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All Journal Jurnal Pengabdian UntukMu NegeRI RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JURNAL MEDIA INFORMATIKA BUDIDARMA IT JOURNAL RESEARCH AND DEVELOPMENT Dinamisia: Jurnal Pengabdian Kepada Masyarakat SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Jurnal Teknologi Terapan Indonesian Journal of Electrical Engineering and Computer Science Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Computer Science and Information Technology (CoSciTech) Jurnal PkM (Pengabdian kepada Masyarakat) Jurnal Gramatika: Jurnal Penelitian Pendidikan Bahasa dan Sastra Indonesia Journal of Software Engineering and Information System (SEIS) JITER-PM (Jurnal Inovasi Terapan - Pengabdian Masyarakat)

Harun Mukhtar

Universitas Muhammadiyah Riau

Author-ID : 616839

Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

Published : 57 Documents Claim Missing Document

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Articles

Title

GAME SEJARAH UMRI SEBAGAI MEDIA PENGENALAN UMRI BERBASIS ANDROID Harun Mukhtar; Jum’atul Zikri; Mitra Unik
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 1 No. 1 (2021)
Publisher : Department of Information System Muhammadiyah University of Riau

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.

IMPLEMENTASI TEXT TO SPEECH DALAM APLIKASI PEMBELAJARAN MATEMATIKA DASAR DENGAN AUGMENTED REALITY Fu’adah Amran, Hasanatul; Medikawaty Taufiq, Reny; Asrul Abdurrahim, Abulkhair; Mukhtar, Harun
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 2 No. 2 (2022)
Publisher : Department of Information System Muhammadiyah University of Riau

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.

Prediksi Curah hujan di Kota Pekanbaru Menggunakan lSTM (Long Short Term Memory) Hendra, Yos; Mukhtar, Harun; Baidarus; Hafsari, Rizka
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 3 No. 2 (2023)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v3i2.5606

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.

ANALISIS KESUBURAN PERTANIAN MELALUI IRIGASI DENGAN MENGGUNAKAN METODE K-MEANS CLUSTERING Mukhtar, Harun; Syafutri, Trimaiyuza Maulina; Rahman, Rayhan Aulia; Putra, Afyuadri; Hafsari, Rizka
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 4 No. 2 (2024)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v4i2.7599

Indonesia is an agricultural country where the majority of its population makes a living from agriculture. The agricultural sector is a very important sector for economic development in an agricultural country like Indonesia. Poor irrigation facilities greatly affect the results of the agricultural sector. Crop quality is based on many factors such as the characteristics of the irrigation process, including the amount of air and irrigation time. Overwatering irrigation can cause air wastage, soil freezing disease, yellowing of plant leaves, wilting of plant leaves, and many other problems. K-Means clustering is a method used to group data into one or more groups or clusters. The advantages of the K-Means algorithm are that it is easy and simple to implement, scalability, speed in convergence, and the ability to adapt to sparse data. K-Means to group agricultural land based on soil fertility and rainfall data, found that this grouping can help in more efficient irrigation planning. The clustering results show that agricultural land can be divided into three main clusters based on soil fertility and irrigation. Soil fertility is formed into three clusters based on the level of soil fertility using the Kmeans algorithm which can also be effective in helping in the Indonesian agricultural sector. By adding technological elements, the results provided will of course be even better.

ALGORITMA K-MEANS UNTUK PENGELOMPOKAN PERILAKU CUSTOMER Mukhtar, Harun; Dwi Pramaditya, Ilham; Saputra Weisdiyanto, Wahyu; Hardian_Putra, Saddam; Trimuawasih, Diana; Auralia Rilda, Azzahra
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 4 No. 2 (2024)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v4i2.7615

In the rapidly evolving digital era, understanding customer purchasing behavior is crucial for marketing strategies and business development. This study uses the K-means clustering algorithm to analyze and segment customer purchasing behavior. This algorithm effectively partitions data into groups based on similar characteristics. The aim of this study is to identify purchasing behavior patterns using attributes such as purchase frequency, expenditure amount, and product types. By segmenting customers into homogeneous groups, companies can design more effective marketing strategies and better personalization. The results show that the K-means clustering method successfully segments customers based on similar behavior patterns, which can be used for market segmentation and strategy development. The application of this algorithm in purchasing behavior analysis is expected to provide deep insights and support better business decision-making, offering a competitive advantage for companies.

