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<![CDATA[Digitalisasi Cagar Budaya Kota Pekanbaru menggunakan web ]]>
<![CDATA[Harun Mukhtar]]>;
<![CDATA[Januar Al Amien]]>;
<![CDATA[Muhammad Ilham Akbar]]>;
<![CDATA[Hasanatul Fu'adah Amran]]>
<![CDATA[ JURNAL FASILKOM Vol 12 No 2 (2022): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) ]]>
Publisher : <![CDATA[Unversitas Muhammadiyah Riau ]]>
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DOI: 10.37859/jf.v12i2.3937
<![CDATA[Recognition of cultural heritage and its preservation raises innovative ideas for digitizing. Digitization began to be discussed as an alternative solution to solving the problem of cultural heritage. Pekanbaru has a cultural heritage that includes buildings, artifacts, and structures. The cultural heritage found in the city of Pekanbaru started from the time of the Siak Kingdom, including the Railway Monument, Sultan Siak Shelter House, Ground Zero Pekanbaru, Red and White Monument, Marhum Pekan Tomb Complex, Pekanbaru Great Mosque, Surau Al Irhash, Tuan Khadi Shelter and Havenmaster's house. This study is intended to digitize the crocodile reserve in the city of Pekanbaru using the PHP and MySql programming languages as data storage. The results of this study contribute to the preservation and recognition of cultural heritage as the nation's heritage. With the existence of a website about cultural heritage, this cultural heritage will not be forgotten by the masses.]]>
<![CDATA[Peramalan Kedatangan Wisatawan ke Suatu Negara Menggunakan Metode Support Vector Machine (SVM) ]]>
<![CDATA[Harun Mukhtar]]>;
<![CDATA[Rahmad Gunawan]]>;
<![CDATA[Amin Hariyanto]]>;
<![CDATA[Syahril]]>;
<![CDATA[Wide Mulyana]]>
<![CDATA[ Jurnal CoSciTech (Computer Science and Information Technology) Vol 3 No 3 (2022): Jurnal Computer Science and Information Technology (CoSciTech) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Riau ]]>
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DOI: 10.37859/coscitech.v3i3.4211
<![CDATA[Tourism is one of the most promising ecosystems for economic sectors worldwide. A strong tourism sector directly contributes to the country's national income, fights unemployment, and improves the balance of payments. Tourism development can be seen from the increase in arrivals to a nation; based on data obtained from the UNWTO from 1995-2019, it has increased and decreased. The sudden increase and decrease in tourists will have positive and negative impacts. Forecasting is an activity to predict events that will occur in the future by taking data from the past. So this study will expect tourist arrivals to a country using the Support Vector Machine (SVM) method. SVM has properties about maximizing margins and kernel tricks to map nonlinear data. The results obtained in this study indicate that SVM Confidence is 86.3%, has a MAPE value of 56.00%, and an RMSE worth of 11126.36 from the total data of 53 countries. And forecasting is carried out in 5 countries with the highest tourist visits. The results obtained are excellent: SVM Confidence of 99.13%, a MAPE value of 2.78%, and an RMSE value of 2783.57.]]>
<![CDATA[Prediksi Kunjungan Wisatawan dengan Reduksi Noise pada Google Trends menggunakan Hilbert-Huang Transform dan Long Short-Term Memory ]]>
<![CDATA[Harun Mukhtar]]>;
<![CDATA[Yoze Rizki]]>;
<![CDATA[Febby Apri Wenando]]>;
<![CDATA[Muhammad Abdul Al Aziz]]>
<![CDATA[ JURNAL FASILKOM Vol 12 No 3 (2022): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) ]]>
Publisher : <![CDATA[Unversitas Muhammadiyah Riau ]]>
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DOI: 10.37859/jf.v12i3.4332
