Information Technology (CoSciTech)
Published by Universitas Muhammadiyah Riau
ISSN : 2723567X     EISSN : 27235661     DOI : https://doi.org/10.37859/coscitech
Core Subject : Science,
Computer Science & IT
Jurnal CoSciTech (Computer Science and Information Technology) merupakan jurnal peer-review yang diterbitkan oleh Program Studi Teknik Informatika, Fakultas Ilmu Komputer, Univeritas Muhammadiyah Riau (UMRI) sejak April tahun 2020. Jurnal CoSciTech terdaftar pada PDII LIPI dengan Nomor ISSN 2723-5661 (Online) dan 2723-567X (Cetak). Jurnal CoSciTech berkomitmen menjadi jurnal nasional terbaik untuk publikasi hasil penelitian yang berkualitas dan menjadi rujukan bagi para peneliti. Jurnal CoSciTech menerbitkan paper secara berkala dua kali setahun yaitu pada bulan April dan Oktober. Semua publikasi di jurnal CoSciTech bersifat terbuka yang memungkinkan artikel tersedia secara bebas online tanpa berlangganan.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 358 Documents
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Analisis sentimen review aplikasi mypertamina pada twitter menggunakan metode naïve bayes classifier Nabilla Saumi Putri
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4789

Abstract

Downstream and Natural Gas Regulatory Agency (BPH Migas) Pertamina launched the mypertamina application for subsidized fuel oil (BBM) such as pertalite and diesel which will then be used as a digital financial service that integrates with the link aja application to ensure the subsidised fuel distribution process is truly on target. The problem after the launch of the mypertamina application harvested many pros and cons, one of which was that the application was difficult to use, complicated to use as evidenced in the comments on Twitter. From this problem it can be used as a sentiment analysis research to find out positive comments and negative comments in the mypertamina application review. The naive Bayes classifier method was used in this study for the classification process. In this study using as many as 1001 tweet data from the data collection process sourced from Twitter consisting of 494 positive and 507 negative, in the naive Bayes classifier classification process the accuracy value is 71% with 90% training data and 10% test data
Analisis sentimen komentar youtube terhadap Anies Baswedan sebagai bakal calon presiden 2024 menggunakan metode naive bayes classifier Chely Aulia Misrun; Elin Haerani; Muhammad Fikry; Elvia Budianita
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4790

Abstract

One of the figures as a presidential candidate is Anies Baswedan, the former governor of DKI Jakarta who received many awards and has an effective work program policy for problems in the DKI Jakarta area. Many comments about Anies Baswedan as a 2024 presidential candidate are found on YouTube social media. Youtube facilitates users to provide comments in response to videos which can be used as sentiment analysis information to find out positive comments and negative comments. The algorithm used in this research is the naïve bayes classifier. There are five main processes in this research, namely data collection, text preprocessing, word weighting (TF-IDF), classification (Naïve Bayes Classifier) and testing. From 1009 comment data on Indonesian-language youtube related to the Anies Baswedan video as a 2024 presidential candidate. Based on the analysis results, there are 610 positive comments and 399 negative comments. The accuracy result using the naïve bayes classifier algorithm is 78% which is obtained by using a comparison of 90% training data and 10% test data.
Pengelompokan pembagian zakat dengan menggunakan metode clustering k-means Alvin Alvin Anzaz Islami; Elin Haerani; Novriyanto; Alwis Nazir
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4804

Abstract

Zakat merupakan ibadah yang menyangkut harta benda. Zakat juga termasuk rukun islam yang ke empat yang memiliki tujuan menyucikan harta bagi setiap muslim dengan cara menyisihkan sebagian harta kekayaannya, jika telah mencapai waktu dan besaran jumlahnya diberikan kepada orang yang berhak menerimanya. Pengumpulan dan penyaluran zakat biasanya ditangani oleh Badan Amil Zakat (BAZ) yang ada disetiap wilayah Indonesia, salah satunya di Pekanbaru. Sesuai dengan peraturan ada dua tahap yang dilakukan dalam memberikan bantuan kepada para mustahik yaitu melakukan wawancara dan observasi lapangan, kemudian menentukan nominal bantuan yang diberikan dengan kategori Mustahik penerima bantuan zakat 1, zakat 2, dan zakat 3. Masalah yang sering dijumpai dalam penentuan calon penerima bantuan adalah cara dalam pemilihan Mustahik yang masih menggunakan cara manual, sehingga sering menimbulkan masalah seperti lamanya proses pemilihan dan terjadinya salah hitung sehingga hasil seleksi Mustahik menjadi kurang akurat. Untuk itu, perlu dibuat suatu analisis yang dapat mengolah data menjadi informasi. Data mining ialah proses untuk mengolah data menjadi suatu informasi dengan teknik statistik, AI, dan machine learning. Ada banyak metode dalam data mining. Pada penelitian ini menggunakan algoritma k-means clustering dan untuk pengujian menggunakan Davies Bouldin Index. berdasarkan pengujian menggunakan davies bouldin index (DBI) klaster 4 merupakan klaster terbaik dengan nilai 0.671, dimana jika nilainya semakin rendah maka akan semakin baik klaster tersebut
Sistem Notifikasi Token Listrik Menggunakan Metode Fuzzy Tsukamoto Dengan Sms Gateway Berbasis Arduino Soni; Miftakhul Jannah; Yulia Fatma
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4839