TEKNIK MACHINE LEARNING UNTUK ANALISA KLASIFIKASI KUALITAS UDARA: A REVIEW Alfian, Haris; Wahyuni, Sri; Revalino, Aqil; Mirano, M. Fitter; Rahmayana, Elsa; Mukhtar, Harun
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 4 No. 2 (2024)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v4i2.7617

Air quality has a significant impact on human health and the environment, making its monitoring and classification extremely important. This review explores the application of machine learning techniques in analyzing and classifying air quality. Various methods such as decision trees, support vector machines, neural networks, and ensemble learning are evaluated to assess their effectiveness in processing complex and multidimensional air sensor data. This study also discusses challenges in data collection and preprocessing, selection of relevant features, and interpretation of classification results. Furthermore, this review identifies recent trends and future research opportunities in the use of machine learning to improve the accuracy and efficiency of air quality monitoring systems. The analysis results show that machine learning techniques have great potential to enhance our understanding of air quality dynamics and support better decision-making in environmental management

IMPLEMENTASI ALGORITMA A STAR DALAM PENCARIAN RUTE TERPENDEK (SHORTEST PATH PROBLEM) PADA SISTEM PENCARIAN KANTOR POS DI KOTA PEKANBARU Mukhtar, Harun; Hendri, Yusriadi; Soni
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 2 No. 1 (2022)
Publisher : Department of Information System Muhammadiyah University of Riau

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.

OPTIMISASI ALGORITMA K-MEANS DENGAN METODE REDUKSI DIMENSI UNTUK PENGELOMPOKAN BIG DATA DALAM ARSITEKTUR CLOUD COMPUTING Putra, Bayu Anugerah; Mukhtar, Harun; Br Bangun, Elsi Titasari; Gusnanda, Alris; Maisyarah, Adila; Kurniawan, Muhammad Irgi; Pradipa, Raditya; Ali, Zurrahman Muhammad
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 5 No. 1 (2025)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v5i1.7616

In the era of big data, data clustering becomes a major challenge due to the complexity and huge volume of data. The K-means algorithm is one of the clustering techniques that is often used due to its simplicity. However, K-means faces difficulties in handling high-dimensional and large-volume data. This study proposes an optimization of the K-means algorithm using the Principal Component Analysis (PCA) dimensionality reduction method to improve the efficiency and accuracy of big data clustering in cloud computing architecture. The KDD Cup 1999 dataset is used to test this method. The dataset undergoes pre-processing and dimensionality reduction using PCA, then K-means clustering is applied. The clustering results are evaluated using the Silhouette Score and Davies-Bouldin Index. The implementation is carried out in the Google Colab environment to utilize cloud computing resources. The results show that dimensionality reduction using PCA significantly reduces computational complexity and improves clustering quality. This method is effective in clustering big data, making it an efficient solution for data clustering in cloud computing architecture.