<![CDATA[In many studies, Google Trends Data is efficient to analyze and estimate as explanatory variables, including tourism predictions. However, data retrieval and tourism are always plagued by noise. Without noise processing, the predictive ability of search engine data may be weak, even invalid. As a noise processing method, Hilbert-Huang Transform (HHT) can reduce or clean noise. Forecasting is the art and science of predicting future events. LSTM is able to overcome long-term dependence. This study tries to provide predictions of tourist visits by processing noise in search engines using the Hilbert-Huang Transform method. The forecasting architecture that is built is composed of 3 hidden LSTM layers with 100 units of neurons or nerves that function to process information, which in the LSTM layer also becomes the input layer. Prediction test results on a dataset of 156 rows, resulting in RMSE values in 2019 getting RMSE LSTM 129249 results, and RMSE HHT + LSTM 653058. so that the resulting RMSE is closer to remembering 0.]]>
<![CDATA[K-Nearest Neighbor (KNN) untuk Menganalisis Sentimen terhadap Kebijakan Merdeka Belajar Kampus Merdeka pada Komentar Twitter ]]>
<![CDATA[Febby Apri Wenando]]>;
<![CDATA[Rahman Septiadi]]>;
<![CDATA[Rahmad Gunawan]]>;
<![CDATA[Harun Mukhtar]]>;
<![CDATA[Syahril]]>
<![CDATA[ Computer Science and Information Technology Vol 3 No 2 (2022): Jurnal Computer Science and Information Technology (CoSciTech) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Riau ]]>
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DOI: 10.37859/coscitech.v3i2.3841
<![CDATA[On December 11, 2019, the Minister of Education and Culture of the Republic of Indonesia Nadiem Anwar Makarim issued a policy of "Merdeka Belajar". Netizens on Twitter have debated this Merdeka Belajar and became a trending topic. This study tries to analyze the sentiment of tweets about opinions on this policy by classifying whether it is a positive opinion or a negative opinion. The classification method applied is the K-Nearest Neighbor algorithm. In this study, four main processes were carried out, namely text-preprocessing, word-weighting (TF-IDF), classification and validation using k-fold cross validation. Tests were carried out with a dataset of 700 data, training was carried out using 630 training data and 70 testing data. In testing, the highest accuracy of the K-Nearest Neighbor algorithm was obtained at the k-8 value, namely 84.28%. Furthermore, validation is carried out using k-fold cross validation with a value of fold = 10 to get an accuracy of 84.42%.]]>
<![CDATA[PENERAPAN FAILOVER NETWORK MENGGUNAKAN JARINGAN VPN DAN JARINGAN WIRELESS POINT-TO-POINT PADA DISTANCE BUILDING DI PT. TITIPAN KILAT RIAU ]]>
<![CDATA[Afdhil Hafid]]>;
<![CDATA[Harun Mukhtar]]>;
<![CDATA[Dani Harlian]]>
<![CDATA[ Jurnal Teknologi Terapan Vol 9, No 1 (2023): Jurnal Teknologi Terapan ]]>
Publisher : <![CDATA[P3M Politeknik Negeri Indramayu ]]>
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DOI: 10.31884/jtt.v9i1.467
<![CDATA[This research is intended to build a network that that can connect branch offices with main office buildings in a company. This is done in order to create all performance connected to a company network that can improve and run well, so as to be able to support the company's business processes. At the stage of meeting company needs and in an effort to overcome problems in the network used technology that can always be online with the expectation of quality of services (QoS) approaching 100%.. The technology applied uses two communication lines, the first connection line is point-to-point wireless and the second connection line applies a Virtual Private Network (VPN) with the use of the internet. Handles failover on both network communication connections used by the mikrotik router. This allows if one connection is lost, the other connection line will automatically become a backup line. In this failed network simulation, it shows satisfactory results, as can be seen from the communication performance that runs without feeling tired of traffic. The application of this method can also operate without involving humans. In addition, the results of the measurement of the time lag required for switching connection lines have an average delay value of not more than 4.97 seconds.]]>
