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INDONESIA
Indonesian Journal on Computing (Indo-JC)
Published by Universitas Telkom
ISSN : 24609056     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
Indonesian Journal on Computing (Indo-JC) is an open access scientific journal intended to bring together researchers and practitioners dealing with the general field of computing. Indo-JC is published by School of Computing, Telkom University (Indonesia).
Arjuna Subject : -
Articles 251 Documents
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Music Recommender System Using K-Nearest Neighbor and Particle Swarm Optimization Randika Dwi Maulana Rasyid; ZK Abdurahman Baizal
Indonesia Journal on Computing (Indo-JC) Vol. 7 No. 2 (2022): August, 2022
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2022.7.2.649

Abstract

In this day, users can listen to music anytime digitally and access them through the already available applications. A music recommender system is needed to help users choose music according to their interests and find music to listen to. K-Nearest Neighbor (KNN) is a popular method used in Collaborative Filtering (CF). In many studies, CF with the KNN method has been widely used, but it does not provide good performance. Thus, in this study, we use KNN, which will be optimized using Particle Swarm Optimization (PSO), which can improve the performance of the results obtained against the method used. System testing is done by comparing the performance of the KNN algorithm with the optimization results of KNN-PSO with several variables being observed, including the Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) values. The results of these recommender will predict the rating value where the KNN method gives MSE 4.48 and RMSE 2.54 while the KNN-PSO method gives MSE 1.70 and RMSE 1.30.
E-Commerce Recommender System on the Shopee Platform Using Apriori Algorithm Rachmi Helfianur; ZK Abdurahman Baizal
Indonesia Journal on Computing (Indo-JC) Vol. 7 No. 2 (2022): August, 2022
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2022.7.2.650

Abstract

The development of E-Commerce continues to increase every year, and all online shopping platforms continue to increase competition. Shopee as an online shopping platform offers various product categories that users need. To make it easier for users when shopping online, it is necessary to implement a product recommender system in E-Commerce. Therefore, in this study, we will build a recommender system using the a priori algorithm. The apriori algorithm is very widely used to find out the buying pattern of each user by looking at a combination of itemset. many recommender systems in e-commerce use various methods used, and provide recommendation results that display popular products, and based on the query results obtained. From the results of previous studies, there are similarities between products that have been liked by customers, so they do not have the best recommendations. Therefore, in this study we apply an apriori algorithm to add user confidence to the given recommendations, and to avoid overspecialization. In this research, we take the domain of electronics goods. In this study, the system produces the best value for association rules with a support value of 0.01, confidence 1.00, and lift 97.35.
Video Based Fire Detection Method Using CNN and YOLO Version 4 Muhammad Salman Farhan; Febryanti Sthevanie; Kurniawan Nur Ramadhani
Indonesia Journal on Computing (Indo-JC) Vol. 7 No. 2 (2022): August, 2022
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2022.7.2.654

Abstract

Fire detection is one of the technological efforts to prevent fire incidents. This is very important because the damage caused by fires can be minimized by having a fire detector. There are two types of fire detection, namely traditional-based and computer vision-based. Traditional-based fire detection has many shortcomings, one of which requires a close fire distance for activation. Hence, computer vision-based fire detection is made to cover the shortcomings of traditional-based fire detection. Therefore, in this study, we propose a video-based fire detection using a Convolutional Neural Network (CNN) Deep Learning approach supported by You Only Look Once (YOLO) object detection model version four. This study uses a dataset of various fire scenarios in the form of images and videos. The fire detection built in this study has an accuracy of above 90% with an average detection speed of 34.17 Frame Per Second (FPS).
Pengembangan Media Pelaporan Kegiatan Asisten Laboratorium Berbasis Web di Prodi Pendidikan Multimedia Alifiandi Nursanni Wiriadikusumah; Feri Hidayatullah Firmansyah; Fahmi Candra Permana
Indonesia Journal on Computing (Indo-JC) Vol. 7 No. 2 (2022): August, 2022
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2022.7.2.658