Abstract

Rapidly developing technological advances have encouraged the emergence of various increasingly sophisticated electrical measurement equipment, including the Kilo Watt Hour meter (KWH). The weakness of this KWH meter system is that the warning system is only in the form of indicator lights and buzzer alarms which are often ignored by users and their range is limited. Users who are outside the home also cannot know the condition of electricity at home. So an electricity token notification system is needed to make it easier for users. This tool is designed by utilizing Arduino Uno, SIM 800L, Potentio. SIM 800L is used to send SMS notifications and Potentio to simulate the number of electricity tokens. In this tool Tsukamoto Fuzzy method is applied to determine the output condition based on the input value. The purpose of designing this tool is to improve the KWH meter warning system so that it can reach users outside the home.
Perencanaan strategis sistem informasi/teknologi informasi menggunakan metode TOGAF pada PT. BukaKios Teknologi Indonesia Edo Arribe; Aryanto; Riri Angraini
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4637

Abstract

Perencanaan strategis sistem dan teknologi informasi merupakan upaya yang diperlukan untuk memastikan bahwa sistem dan teknologi yang diusulkan perusahaan selaras atas kepentingan bisnis perusahaan. PT. BukaKios Teknologi Indonesia hadir untuk membantu para pebisnis pulsa dan Payment Point Online Bank (PPOB) dalam penyediaan berbagai produk digital yang biasa dibutuhkan masyarakat. Akan tetapi, dalam prakteknya masih terdapat penerapan sistem maupun teknologi perusahaan yang tidak dan belum sinkron dengan harapan PT. BukaKios Teknologi Indonesia. Maksud penelitian ini yaitu merancang perencanaan strategis yang terintegrasi dengan metode the open group architecture framework (TOGAF) yang dapat diimplementasikan pada PT. BukaKios Teknologi Indonesia. Hasil penelitian ini diharapakan dapat membantu mengimplementasikan sistem dan teknologi yang belum diterapkan pada PT. BukaKios Teknologi Indonesia.
Perencanaan Strategis SI/TI Menggunakan Analisis Ward & Peppard Pada Toko Trubus Pekabaru Aryanto; Edo Arribe; Tengku Muhammad Zainul Aprilizar
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4640

Abstract

Toko Trubus is a company that wants to invest in IS in the form of software development for its strategic business needs by using outsourcing services. Using information systems and information technology can improve business strategy. This analysis is useful for designing IS/IT that produces the output of a portfolio of software applications that best suit the conditions or needs of the company in achieving goals based on the vision and mission. Therefore, research using the Ward & Peppard method is expected to obtain optimal results in accordance with the objectives of this company's business strategy. It is hoped that this framework can improve the company's management process by managing information better in the future. This Ward & Peppard methodology is a methodology in which there are several diagrams that will help how to understand an organization or company, with an IS/IT strategic plan, so that it has an impact on future plans.
The Implementation of Artificial Neural Networks to measure the correlation of teacher's workload to the number of own learning media Erizke Aulya Pasel; Yuhandri Yuhandri; Gunadi Widi Nurcahyo Nurcahyo
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4757

Abstract

The use of learning media in the teaching and learning process is an effort to increase the effectiveness and quality of the learning process. However, the need for learning media is not compatible with the number of learning media made by the teacher himself. One of the factors that causes it is the teacher's workload which is quite a lot so that the teacher does not have enough time to make his own learning media. This study aims to measure the extent of the correlation between the teacher's workload and the amount of instructional media that the teacher himself made. Artificial Neural Network with Backpropagation method is a tool that can be used to solve complex problems, one of which is to measure the level of correlation. The ability of an Artificial Neural Network with the Backpropagation method to adapt to changes that occur in the input and output values makes the prediction accuracy quite high. The teacher's workload variables used are the number of face-to-face hours of even and odd semesters, additional assignments (deputy principal/head of laboratory), homeroom teacher, and extracurricular coaches. The target used is the number of learning media made by the teacher himself. The data used in this study were taken from the workload of teachers at SMAN 4 Payakumbuh in 2022. The architectural patterns used are 5-4-1, 5-5-1, 5-7-1, 5-10-1, and 5- 12-1. From the test results with the Matlab R2013a software, the best pattern was obtained, namely the 5-12-1 pattern with an MSE value of 0.1001, a MAPE of 2.11, and a data accuracy of 97.89%. From the results of the training and testing, it was concluded that the correlation between the teacher's workload and the amount of self-made learning media is very low or not closely related.
Analisis perbandingan tools mobile forensic menggunakan metode national institute of justice (NIJ) Mualfah, Desti; Muhammad Iqbal Syam; Baidarus
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4767