<![CDATA[GAME SEJARAH UMRI SEBAGAI MEDIA PENGENALAN UMRI BERBASIS ANDROID ]]>
<![CDATA[Harun Mukhtar]]>;
<![CDATA[Jum’atul Zikri]]>;
<![CDATA[Mitra Unik]]>
<![CDATA[ Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 1 No. 1 (2021) ]]>
Publisher : <![CDATA[Department of Information System Muhammadiyah University of Riau ]]>
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DOI: 10.37859/seis.v1i1.1912
<![CDATA[Muhammadiyah Riau University (UMRI) is one of private University on Riau – Pekanbaru. A University which is one of the business charities of Muhammadiyah Indonesia. To maintain the historical value of UMRI requires an interesting media to keep Umri citizen in particular keep in mind the history of UMRI development. for that made an interactive game that is able to tell the history of development of UMRI. In the development of this game used MDLC as a method in the development of interactive games. For the development of this game is used Unity as Game editor. With this game the history of UMRI development can be known by the public.]]>
<![CDATA[IMPLEMENTASI ALGORITMA A STAR DALAM PENCARIAN RUTE TERPENDEK (SHORTEST PATH PROBLEM) PADA SISTEM PENCARIAN KANTOR POS DI KOTA PEKANBARU ]]>
<![CDATA[Harun Mukhtar]]>;
<![CDATA[Yusriadi Hendri]]>;
<![CDATA[Soni]]>
<![CDATA[ Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 2 No. 1 (2022) ]]>
Publisher : <![CDATA[Department of Information System Muhammadiyah University of Riau ]]>
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DOI: 10.37859/seis.v2i1.3313
<![CDATA[With the advancement of information technology today, there are several solutions that can facilitate the search for the shortest path (Shortest Path Problem) by using various algorithms such as the djiktra algorithm, A star algorithm, floyd warshall algorithm, prim algorithm and others. Algorithm A* (A star) is one of the algorithms included in the category of search methods that have information (informed search method). This algorithm is very good as a solution to the path finding process where this algorithm looks for the distance of the fastest route that will be taken by an initial point (starting point) to the destination object. The search technique used in this simulation is using the A* Algorithm with the manhattan distance heuristic function. Path Finding is one of the most important materials in Artificial Intelligence. Path Finding is usually used to solve problems on a graph. This study aims to provide a solution in finding the shortest route, so as to reduce operational costs that must be incurred by the company and also with this new system, it can be known the distance from one point to another without using manual calculations.]]>
<![CDATA[IMPLEMENTASI TEXT TO SPEECH DALAM APLIKASI PEMBELAJARAN MATEMATIKA DASAR DENGAN AUGMENTED REALITY ]]>
<![CDATA[Hasanatul Fu’adah Amran]]>;
<![CDATA[Reny Medikawaty Taufiq]]>;
<![CDATA[Abulkhair Asrul Abdurrahim]]>;
<![CDATA[Harun Mukhtar]]>
<![CDATA[ Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 2 No. 2 (2022) ]]>
Publisher : <![CDATA[Department of Information System Muhammadiyah University of Riau ]]>
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DOI: 10.37859/seis.v2i2.3999
<![CDATA[Mathematical science is a basic science that supports other sciences in its application. Therefore, understanding mathematics correctly will have implications for the ability to study several sciences related to mathematics. This study developed an augmented reality-based basic math learning application that can provide education to students with different media in order to increase student interest in learning mathematics. This application uses the Vuforia SDK library which is able to display 3-dimensional characters with markerless techniques in the form of augmented reality. The final result of this study is an application that can be used on smartphones with the Android operating system, based on the results of testing the application, it is concluded that the research and development of basic