Abstract

Keperluan administrasi pelaporan kegiatan asisten laboratorium di Prodi Pendidikan Multimedia UPI Kampus Cibiru masih menggunakan media konvensional. Kasus pandemi virus Covid-19 yang terjadi menyebabkan permasalahan yang berimplikasi pada penundaan pencairan honor asisten laboratorium. Penelitian ini adalah sebuah pengembangan media pelaporan kegiatan asisten laboratorium di program studi pendidikan multimedia upi cibiru berbasis web dengan tujuan untuk mengatasi masalah yang berkaitan dengan keperluan administrasi pelaporan kegiatan asisten laboratorium. Pada penelitian ini menggunakan metode Waterfall sebagai metode pengembangan, dalam implementasinya penulis memanfaatkan ekosistem Node.js dan layanan firebase, serta membuat desain antarmuka yang responsif sehingga meningkatkan aspek aksesibilitas media. Hasil pengujian blackbox menunjukan sistem yang dibuat sudah berjalan dengan baik, sedangkan pengujian aksesibilitas seluruh halaman media yang dibuat dengan menguji di 2 tipe perangkat yang berbeda yaitu desktop dan mobile menggunakan tools Chrome Lighthouse menunjukan hasil dengan tingkat yang sangat baik dengan nilai rata rata 96,2 dari 10 halaman yang diuji. Pengembangan media pelaporan kegiatan berbasis web dapat membantu asisten laboratorium dalam mengatasi masalah keperluan administrasi konvensional.
Forecasting Fuel Consumption Based-On OBD II Data Satrio Nurcahya; Bayu Erfianto; Setyorini Setyorini
Indonesia Journal on Computing (Indo-JC) Vol. 7 No. 2 (2022): August, 2022
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2022.7.2.659

Abstract

Cyber Physical System consists of computing devices that communicate with each other by interacting with the physical world assisted by sensors and actuators with an iterative response. Intelligent Transportation System which aims to apply information and communication technology in every transportation area. Applying ITS to vehicles, especially in the aspect of fuel consumption, vehicles must begin to be able to analyze the use of fuel that is being used to provide users so that users can be more effective. Regarding the analysis of fuel consumption, several researchers have done this with several existing methods such as ANN, SVM and the like. The use of the Multivariate time series method is used as a solution to the forecast analysis of vehicle fuel consumption. In this study, data from vehicles obtained from OBD-II will be processed using the Multivariate time series method with output in the form of analysis and visual data from the forecast with parameters related to RPM, TPS and fuel consumption. So the expected result is the relationship between RPM, TPS and fuel consumption as well as the formation of a system model to obtain sample data related to RPM, TPS and fuel consumption.
Perancangan Aplikasi Pembelajaran Pemrograman Dasar Bahasa C untuk Kelas X Multimedia SMKN 1 Majalaya Rizki Cahya Iskandar; Fahmi Candra Permana; Feri Hidayatullah Firmansyah
Indonesia Journal on Computing (Indo-JC) Vol. 7 No. 2 (2022): August, 2022
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2022.7.2.660

