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Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Published by Universitas Muhammadiyah Riau
ISSN : 20893353     EISSN : 28089162     DOI : https://doi.org/10.37859/jf.v11i3.2781
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) is expected to be a media of scientific study of research result, a thought and a study criticial analysis to a System engineering research, Informatics Engineering, Information Technology, Computer Engineering, Informatics Management, and Information System. We accept research papers which focused to these following topics: System Engineering Expert System Decision Support System Data Mining Artificial Intelligent Computer engineering Digital Image Processing Computer Graphic Computer Vision Genetic Algorithm Machine Learning Deep Learning Information System Design Business Intelligence and Knowledge Management Database System Big Data IOT Enterprise Computing ICT and Islam Technology Management and other relevant topics to field of Information Technology
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 374 Documents
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Sistem Pendukung Keputusan Seleksi O2SN Cabang Pencak Silat Menggunakan Metode SAW Septian, Fajar; Syaripudin, Ari; Punkastyo, Dimas Abisono
JURNAL FASILKOM Vol. 13 No. 3 (2023): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v13i3.6239

Abstract

Kegiatan ekstrakurikuler adalah aktivitas pendidikan non-formal yang dilakukan oleh siswa di sekolah, biasanya di luar jam pelajaran kurikulum reguler. MTS Muhammadiyah 1 menawarkan berbagai kegiatan ekstrakurikuler seperti futsal, voli, dan silat, dan setiap tahun mereka berpartisipasi dalam kompetisi O2SN (Olimpiade Olahraga Siswa Nasional). O2SN adalah acara nasional yang bertujuan untuk menemukan bakat-bakat olahraga baru di Indonesia dalam berbagai cabang olahraga. Proses pemilihan siswa untuk berpartisipasi dalam kompetisi-kompetisi ini di MTS Muhammadiyah Depok belum terstruktur dengan baik, sehingga diterapkanlah Sistem Pendukung Keputusan (Decision Support System) dengan metode Simple Additive Weighting (SAW). Sistem Pendukung Keputusan merupakan bagian penting dari sistem informasi berbasis komputer dan berperan krusial dalam mendukung proses pengambilan keputusan. Metode SAW sering disebut sebagai penjumlahan tertimbang dari penilaian kinerja untuk setiap alternatif pada setiap atribut. Aplikasi ini dikembangkan menggunakan bahasa pemrograman PHP, perangkat lunak basis data MySQL, dan metode SAW. Hasil dari aplikasi ini mengidentifikasi siswa-siswa yang memiliki potensi untuk berpartisipasi dalam kompetisi berdasarkan sembilan kriteria. Berdasarkan hasil uji dengan Black box testing menunjukkan seluruh fungsionalitas dapat berjalan sebgaimana mestinya. Sistem ini membantu sekolah dalam membuat keputusan yang lebih objektif dan kurang bersifat subjektif dalam proses pemilihan siswa.
Peningkatan Pelayanan Laboratorium Dengan Memprediksi Kedatangan Pasien Menggunakan Metode Monte Carlo Eko Syaputra, Aldo; Eirlangga, Yofhanda Septi; Sapriadi, Sopi
JURNAL FASILKOM Vol. 13 No. 3 (2023): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v13i3.6242

Abstract

The number of patient visits to the laboratory is unstable sometimes decreasing and increasing, when the increase in the number of visits to the laboratory makes everything disrupted because the number of patients who come is not proportional to the staff who are working / assigned at that time in the laboratory. So that some patients do not even get thorough service and even some patients wait too long in the queue. This causes services in the laboratory to be hampered, disrupted and become less than optimal. So the laboratory must be able to overcome this problem by knowing the number of visits to the laboratory in the future. So the researchers conducted this study with the aim of providing accurate information regarding the prediction of the number of patient arrivals to the laboratory with the application of the Monte Carlo Method. This method is a method that is often used to solve problems that are often related to uncertainty. The data used in this study is the last 3 years of patient arrivals to the laboratory with the frequency of arrivals from January to December. The results of this research are compacted accuracy of 87% in 2020 and 91% in 2021. So that the laboratory can take action on services in the future and make this research as a reference material.
Inovasi Interaktif Merancang dan Membangun Virtual Tour Asriloka Wonosalam Menggunakan Metode MDLC Hendra Maulana; Tri Lathif Mardi Suryanto; Ronggo Alit; Wardhani, Lintang Sari Putri; Tsabita Safana Mustofa
JURNAL FASILKOM Vol. 13 No. 3 (2023): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v13i3.6245

