JUTI: Jurnal Ilmiah Teknologi Informasi
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REMARKETING MEDIA ALTERNATIVES BASED ON CUSTOMER PREFERENCES
Full text linkRemarketing is a powerful tool for marketers to offer products over and over to existing customers or potential customers. By using remarketing, the marketers target to further down their sales funnel. As in traditional marketing, most online marketers find it challenging to deliver the best way of advertising their products according to what customers need or like. This research aims to achieve the right promotional media alternatives based on customer preferences. A clustering method was used to perform behavior segmentation on sales data. Then, customer reviews on the purchased products collected from online platforms were analyzed to obtain customer preferences. Finally, customer preference was mapped to some suitable promotion media. The experiment result showed that pipelining sales data and product reviews could obtain definite and distinct promotional media based on customer preference. Overall, this research may help online marketers bundle specific remarketing content into promotional media that matches to customer favorites
DELINEATION OF ECG FEATURE EXTRACTION USING MULTIRESOLUTION ANALYSIS FRAMEWORK
Full text linkECG signals have very features time-varying morphology, distinguished as P wave, QRS complex, and T wave. Delineation in ECG signal processing is an important step used to identify critical points that mark the interval and amplitude locations in the features of each wave morphology. The results of ECG signal delineation can be used by clinicians to associate the pattern of delineation point results with morphological classes, besides delineation also produces temporal parameter values of ECG signals. The delineation process includes detecting the onset and offset of QRS complex, P and T waves that represented as pulse width, and also the detection of the peak from each wave feature. The previous study had applied bandpass filters to reduce amplitude of P and T waves, then the signal was passed through non-linear transformations such as derivatives or square to enhance QRS complex. However, the spectrum bandwidth of QRS complex from different patients or same patient may be different, so the previous method was less effective for the morphological variations in ECG signals. This study developed delineation from the ECG feature extraction based on multiresolution analysis with discrete wavelet transform. The mother wavelet used was a quadratic spline function with compact support. Finally, determination of R, T, and P wave peaks were shown by zero crossing of the wavelet transform signals, while the onset and offset were generated from modulus maxima and modulus minima. Results show the proposed method was able to detect QRS complex with sensitivity of 97.05% and precision of 95.92%, T wave detection with sensitivity of 99.79% and precision of 96.46%, P wave detection with sensitivity of 56.69% and precision of 57.78%. The implementation in real time analysis of time-varying ECG morphology will be addressed in the future research
ENHANCEMENT OF DECISION TREE METHOD BASED ON HIERARCHICAL CLUSTERING AND DISPERSION RATIO
Full text linkThe classification process using a decision tree is a classification method that has a feature selection process. Decision tree classifications using information gain have a disadvantage when the dataset has unique attributes for each imbalanced class record and distribution. The data used for decision tree classification has 2 types, numerical and nominal. The numerical data type is carried out a discretization process so that it gets data intervals. Weaknesses in the information gain method can be reduced by using a dispersion ratio method that does not depend on the class distribution, but on the frequency distribution. Numeric type data will be dis-criticized using the hierarchical clustering method to obtain a balanced data cluster. The data used in this study were taken from the UCI machine learning repository, which has two types of numeric and nominal data. There are two stages in this research namely, first the numeric type data will be discretized using hierarchical clustering with 3 methods, namely single link, complete link, and average link. Second, the results of discretization will be merged again then the formation of trees with splitting attributes using dispersion ratio and evaluated with cross-validation k-fold 7. The results obtained show that the discretization of data with hierarchical clustering can increase predictions by 14.6% compared with data without discretization. The attribute splitting process with the dispersion ratio of the data resulting from the discretization of hierarchical clustering can increase the prediction by 6.51%
MODIFIKASI METODE PEMILIHAN FORWARDING NODE BERDASARKAN FAKTOR ARAH DAN KECEPATAN KENDARAAN PADA PROTOKOL ROUTING GPSR DALAM LINGKUNGAN VANETS