Co-Authors ., Farid Hasfindra Abdul Ghofur Addarisalam, Alif Al Amien, Januar Aldi, M Tri Alfaizun Nur Alfidin Alfanico, Febrian Alfian, Haris Ali, Zurrahman Muhammad Alris Gusnanda Amin Hariyanto Aminuyati Amran, Hasanatul Fu'adah Amran, Hasanatul Fuadah Apriansyah Apriansyah Arkan, M Alif Arviero L Tobing, Yandi Aryanto, Eggy Asrul Abdurrahim, Abulkhair Auralia Rilda, Azzahra Awaluddin Ayodya Putri Baidarus Bayu Anugerah Putra Benu, M. Rajib Owiendra Br Bangun, Elsi Titasari Budi Arham Chan, Ridzky Dani Harlian Daniel Adi Putra Sitorus Danillo, Amadel Daud, Kauthar Mohd Deprizon, Deprizon Dermawan, Aldi Desti Mualfah Dhea Dahliana Amanda Diah Angraina Fitri Diah Angraini Putri Dian Utami Dinia Putri doni, Rhoma Durades, M.Azri Dwi Pramaditya, Ilham Edi Ismanto Edo Arribe, Edo Efry Hady Nata Eka Putra Evans Fuad Fadly Gunawan Fakhira Frisya Ramadhani Fatchiyah Maharani, Masti Fatma, Yulia Fatma, Yulia Febby Apri Wenando Fitri Handayani Fitri Handayani Fitria Aini, Fitria Fitriani, Aisyah Fu’adah Amran, Hasanatul Gunawan, Rahmad Gusnanda, Alris Hadi Nasbey Hafid, Afdhil Hafsari, Rizka Hanum Salsabila Hardian_Putra, Saddam Haris, Aidil Hartanto, Fizhra Dwi Putra Hasanatul Fu'adah Amran Hasanuddin Hasanuddin Hasanuddin, Hasanuddin, Hayami, Regiolina Hendri, Yusriadi Herlandy, Pratama Benny Ilham Dwi Pramaditya Indra Saputra Irawan, Eldi Januar Al Amien Januar Al Amien Januar Al Amin Jihan Aulia Jum’atul Zikri Ken Rio Agizki Khusnul Hanafi Khusyaini, Ilham Kultum, Fi Ardhi Kurniawan, Muhammad Irgi Lisman, Muhammad Lorenza, Dina Lutfi Mz, Al Agib M Arif Rucyat M Djodi Andikarama M. Yogi Riyantama Isjoni Maisyarah, Adila Marcelino, Ananda Mardiya, Ainul Mas’yuri, Dhina Nurriska Maulana, Ade Irvan Medikawaty Taufiq, Reny Mirano, M. Fitter Mohamad, Mohd Saberi Muchtadi, Bill Fikra Muhammad Abdul Al Aziz Muhammad Fithra Muhammad Ilham Akbar Muhammad Rifaldo Muhammad Taufik Munanda, Rizka Muzahaffar, Fatih Al Nengsih, Rafni Yulia NUR FADILAH Nuradlin Syafini Nurwijayanti O.K Saddam Hussein Okta Tri Antoni Permadi Permadi Peter Wijaya, Peter Pradipa, Raditya Prasasti, Aditia Prastiwi, Adila Pramudiah Prastiwi, Adila Pramudiah Pratiwi Gasril Prayoga, Yuda Putra, Afyuadri Rahma Dayani, Lilian Rahmad Firdaus Rahmad Firdaus Rahman Septiadi Rahman, Rayhan Aulia Rahmawilda, Rahmawilda Rahmayana, Elsa Rama Putra Ramanda, Yuki Rayhan, Aqeel Refni Wahyuni Remli, Muhammad Akmal Reny Medikawati Taufik Revalino, Aqil Rhoma doni Ricinur Ricinur Rico Apriandika Ridhollah, Farhan Rizki Yasin Rizki, Rafi Hamdan Royan Choiro Yahya Saputra Sy, Yandiko Saputra Weisdiyanto, Wahyu Septiana Srinandini Shafwan, Affif Dzaky Silvia Elki Putri Soni Sri Wahyuni Sunanto Sunanto Suryanti, Anggi Aprilia Syafutri, Trimaiyuza Maulina Syahril Syahril Syahril Syahrul R, Syahrul Taufiq, Reny Medikawati Tiara Putri, Rahma Triana Dahar, Ulya Trimuawasih, Diana Unik, Mitra Vanama, Melsa W. M. Azim Wan Salihin Wong, Khairul Nizar Syazwan Wen Jia Wide Mulyana Yordan, Gibril Yos Hendra, Yos Yoze Rizki Yulia Fatma Yulia Fatma Yusoff, Nooraini

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Journal : Journal of Software Engineering and Information System (SEIS)