Abstract

Virtual tour (VT) technology is a virtualized digital technology that allows users to visit and explore locations without physically being there. This allows tourism owners to promote their tours using VT technology. One of them is Asriloka Wonosalam Ecotourism in Jombang, which is concerned with how potential visitors can see an overview of the facilities and atmosphere available. Through the Multimedia Development Life Cycle (MDLC) method, this paper aims to design and build Asriloka Wonosalam VT and then evaluate its application. This paper results in the design and creation of the Asriloka Wonosalam VT which has 3600 panoramic features, voice over information, text information, and a simple tour guide. The evaluation results show that 7 black box testing question items have a successful conclusion, finally the Asriloka Wonosalam VT was successfully created, implemented, and launched to support digital promotion.
Analysis of ChatGPT Usage to Support Student Lecture Assignments Randa Liling, Jenary; Anas Aklani, Syaeful
JURNAL FASILKOM Vol. 13 No. 3 (2023): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v13i3.6254

Abstract

Technology is revolutionizing the way education is delivered, making it more accessible, efficient, and effective than ever before. The pace of technological advancement in the educational sector is accelerating at an unprecedented rate, transforming the traditional classroom model, and empowering learners with new tools and resources to enhance their learning experience. One such technology is artificial intelligence, such as ChatGPT. This artificial intelligence technology developed by OpenAI is increasingly being utilized in educational settings, particularly to assist students in completing their academic tasks. This study aims to analyze and understand the perspectives of students regarding the use of ChatGPT, an AI-powered chatbot, as an aid in their academic coursework. The research employs both quantitative and qualitative approaches based on the Technology Acceptance Model (TAM), and data analysis is conducted using PLS-SEM. The results indicate that the research variable "Perceived Usefulness" has a significant influence on students' attitudes towards the use of ChatGPT. Additionally, the variable "Attitude towards ChatGPT" significantly impacts students' intention to use ChatGPT as a tool to assist them with academic tasks in the future. These findings provide valuable insight into the potential benefits of ChatGPT as an educational tool and highlight the importance of students' perceptions and attitudes towards technology in shaping their academic experiences.
Sistem Pendukung Keputusan Rekomendasi Penerima Bantuan Iuran BPJS Kesehatan Menggunakan Metode ROC dan SMART Masroni; Syarifah Putri Agustini Alkadri; Rachmat Wahid Saleh Insani
JURNAL FASILKOM Vol. 13 No. 3 (2023): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v13i3.6271

Abstract

Bantuan Sosial Penerima Bantuan Iuran (PBI) yang merupakan program dari pemerintah untuk pelayanan kesehatan dalam pemberian bantuan yang berupa jaminan kesehatan kepada masyarakat indonesia, dalam proses rekomendasi untuk Penerima Bantuan Iuran (PBI) BPJS Kesehatan di Dinas Sosial Kabupaten Sambas selama ini masih berdasarkan hasil penilaian musyawarah desa (MUSDES) baru kemudian diserahkan ke Dinas Sosial, penilaian dan pendataan yang dilakukan masih secara manual yaitu pendataan dengan mengisi form kertas verifikasi dan validasi data yang belum terkomputerisasi dengan baik, sehingga memakan waktu paling cepat seminggu atau 21 hari paling lama. Sistem yang dibangun menggunakan metode ROC dan SMART bertujuan agar dapat membantu pihak pendata untuk mengurangi waktu dalam pendataan dan efektif dalam merekomendasikan penerima bantuan sosial PBI sesuai kriteria yang digunakan. Hasil penelitian ini hanya 13 alternatif yang akan direkomendasikan untuk mendapatkan bantuan sosial yaitu alternatif bahar dengan nilai 0,07381 sampai alternatif tambrin dengan nilai 0,6993 dengan hasil perhitungan yang cukup akurat diketahui melalui pengujian MAPE (Mean Absolute Perentage Error) menunjukkan hasil 25,31%.
Deep Learning Untuk Klasifikasi Kematangan Buah Mangrove Berdasarkan Warna Mukhtar, Harun; Alfanico, Febrian; Fu’adah Amran, Hasanatul; Handayani, Fitri; Medikawati Taufiq, Reny
JURNAL FASILKOM Vol. 13 No. 3 (2023): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v13i3.6292

