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Contact Name
-
Contact Email
coscitech@umri.ac.id
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+6285225539224
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coscitech@umri.ac.id
Editorial Address
Program Studi Teknik Informatika Fakultas Ilmu Komputer Gedung Rektorat Lt. 4, Universitas Muhammadiyah Riau Jl. Tuanku Tambusai, Pekanbaru, Riau
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Kota pekanbaru,
Riau
INDONESIA
Jurnal Computer Science and Information Technology (CoSciTech)
ISSN : 2723567X     EISSN : 27235661     DOI : https://doi.org/10.37859/coscitech
Core Subject : Science,
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.
Articles 358 Documents
Analisa sentimen terhadap kenaikan bbm di twitter (x) menggunakan naive bayes classifier Muhammad Abdillah; Fikry, Muhammad; Yusra; Nazir, Alwis; Insani, Fitri
Computer Science and Information Technology Vol 5 No 1 (2024): 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.v5i1.6954

Abstract

In early September 2022, there was a shock from the news of the rise in fuel prices. The government decided to increase the price of fuel due to the surge in world oil prices. PT Pertamina (Persero) officially raised the price of Fuel Oil (BBM) one-third of September 2022, at 2:30 PM WIB (Western Indonesia Time). Since the decision, it has sparked opinions from the public. Many people expressed their responses through the social media platform Twitter, both in positive and negative ways. This resulted in both positive and negative sentiments from the public. The data used consisted of 3,000 tweets with the keyword "FUEL PRICE INCREASE," collected from November 1, 2022, to December 1, 2022. This research utilized the Naive Bayes Classifier method, conducted with three comparisons using thresholds ranging from 0.001 to 0.007. The experiment was conducted with three types of data testing: opinion data, mixed data (opinion-non-opinion), and balanced data. Here are the test results: for opinion data, the highest accuracy obtained was 80% with a ratio of 90:10, for mixed data, the accuracy obtained was 67.7% with a ratio of 70:30, and for balanced data, the accuracy obtained was 63.6% with a ratio of 90:10.
Penerapan Algoritma K-Means Clustering pada Sentimen Pengunjung Desa Wisata Hanjeli Arul, Sahrul Ismail Usman; Sanjaya, Imam
Computer Science and Information Technology Vol 5 No 1 (2024): 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.v5i1.6955

Abstract

Berwisata merupakan suatu kegiatan yang sudah menjadi kebiasaan yang dilakukan masyarakat, semakin berkembangnya informasi GEO wisata maka berpengaruh terhadap perkembangan masyarakat ekonomi lokal. GEO wisata desa hanjeli seharusnya sudah ada pada tahap maju karena sudah 10 tahun dari 2013. Analisis sentimen objek wisata desa hanjeli berguna untuk mengetahui pandangan pengunjung yang datang ke Desa Wisata Hanjeli dan Kabupaten Sukabumi. Dengan menggunakan perhitungan berbasis python untuk mengetahui sentimen dari pengunjung yang datang pada tahun 2022 dan euclidean distance untuk mengetahui jumlah kemungkinan pengunjung yang datang kembali. Berdasarkan hasil penelitian dengan membagikan angket pada pengunjung yang datang pada tahun 2022 melalui whatsapp dan email jumlah data yang terkumpul ada 143 serta setelah melalui perhitungan pertama(python) sentimen pengunjung dinyatakan positif dan hasil perhitungan kedua euclidean distance kemungkinan berkunjung kembali 22% dari pengunjung yang hadir.
Pencarian adverse event yang timbul akibat penggunaan obat dexamethasone menggunakan algoritma apriori Nuradha Liza Utami; Alwis Nazir; Pizaini; Elvia Budianita; Fitri Insani
Computer Science and Information Technology Vol 5 No 1 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Inflammation is the body's response to infection, irritation, or injury characterized by redness, increased temperature, swelling, and pain. Dexamethasone is one of the drugs from the corticosteroid group that is commonly used, dexamethasone has a wide indication in medicine is often considered a drug that can save lives, causing many people to then buy dexamethasone drugs without medical indications and prescriptions assuming dexamethasone drugs can treat various diseases. The use of dexamethasone can result in side effects including decreased immunity, diabetes, hypertension, moon face, osteoporosis, and cataracts. In addition to frequent side effects, adverse events may also occur. This study aims to find the relationship of adverse events that arise as a result of using dexamethasone drugs, by applying the data mining technique of association rule method with apriori algorithm. The dataset used in the research is sourced from the FDA Adverse event Reporting System (FAERS) database which is managed using the KDD stages which include data selection, cleaning, transformation, and data mining. the results of the research are implemented into the apriori algorithm data mining system and tested using the lift ratio value. The rules generated in this study have a lift ratio value of more than 1, which means that the rules generated are valid and show the benefits of these rules.
Sistem Prediksi Penjualan Pupuk Kelapa Sawit PT. Agro Subur Anugrah Menggunakan Metode Single Exponential Smoothing: Sistem Prediksi Penjualan Pupuk Kelapa Sawit PT. Agro Subur Anugrah Menggunakan Metode Single Exponential Smoothing Sunanto, Sunanto; Mualfah, Desti; Ronaldo, Aditya
Computer Science and Information Technology Vol 5 No 1 (2024): 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.v5i1.6976