Full text linkVANETs (Vehicular ad hoc networks) merupakan teknologi yang digunakan untuk komunikasi antar kendaraan. Dalam VANETs, kendaraan bergerak dengan kecepatan tinggi dan arah yang berbeda-beda, sehingga menyebabkan jaringan komunikasi yang telah terbentuk berubah dengan cepat. Salah satu contoh protokol routing yang sering digunakan dalam komunikasi VANETs adalah GPSR. Greedy perimeter stateless routing (GPSR), routing protokol baru untuk jaringan nirkabel yang menggunakan informasi posisi node tujuan untuk membuat keputusan penerusan paket. Topologi jaringan VANETs yang sangat dinamis menyebabkan komunikasi antar node tidak stabil. Node next hop yang telah dipilih mungkin telah keluar dari jangkauan transmisi sebelum menerima paket. Penelitian ini bertujuan untuk memecahkan masalah dalam protokol routing GPSR terkait ketidakstabilan komunikasi karena posisi node yang berubah dalam mode greedy forwarding. Dalam penelitian ini penulis menambahkan set parameter yang digunakan untuk mengambil keputusan routing dengan memasukkan faktor kecepatan dan arah pergerakan kendaraan. Setiap node akan melakukan penghitungan rata-rata geometrik kecepatannya sebelum penyiaran beacon message. Informasi rata-rata geometrik tersebut akan ditambahkan pada beacon message. Setelah node menerima paket beacon message, node akan memperbarui informasi yang terdapat pada neighbor table. Pada penelitian ini, neighbor table juga menyimpan informasi posisi node pada waktu sebelumnya dan informasi rata-rata geometrik kecepatan. Informasi dalam neighbor table tersebut akan digunakan dalam pengambilan keputusan routing. Penelitian ini juga melakukan modifikasi pada metode penerusan paket greedy forwarding. Jika penerusan paket menggunakan metode greedy forwarding, tahapan pertama yang dilakukan adalah menemukan node-node yang berada dalam area komunikasi optimum. Selanjutnya dari node-node yang berada pada area komunikasi optimum, akan dilakukan seleksi pemilihan forwarding node. Node yang layak menjadi forwarding node adalah node yang paling minimal perbedaan rata-rata geometrik kecepatannya dan bergerak mendekati node tujuan. Diharapkan dengan penelitian ini dapat meningkatkan performa protokol routing GPS
GECOM: GREEN COMMUNICATION CONCEPTS FOR ENERGY EFFICIENCY IN WIRELESS MULTIMEDIA SENSOR NETWORK
Full text linkWireless multimedia sensor network (WMSN) is one of broad wide application for developing a smart city. Each node in the WMSN has some primary components: sensor, microcontroller, wireless radio, and battery. The components of WMSN are used for sensing, computing, communicating between nodes, and flexibility of placement. However, the WMSN technology has some weakness, i.e. enormous power consumption when sending a media with a large size such as image, audio, and video files. Research had been conducted to reduce power consumption, such as file compression or power consumption management, in the process of sending data. We propose Green Communication (GeCom), which combines power control management and file compression methods to reduce the energy consumption. The power control management method controls data transmission. If the current data has high similarity with the previous one, then the data will not be sent. The compression method compresses massive data such as images before sending the data. We used the low energy image compression algorithm algorithm to compress the data for its ability to maintain the quality of images while producing a significant compression ratio. This method successfully reduced energy usage by 2% to 17% for each data.
EFFECTIVENESS STUDIES OF THE LEARNING BASIC MATHEMATICAL OPERATIONS ON USERS USING EDUCATION GAMES WITH ESCALATING DIFFICULTY LEVEL IN SEVERAL TYPES OF GAMES
Full text linkMathematic is basic but fundamental knowledge, but in fact many students do not have the motivation to learn it because they think mathematic is boring. Therefore, an innovation is needed to motivate students, one of them is by using an educational game. Racing, shooting and fighting games are the most popular types of games in 2019 according to InvisionCommunity. Shooting game is a genre that used a lot in the educational games for learning math, while racing game and fighting game are not used much for educational games. This research aims to develop and measure the effectiveness of the games from these three genre of games as a means of learning elementary arithmetic at the elementary school level. The effectiveness of an educational game can be observed from the increment in learning outcomes obtained after conducting an experiment. We can know the most effective type of game in this experiment by compare the improvement in learning outcomes after playing all three games. The comparative analysis will be carried out using ANOVA. In this research, we used data from 60 participant with elementary level of education between grade 1 to 3. The results were obtained by calculating the difference in the participants\u27 initial scores obtained from before playing the game and participants’ final scores obtained after playing the educational game. The results show that educational racing games have the highest increase of 6.3% compared to shooter games with 3% increase or fighting games with increase of 4.3%