Abstract

Plants that live between land and sea, such as mangroves, are influenced by the tides and tides. Indonesia has the largest mangrove forest in the world and a variety of biodiversity and structure. People currently detect mangrove maturity by looking directly at the fruit. This study proposes to classify the maturity of mangrove fruit using artificial intelligence techniques, making it easier for farmers to determine the ripeness of the fruit. This proposal uses data from 200 images for mangroves taken directly from Lukit Village, Merbau District, Meranti Islands Regency. This research improves the Convolutional Neural Network (CNN) method to classify mangrove fruit maturity. The results obtained from this research were by classifying ripe and unripe fruit. Based on this research, accuracy reaches a maximum of 96%.
Analisis Sentimen Mobil Listrik di Indonesia Menggunakan Long-Short Term Memory (LSTM) Sri Widagdo, Adika; Ardiansyah; Krisna Nuresa Qodri; Fachruddin Edi Nugroho Saputro; Nisrina Akbar Rizky Putri
JURNAL FASILKOM Vol. 13 No. 3 (2023): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v13i3.6303

Abstract

Vehicles using fuel oil that is converted into mechanical energy were introduced in 1891 by John W. Lambert in America. But with this, the level of air pollution caused by exhaust emissions has become a problem today, until environmentally friendly engine innovations appear. The beginning of the development of these innovations was marked by hybrid technology cars. This technology has not completely abandoned the use of oil as fuel. In general, these vehicles are known as HEV or Hybrid Electic Vehicles. Then came a car that was entirely with an electric motor drive or EV or Electric Vehicle. Although the technology is considered environmentally friendly, on the other hand it does not make all elements of society accept any changes, especially in fuel oil engines to electric motors. With these changes, there are pros and cons that are the focus of researchers by utilizing sentiment analysis which is a Natural Language Processing (NLP) scientific family to analyze what aspects make society pro or con to the emergence of environmentally friendly vehicles. Data collection in this study took from YouTube comments in the form of Indonesian text data carried out using Python programming language and Long-Short Term Memory (LSTM) as an algorithm for analyzing public opinion. The dataset was divided into training data and test data with a ratio of 67:33, The results showed that the model can be used on Indonesian text data well. Then for the process of accuracy test data 63%, then macro avg precision 62%, macro avg recall 60%, macro avg f1-score 60%, weighted avg precision 62%, weighted avg recall 63%, weighted avg f1-score 62%, roc_auc 81%. In this study, it can also be seen that the topic of discussion that often arises, namely prices in all classes. However, negative sentiment is more than other sentiment classes, one of which is due to electric car manufacturers so it is very necessary to pay attention to stakeholders regarding prices that are suitable for the Indonesian market.
Penerapan Algoritma C5.0 Untuk Memprediksi Tingkat Kepuasan Siswa Terhadap Kinerja Guru MAN Simalungun Kherina Surya Ningsih; Zufria, Ilka
JURNAL FASILKOM Vol. 13 No. 3 (2023): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v13i3.6347