Abstract

Penggunaan media sangat dibutuhkan untuk mengatasi media pembelajaran yang terbatas di sekolah, mengatasi kejenuhan dan kebingungan belajar tanpa alat untuk melakukan coding secara langsung. penggunaan media yang tepat dan bervariasi dalam proses pembelajaran dapat meningkatkan motivasi belajar dan dapat mengurangi sikap pasif peserta didik. Berdasarkan hal tersebut peneliti bermaksud mengembangkan media pembelajaran yang dapat digunakan oleh siswa di kelas X SMKN 1 Majalaya dengan tujuan dari penelitian ini ialah menghasilkan suatu produk media pembelajaran aplikasi Pembelajaran Pemrograman C pada mata pelajarangan Pemrograman Dasar dengan menggunakan dengan model penelitian ADDIE (Analysis, Design, Develoment, Implementation and Evaluation). Hasil dari produk tersebut berupa aplikasi yang dipasang di perangkat android dengan pembuatan aplikasi menggunakan perangkat lunak Construct 2 dan desain dengan Adobe Illustrator dibantu Canva. Hasil dari validasi kelayakan media pembelajaran yaitu validasi materi meperoleh rata-rata 91,75%, dan validasi media memperoleh rata-rata 90,11%, secara keseluruhan hasil validasi berpredikat sangat layak. Untuk uji coba kepada peserta didik memperoleh presentase 91,98% dengan predikat sangat layak. Dari hasil tersebut dapat disimpulkan bahwa aplikasi Pembelajaran Pemrograman C layak digunakan dalam mata pelajaran Pemrograman dasar pada program multimedia.
The Quality Analysis of Cashier Information System (Majoo) Using ISO 25010:2011 Method Based on Usability Characteristics Widya Asmara
Indonesia Journal on Computing (Indo-JC) Vol. 7 No. 3 (2022): December, 2022
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2022.7.3.668

Abstract

Perkembangan dunia bisnis terus bergerak pesat seiring dengan munculnya banyak pelaku usaha, khususnya usaha Food&Beverage. Salah satu hal yang dapat meningkatkan kenyamanan dan kepuasan pelanggan pada layanan yaitu menu yang dipesan dapat dihidangkan dengan cepat. Pada saat pelanggan melakukan pesanan baru maupun pesanan tambahan, pelanggan ingin disajikan tanpa harus menunggu terlalu lama, sesegera mungkin dan tanpa ada kesalahan, beberapa pemilik usaha masih menggunakan penelitian transaksi dengan cara manual dan tidak efektif. Hal ini membuat karyawan sering mengalami kesalahan dalam menghitung jumlah yang harus dibayar dan banyak waktu yang dibutuhkan untuk penelitian laporan yang tepat dan akurat. Tujuan dari penelitian ini adalah melakukan analisis kualitas sistem informasi kasir (Majoo) berdasarkan ISO 25010:2010 dengan karakteristik usability. Tahapan penelitian diawali dengan analisis masalah, penentuan metode, penentuan karakteristik dan subkarakteristik, penentuan bobot karakteristik dan subkarakteristik, penilaian pengujian karakteristik usability, perhitungan total penilaian, dan rekomendasi sistem tersebut. Diperoleh nilai yang didapat rata rata yaitu sebesar 80,5% di mana aplikasi dikatakan Baik dari segi fitur dan fungsional, tetapi terdapat penilaian rendah yaitu di dalam subkarateristik Learnability, dengan nilai 82,07%. Total nilai usability adalah 4,995. Secara fungsi dan fitur aplikasi majoo sudah memenuhi kebutuhan aktifitas bisnis di dawet Indonesia namun belum optimal menjalankan fungsi yang tersedia
Gated Recurrent Unit for Fall Detection on Motorcycle Smart Helmet with Accelerometer Sensor Aji Gautama Putrada
Indonesia Journal on Computing (Indo-JC) Vol. 7 No. 3 (2022): December, 2022
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2022.7.3.672

Abstract

Smart motorcycle helmets are an emerging topic that can provide convenience to motorcyclists, such as providing information about the gas tank and tire pressure through the sound on the helmet. However, extracting important features of sequential data from accelerometer sensors becomes challenging when attempting to add a fall detection function to the helmet. This study proposes a gated recurrent unit (GRU) for fall detection using an accelerometer mounted on a smart motorcycle helmet. The first step is to get the x-axis, y-axis, and z-axis data from the accelerometer for the fallen human condition and the non-falling human condition. The data preparation involves the autocorrelation function (ACF), the partial autocorrelation function (PACF), normalization, standardization, random oversampling, and one hot encoder. The last is to train the GRU model. We use long short-term memory (LSTM) and convolutional neural network (CNN) as benchmarks. Accuracy, Loss, Precision, Recall, and F1−Score are the metrics we use to measure model performance. The test results show that GRU has Accuracy that is better than LSTM and CNN, which are 0.98, 0.97, and 0.96, respectively. Then other GRU performances in fall detection using the accelerometer sensor are 0.99, 0.97, and 0.98 for Precision, Recall, and F1−Score, respectively.
The Perancangan Sistem Informasi Laporan Kegiatan Penanaman Modal Dengan Menggunakan Arsitektur Microservices Pada Kementerian Investasi/Badan Koordinasi Penanaman Modal Ari Tjahyono
Indonesia Journal on Computing (Indo-JC) Vol. 7 No. 3 (2022): December, 2022
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2022.7.3.674