mathematics learning applications based on augmented reality have been successfully implemented and a series of tests have been carried out to test the capabilities of the application. From the results of testing conducted by distributing questionnaires to students who are sitting in elementary school, from grade 3 (three) to grade 6 (six). The result of the percentage of students' answers who answered correctly was 97 percent (%) and the wrong one was 3 percent (%), it can be concluded that the application of basic mathematics learning based on augmented reality can help students in learning mathematics with learning media and can help students learn math anywhere easily.]]>
<![CDATA[Prediksi Indeks Harga Produsen Pertanian Karet Di Indonesia Menggunakan Metode LSTM ]]>
<![CDATA[Rahmad Firdaus]]>;
<![CDATA[Harun Mukhtar]]>;
<![CDATA[Awaluddin]]>
<![CDATA[ JURNAL FASILKOM Vol 13 No 01 (2023): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) ]]>
Publisher : <![CDATA[Unversitas Muhammadiyah Riau ]]>
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DOI: 10.37859/jf.v13i01.4851
<![CDATA[Karet alam merupakan salah satu bahan baku tanaman yang memiliki pasar yang cukup luas dalam perdagangan internasional, karena dibutuhkan sebagai bahan baku di berbagai industri. Harga produksi karet harus diramalkan karena harga produksi merupakan harga pertama diantara tingkat harga lainnya. Oleh karena itu, informasi mengenai perubahan harga pada suatu produsen sangat penting sebagai sistem peringatan dini terhadap fluktuasi harga pada tingkat harga selanjutnya. Algoritma Long-Short-Term-Memory (LSTM) dipilih karena dianggap cocok untuk menyelesaikan permasalahan peramalan indeks harga produsen pada sektor budidaya karet, karena LSTM sendiri merupakan salah satu pengembangan neural network yang dapat digunakan untuk memodelkan. data deret waktu dan mampu belajar terus menerus. Analisis parametrik yang dilakukan pada penelitian ini adalah jumlah hidden neuron, epoch dan ukuran stack. Kombinasi parameter terbaik yang dihasilkan pada penelitian ini adalah 50 hidden neuron, 25 epoch, dan stack size 10. Nilai terbaik yang dihasilkan pada penelitian ini adalah nilai RMSE data training sebesar 384,20 dan nilai RMSE test sebesar 306,01 dan nilai latih MAPE sebesar 1,25 dan nilai uji MAPE sebesar 1,09%. Perhitungan error MAPE terbaik pada penelitian ini adalah studi Prediksi Indeks Harga Produsen Pertanian Karet di Indonesia dengan Metode Long Short Term Memory yang memberikan MAPE terbaik. Hasil tersebut menunjukkan bahwa MAPE error dapat dikatakan sangat baik karena nilai MAPE terbaik yang dihasilkan kurang dari 10%.]]>
<![CDATA[Prediksi Curah hujan di Kota Pekanbaru Menggunakan lSTM (Long Short Term Memory) ]]>
<![CDATA[Yos Hendra]]>;
<![CDATA[Harun Mukhtar]]>;
<![CDATA[Baidarus]]>;
<![CDATA[Rizka Hafsari]]>
<![CDATA[ Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 3 No. 2 (2023) ]]>
Publisher : <![CDATA[Department of Information System Muhammadiyah University of Riau ]]>
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DOI: 10.37859/seis.v3i2.5606
<![CDATA[Based on data obtained from BMKG Pekanbaru City in 2010-2020 there was an increase anddecrease in the intensity of rainfall that occurred in Pekanbaru city. The increase in rainfall in thecity of Pekanbaru will cause problems such as the occurrence of flooding of several roads and severalareas in the city of Pekanbaru and the occurrence of other unexpected disasters that will causeproblems and experience difficulties. In overcoming this problem, research was conducted in the formof Rainfall Prediction in Pekanbaru City Using LSTM (Long Short Term Memory) using 2 methods,namely in finding the accuracy of the error rate using RMSE (Root Mean Square Error) and MSE(Mean Square Error). The results showed that the predictions made were quite good. With the lowesterror rate of 21,328 in the train and 454,901 in the test, the composition of the train data and the testdata half gave the best results.]]>