Abstract

Peran guru sangat penting dalam membentuk lanskap pendidikan, yang mencakup pendidikan formal di berbagai tingkatan. Tanggung jawab ini mencakup pengasuhan, bimbingan, penilaian, dan evaluasi siswa. Mengambil inspirasi dari sebuah ayat yang mendasar, penelitian ini menyelidiki pengaruh mendalam dari prinsip-prinsip Alquran, dengan menggunakan kehidupan Nabi Muhammad sebagai model, dalam membentuk profesionalisme guru. Hubungan ini berfungsi sebagai aspek dasar dalam memahami peran pendidik. Tantangan yang teridentifikasi dalam kinerja guru di Madrasah Aliyah Negeri Simalungun secara signifikan berdampak pada kepuasan dan hasil belajar siswa, dengan faktor-faktor seperti penjelasan yang tidak jelas dan kurangnya antusiasme yang menonjol. Dengan menggunakan teknik-teknik canggih, penelitian ini menggunakan data mining, khususnya algoritma C5.0, untuk memprediksi tingkat kepuasan siswa. Algoritma ini menganalisis kumpulan data yang terdiri dari 70% data pelatihan dan 30% data pengujian. Hasilnya menunjukkan tingkat akurasi 77,78%, presisi 87,50%, recall 87,50%, spesifisitas 0%, dan skor F1 87,50% pada percobaan pertama. Pada percobaan kedua, dengan 80% data pelatihan dan 20% data pengujian, akurasi sebesar 83,33%, presisi 83,33%, recall 100%, spesifisitas 0%, dan F1-score 90,90%. Penelitian ini menggarisbawahi pentingnya pengambilan keputusan yang tepat untuk meningkatkan kualitas pendidikan. Dengan memprediksi dan menangani faktor-faktor yang mempengaruhi kepuasan siswa, para pendidik dapat mengimplementasikan perbaikan yang ditargetkan dalam metode pengajaran. Selain itu, penelitian ini juga sejalan dengan dan menunjukkan kepatuhan terhadap Undang-Undang Sistem Pendidikan Nasional. Analisis kuantitatif ini memberikan wawasan yang berharga bagi para pendidik dan pembuat kebijakan dalam upaya berkelanjutan mereka untuk memperbaiki dan mengoptimalkan dinamika guru-siswa.
SPK PENYELEKSIAN SISWA KELAS UNGGUL DENGAN METODE ANALYTICAL HIERARCHY PROCESS (AHP) eirlangga, Yofhanda Septi; Aldo Eko Syaputra; Muhammad Thoriq
JURNAL FASILKOM Vol. 14 No. 1 (2024): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v14i1.6348

Abstract

High-achiever classes are specialized groups comprising students who excel in two areas of assessment, possessing intelligence above the average. Teaching in these specialized classes requires specific skills to optimize the potential of the students. Each year, West Pasaman High School conducts screenings for hundreds of students eligible for placement in the high-achiever classes, which are limited to only 50 students. The selection process for these high-achiever classes at West Pasaman High School has traditionally been manual, lacking a systematic method to support the selection process. Consequently, the selection process has been time-consuming, resulting in inefficiencies, compounded by subjective factors like social jealousy over the outcomes of the selection. The proposed solution to address the issue in selecting high-achiever students is by implementing a systematic, computerized method to expedite and improve the accuracy of the selection process. The methodology employed in this study is the Analytical Hierarchy Process (AHP). The school has outlined six criteria for evaluation: normative value, adaptive value, attitude, discipline, creativity, and academic performance. The primary objective of this research conducted at West Pasaman High School is to assist the school administration in swiftly and efficiently identifying high-achiever students. The data processing from this study provides the final scores of students, ranked from highest to lowest, with the highest score obtained by 'Payau' at 0.232 or 23.2%, followed by 'Pada' with a score of 0.229 or 22.9%. It is hoped that this research can serve as a reference for the school administration in refining their selection process and identifying students deserving of a place in the high-achiever classes. Keywords: AHP, high-achiever classes, decision support system, school, selection.
Analisis Sentimen Masyarakat Terhadap Kasus Pembobolan Data Nasabah Bank BSI Pada Twitter Menggunakan Metode Random Forest Dan Naïve Bayes Mualfah, Desti; Prihatin, Ananda; Firdaus, Rahmad; Sunanto
JURNAL FASILKOM Vol. 13 No. 3 (2023): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v13i3.6478

Abstract

Indonesia has recently been enlivened by the data breach case that hit Bank Syariah Indonesia (BSI) in May 2023, this has invited many responses from the public with various kinds of responses, especially on Twitter social media. Some people support BSI bank so they can restore the system they have but many criticize and blaspheme bank BSI for not being able to quickly fix its system which hackers compromised. The purpose of this study is to conduct a sentiment analysis to find out the response of the Indonesian people regarding cases of data breaches by bank BSI customers whether positive, negative or neutral. The methods used in this study are the naive Bayes method and the random forest method. Both of these methods have been widely used in the text data classification process and produce high accuracy. The dataset used is community responses from Twitter social media taken by crawling the data totaling 809 tweets. The results of this study are the accuracy of the Naive Bayes method of 74% and the random forest method of 70%.

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