Abstract

A factory is an industrial facility where raw materials or components are processed or processed into finished products. The production process in a factory can involve a wide range of activities, including manufacturing, processing, assembly, and energy production. PT. Agro Subur Anugrah is the owner of the Ultra Agrotan organic fertilizer factory which is made from empty palm oil bunches. The Ultra Agrotan fertilizer factory started production in 2017 with a production capacity of 15 tons per day. Due to the increase in the price of chemical fertilizers, demand for Ultra Agrotan fertilizer increased, so production was increased to 50 tons per day. Fertilizer sales are greatly influenced by various factors, namely weather conditions, soil quality, soil type, age of oil palm plants, and cultivation practices carried out by farmers or plantation companies which are not fixed every year, so that fertilizer sales are not smooth due to these conditions. Large unsold fertilizer stocks will harden, this can be detrimental to the company. In this case, a system is applied that can predict the amount of fertilizer production every day, week, month and year based on fertilizer demand data in the previous year, namely fertilizer sales data for 2017, 2018, 2019, 2020, 2021 and 2022. The application is presented using a web-based The single exponential smoothing method is expected to help calculate the amount of production, stock and consumer demand for Ultra Agrotan fertilizer.
Pengaruh literasi digital, media sosial dan pengetahuan kewirausahaan terhadap minat berwirausaha mahasiswa akuntansi Universitas Muhammadiyah Riau Filia, Sarahana; Rodiah, Siti; Samsiah, Siti
Computer Science and Information Technology Vol 5 No 1 (2024): 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.v5i1.7060

Abstract

Based on the results of the researcher's interview with the Head of the FEB UMRI Incubator, Mrs. Dian Puji Puspita Sari, SE., M. Ak, it shows that students' interest in entrepreneurship is still very low. This is shown by the number of Accounting students from the Faculty of Economics and Business (FEB) at Muhammadiyah University of Riau (UMRI) who only have 50 students. This figure is considered very low when compared to the number of FEB UMRI Accounting students as a whole. As accounting students, students are expected to not only master accounting knowledge but also master entrepreneurship knowledge, where this knowledge will later be able to equip students to enter the world of work. Because as students with economic and business backgrounds, students are expected not only to look for work when they graduate from college, but also to be able to create jobs for others by becoming entrepreneurs. This research aims to determine the influence of digital literacy, social media and entrepreneurial knowledge on students' entrepreneurial interest. This research uses a quantitative approach for students taking entrepreneurship courses at the Muhammadiyah University of Riau Accounting Study Program with a sample of 83 people. This research data analysis technique uses validity testing, reliability testing, classical assumption testing and hypothesis testing using multiple linear regression, t test and coefficient of determination test. The research results show that digital literacy, social media, and entrepreneurial knowledge have a partial influence on the entrepreneurial interest of students in the Accounting Study Program at Muhammadiyah University of Riau.
Studi Literatur Penerapan Clustering Data Numerik Untuk Sistem Rekomendasi Berbasis Collaborative Filtering Ifada, Noor; Pratama, Rizki Ashuri
Computer Science and Information Technology Vol 5 No 2 (2024): 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.v5i2.7087

Abstract

The recommendation system assists users in finding items that match their preferences from the large number of items that exist. Recommendation systems have two types of approaches: a content-based approach and a Collaborative Filtering (CF) approach. CF approaches can be categorized into model-based and memory-based CF. The problem faced in the CF method is the complexity or long computation time due to the large data dimensions, data sparsity, and accuracy. In overcoming the problems mentioned, several data mining and machine learning techniques are used in collaboration with traditional CF methods. Many studies are using numerical data clustering techniques on CF-based recommendation systems. However, to date, there is still no literature review regarding the implementation of clustering techniques to numerical data to develop recommendation system methods based on the CF approach. Therefore, a literature study was carried out regarding the implementation of clustering techniques to numerical data to develop recommendation system methods based on the CF approach using 20 related literature. As a result, the various clustering techniques used can be grouped into K-Means, Subspace Clustering, Bi-Clustering, Canopy Clustering, K-Medoids, Evolutionary Heterogeneous Clustering, Fuzzy, Self-Constructing Clustering (SCC), and Agglomerative Hierarchical Clustering (AHC). K-Means and Fuzzy clustering techniques are the most commonly found in the literature.
Perancangan antarmuka aplikasi foodCare menggunakan metode user centered design Putro Setyoko
Computer Science and Information Technology Vol 5 No 2 (2024): 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.v5i2.7117