Abstract

Pemerintah Indonesia membutuhkan investasi untuk mengoptimalkan potensi Indonesia. Kementerian Investasi menyediakan aplikasi berbasis web untuk layanan Laporan Kegiatan Penanaman Modal(LKPM) yang digunakan pelaku usaha untuk melaporkan kegiatan usahanya atas izin penanaman modal yang dimiliki. Dengan bertambahnya pengguna aplikasi LKPM seiring dengan bertambahnya jumlah realisasi penanaman modal, kondisi ini berpengaruh terhadap kinerja dari aplikasi tersebut. Adanya perubahan peraturan dan implementasi basis tingkat risiko usaha, membuat Kementerian Investasi perlu melakukan pengembangan aplikasi LKPM agar dapat terintegrasi dengan OSS, dengan mempertimbangkan pilihan arsitektur microservices untuk kebutuhan integrasinya. Tujuan penelitian ini adalah menganalisis kebutuhan fungsi-fungsi pelaporan dan pengawasan pada aplikasi LKPM Online. Tahapan penelitian diawali dengan Pengumpulan Data Awal, Telaah Pustaka, Identifikasi Kebutuhan, Analisis Kondisi, dan Rancangan Arsitektur Sistem untuk Implementasi Pengembangan LKPM Online. Hasil penelitian yaitu Arsitektur microservices digunakan dalam pembangunan dan pengembangan LKPM Online karena beberapa kelebihannya, seperti lebih mudah dikelola karena modul-modulnya dipecah mnjadi bagian-bagian kecil, serta karena terdapat kebutuhan pada LKPM Online yang terintegrasi dengan OSS. Dan rekomendasinya, Perancangan aplikasi LKPM Online dapat dilanjutkan ke proses pembangunan, pemeliharaan, dan pengembangan sesuai dengan Software Development Life Cycle dan Komparasi secara berkala dengan perkembangan teknologi perlu terus dilakukan, terutama pada sisi efektivitas dalam pembangunan arsitektur microservices dan manajemen proyek teknologi informasi.
Solving Tatamibari Puzzle Using Exhaustive Search Approach Enrico Christopher Reinhard; Muhammad Arzaki; Gia Septiana Wulandari
Indonesia Journal on Computing (Indo-JC) Vol. 7 No. 3 (2022): December, 2022
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2022.7.3.675

Abstract

Tatamibari is a puzzle that was first published in 2004 and was proven to be NP-complete in 2020. However, to the best of our knowledge, algorithmic investigation of the Tatamibari puzzle is relatively new and limited. There are discussions about an approach for solving the Tatamibari puzzle using the Z3 SMT solver, but there are no details regarding the steps of the algorithm as well as its explicit asymptotic upper bound. In addition, this solver requires an additional library that cannot be directly executed using standard libraries in an arbitrary imperative programming language. Hence, this paper discusses an exhaustive search approach for solving an arbitrary Tatamibari puzzle. We show that this algorithm can find all solutions to an \(m \times n\) Tatamibari instance with \(h\) hints in \(O(\max\{m^2 n^2, h^{mn-h} \cdot hmn\})\) time. We also use this algorithm to find the number of possible Tatamibari solutions in an \(m \times n\) grid for some small values of \(m\) and \(n\).

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