Abstract

Media sosial sebagai salah satu aplikasi pesan singkat berbasis online dan sangat populer dikalangan masyarakat khususnya di Indonesia. Salah satu aplikasi media sosial terpopuler adalah Signal Messenger. Kepopuleran penggunaan aplikasi ini dipengaruhi karena kekhawatiran dan kepedulian dalam menjaga informasi pribadi masing-masing penggunanya. Aplikasi pesan instan seringkali disalahgunakan pada momen kejahatan dunia maya atau dikenal dengan istilah cybercrime. Pada penelitian telah dilakukan perbandingan kinerja dari dua forensic tools yaitu Oxygen Forensic Detectivedan Belkasoft Evidence Center, yang digunakan untuk mengembalikan data yang telah dihapus, dan barang bukti digital lainnya pada skenario kasus transaksi jual beli narkoba. Metode investigasi dalam penelitian mobile forensic ini menggunakan National Institute of Justice (NIJ), yang terdiri atas lima tahapan antara lain identification, collection, examination, analysis, dan reporting. Dari hasil analisis pada pencarian 6 bukti digital pada file physical image ‘mmcblk0’, menggunakan tool mobile forensic Oxygen Forensic Detective, didapatkan sebanyak 5 dari 6 total bukti digital dengan pencapaian nilai 83.33%. Sedangkan tool mobile forensic Belkasoft Evidence Center, mendapatkan sebanyak 4 dari 6 total bukti digital dengan pencapaian nilai 66.67%. Penggunaan kedua tools tersebut telah berhasil mendapatkan bukti digital, yang digunakan pada skenario kasus transaksi jual beli narkoba, pada barang bukti perangkat smartphone android Samsung Galaxy J2 Prime.
Klasifikasi Multi-Class Penyakit Jantung Dengan SMOTE dan Pearson’s Correlation menggunakan MLP Rahmad Firdaus; Desti Mualfah; Julian Silvia Hasanah
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4769

Abstract

Penyakit jantung merupakan penyakit paling mematikan didunia. Laporan WHO tahun 2019 menyebutkan penyakit jantung sebagai penyebab kematian tertinggi didunia dengan persentase 16% dari jumlah kematian atau 8.9 juta kematian. Tingginya kematian yang disebabkan oleh penyakit ini terjadi karena penyakit ini biasanya timbul tanpa adanya gejala sehingga sulit untuk diketahui sejak dini oleh penderita. Salah satu cara untuk mengatasi permasalahan tersebut adalah dengan pemanfaatan metode klasifikasi. Hasil klasifikasi multi-class pada penelitian sebelumnya dengan dataset dan metode yang sama masih terbilang rendah yang salah satunya disebabkan oleh adanya imbalace data. Untuk itu dibutuhkan teknik balancing data serta feature selection (FS) untuk melihat pengaruh imbalance data dan pengaruh korelasi fitur pada klasifikasi multi-class. Pada penelitian ini menggunakan Synthetic Minority Over-sampling Technique (SMOTE) untuk balancing data dan Pearson’s Correlation (PS) untuk memilih fitur dengan korelasi yang baik pada klasifikasi penyakit jantung menggunakan metode Multi-Layer Perceptron (MLP). Penelitian ini dengan MLP+Pearson’s Correlation hanya mendapatkan akurasi tertinggi sebesar 63.33%. Akurasi tertinggi dengan penggabungan metode MLP+SMOTE+Pearson’s Correlation sebesar 92.5%. Serta akurasi tertinggi pada penelitian ini didapat menggunakan metode MLP+SMOTE yaitu sebesar 97.5%.
Implementasi Naïve Bayes Dalam Analisis Sentimen Masyarakat pada Twitter Terhadap Flash Sale Shopee Doni Winarso; Ilham Kurniawan
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4779

Abstract

Rumors spread among the public that there was fraud occurring during the ongoing flash sale Shopee process. In order to answer the problems found, this study aims to find out how the public feels about the flash sale activity. Data was taken using the Twitter API, and the tweets used started from January 2021–June 2021. As a result, there were 3,467 Twitter data points. After passing through the text preprocessing stage, the data becomes clean data, which amounts to 457. The research results obtained using the Nave Bayes Classifier method show the results of public opinion on Twitter with positive sentiment categories of 19.4%, negative sentiment categories of 43.1%, and neutral sentiment categories of 37.4%, with an accuracy rate of 98%.

Page 13 of 36 | Total Record : 358

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