Abstract

Sustainable Development Goals (SDGs) is a global development plan that aims to eradicate poverty, reduce inequality and preserve the environment. FoodCare application design solutions or Mobile-based free food sharing applications are rare, although they only existed about a few years ago. The development of foodCare application design solutions generally focuses on the role of users or donors. The purpose of developing a foodCare app design solution is to help donors who want to voluntarily donate their excess food. Application usability is an important component of the application, which indicates how easy it is for users to use it. For this reason, this research was conducted to design the application interface in terms of user needs. The method used is User Centered Design (UCD) while the usability measurement uses the System Usability Scale (SUS) involving 14 respondents. The results of measuring the usability of foodCare using SUS are 85.35 with the Best Imaginable rating and are in grade A. These results indicate that designing foodCare application design solutions with the User Centered Design method can present a new solution that can help meet the needs of users.
Perancangan dan Pembuatan Aplikasi Permainan Edukasi Mathventure Quest Berbasis Android Trianto, Edwin Meinardi; Ariel Kristianto; Ivan Leonardi Candra; Timothy John Pattiasina; Titasari Rahmawati
Computer Science and Information Technology Vol 5 No 2 (2024): 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.v5i2.7211

Abstract

Mathematics can be said to be a mandatory subject from elementary school to college or higher education whose function is used to this day. Mathematics lessons are sometimes considered quite difficult subjects by students at school because mathematics is always related to formulas, calculations and numbers. Games are defined as activities that relieve boredom and fill free time. Games can also increase the level of intelligence, increase knowledge and solve problems easily. The author was inspired to create or design an educational game application with a mathematics theme entitled Mathventure Quest using Android-based Unity Engine software. In this game there are enemies that must be fought to move to the next place. The way to fight these enemies is to answer the questions given by the application. If the player can answer, the enemy will lose and move on to the next place. This educational game can help educate and attract the attention of elementary school students with mathematics lessons which can also be a medium of entertainment for elementary school students.
Sistem Pendukung Keputusan Pemilihan Makanan Balita Menggunakan Metode Weighted Product Berbasis Android Mufreni, Sadr Lufti; Arizona Firdonsyah; Sabrina Khusnul Khotimah
Computer Science and Information Technology Vol 5 No 2 (2024): 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.v5i2.7240

Abstract

Parents often find it challenging to choose the right foods that meet their toddlers' nutritional needs. Nutritional requirements are crucial during the growth and development phase of toddlers. Ensuring toddlers get proper nutrition is vital for their growth. Selecting the wrong foods can lead to insufficient nutrition, which could hinder their growth and development. This research aimed to develop an Android-based decision support system for selecting toddler foods and making it easier for parents to choose the right foods for their toddlers. This research employed the Weighted Product method, based on six criteria: carbohydrates, protein, fat, vitamin A, iron, and zinc. The data were collected by reviewing literature, conducting field studies, and using the System Development Life Cycle (SDLC) waterfall model for system development. The results rank forty different types of food, with fried shrimp being the top-ranked option. The accuracy of the Weighted Product method is calculated to be 100%.
Implementasi Deteksi Langsung Pada Sistem Ujian Online Menggunakan Algoritma Convolutional Neural Network Putri Iskandar, Alyanissa; Muhammad Ikhsan Thohir; Ivana Lucia Kharisma; Kamdan; Anggun Fergina
Computer Science and Information Technology Vol 5 No 2 (2024): 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.v5i2.7270

Abstract

Pendidikan adalah fondasi penting dalam pembentukan potensi manusia, dan pergeseran ke arah ujian online menandai transformasi besar dalam cara kita menilai dan mengukur pencapaian akademik. Dengan kemajuan teknologi, penggunaan sistem proctoring dengan teknologi pengenal wajah merupakan langkah progresif untuk menjaga integritas ujian. Namun, peralihan ke ujian online juga membawa tantangan tersendiri, karena kecurangan, identitas ganda, dan kurangnya pengawasan dapat mengurangi kepercayaan terhadap hasil ujian. Oleh karena itu, pengembangan sistem pengawasan yang handal dan efektif sangat penting untuk menjaga standar akademik. Penelitian ini bertujuan untuk merancang dan mengembangkan sistem pengawasan ujian online yang memanfaatkan teknologi pengenalan wajah. Proctoring ujian secara daring diperlukan untuk memastikan validitas dan keamanan ujian. Sistem yang diusulkan mengimplementasikan algoritma pendeteksi pergerakan peserta selama ujian berlangsung yang diperkuat dengan algoritma Convolutional Neural Network (CNN) untuk memonitoring perilaku selama ujian berlangsung, dan mendeteksi tindakan yang mencurigakan. Hasil dari penelitian ini diharapkan dapat memberikan kontribusi dalam meningkatkan integritas ujian online, mendorong adopsi teknologi proctoring, dan memberikan solusi yang efektif bagi institusi pendidikan yang menghadapi tantangan terkait keamanan ujian online. Dimana sistem dibangun dengan menggunakan bahasa python dan framework Laravel untuk bahasa pemrograman dan MySQL untuk DBMS-nya.