APPLIED MACHINE LEARNING IN LOAD BALANCING
Full text linkA common way to maintain the quality of service on systems that are growing rapidly is by increasing server specifications or by adding servers. The utility of servers can be balanced with the presence of a load balancer to manage server loads. In this paper, we propose a machine learning algorithm that utilizes server resources CPU and memory to forecast the future of resources server loads. We identify the timespan of forecasting should be long enough to avoid dispatcher\u27s lack of information server distribution at runtime. Additionally, server profile pulling, forecasting server resources, and dispatching should be asynchronous with the request listener of the load balancer to minimize response delay. For production use, we recommend that the load balancer should have friendly user interface to make it easier to be configured, such as adding resources of servers as parameter criteria. We also recommended from beginning to start to save the log data server resources because the more data to process, the more accurate prediction of server load will be
PENGEMBANGAN GREEDY PERIMETER STATELESS ROUTING (GPSR) DENGAN KONSEP OVERLAY NETWORK PADA VANETS
Full text linkGreedy Perimeter Stateless Routing (GPSR) merupakan protokol routing yang memiliki performa baik di lingkungan VANET. Protokol GPSR memiliki kelemahan ketika node selanjutnya mengalami keadaan local maximum, yaitu ketika node selanjutnya tidak dapat mengirim paket ke node selanjutnya dikarenakan tidak ada node di sekitar yang memiliki posisi terdekat dengan node tujuan atau semua node terdekat sudah pernah menerima paket tersebut. Untuk mengatasi keadaan local maximum, protokol GPSR dimodifikasi dengan konsep overlay network. Overlay network diterapkan dengan menggunakan route discovery milik protokol dynamic source routing (DSR). Hasil dari proses route discovery akan menjadi acuan pencarian virtual anchor point (VAP). VAP merupakan representasi dari overlay network dan berguna untuk mengganti acuan posisi node tujuan dalam metode greedy forwarding. Selain VAP, pemilihan node selanjutnya menerapkan metode area optimum dalam pemilihan node selanjutnya untuk menghindari node yang berada pada luar batas transmisi node pengirim. Dalam makalah ini, evaluasi dilakukan terhadap kinerja routing protocol pada skenario real. Hasil simulasi diukur berdasarkan nilai rata-rata packet delivery rasio (PDR), end to end delay dan routing overhead (RO). Jumlah node yang digunakan dalam simulasi dimulai dari 50, 100, dan 150 node. Dari simulasi yang dilakukan didapatkan bahwa real performa GPSR modifikasi dibandingkan dengan GPSR tradisional mengalami peningkatan nilai PDR sebesar 72%, tetapi terjadi peningkatan pada nilai rata-rata end to end delay sebesar 1118% dan peningkatan nilai rata-rata RO sebesar 0.6%
CLOUTIDY: A CLOUD-BASED SUPPLY CHAIN MANAGEMENT SYSTEM USING SEMAR AND BLOCKCHAIN SYSTEM
Full text linkSupply chain management (SCM) system is an essential requirement for companies and manufacturers to collaborate in doing business. There are many techniques to manage supply chains, such as using Excel sheets and web-based applications. However, these techniques are ineffective, insecure, and prone to human error. In this paper, we propose CLOUTIDY, a cloud-based SCM system using SEMAR (Service Market) and Blockchain system. We modify JUGO architecture to develop SEMAR as a broker between users and cloud service providers. Also, we apply the Blockchain concept to store the activity log of the SCM system in a decentralized database. CLOUTIDY system can solve several common cases: service selection, resource provisioning, authentication and access control. Also, it improves the security of data by storing each activity log of the supply chain management system in the Blockchain system
PENENTUANT JUMLAH CLUSTER OPTIMUM PADA SEGMEN RUTE PENERBANGAN MENGGUNAKAN DATA AUTOMATIC DEPENDENT SURVEILLANCE-BROADCAST
Full text linkTerdapat beberapa titik acuan dalam satu rute penerbangan untuk keperluan navigasi yang disebut waypoint. Pada penelitian ini penulis melakukan segmentasi untuk membagi satu rute penerbangan (Surabaya-Palu) menjadi 7 segmen yang terdiri dari 8 waypoint, dengan membuat garis imajiner secara tegak lurus melewati masing-masing waypoint. Pada tiap segmen dilakukan analisa terkait lokasi yang paling sering dilalui menggunakan pendekatan clustering.Dalam penelitian ini penulis menggunakan algoritma clustering K-means dengan optimasi centroid yang mengimplementasikan algoritma Ant Lion Optimizer (ALO) atau disebut dengan K-means-ALO. Jumlah cluster ditentukan sebelumnya, kemudian dilakukan validasi pengelompokan internal dengan menggunakan silhouette index. Hasil metode pengelompokan diuji nilai performansinya. Hasil akhir dari jumlah cluster yang sudah ditentukan diambil nilai validitas cluster terbaik yaitu jumlah cluster yang optimum pada tiap segmen area penerbangan.Pengujian dilakukan dengan membandingkan nilai silhouette index untuk setiap percobaan jumlah cluster terhadap kedua metode yaitu K-means dan K-means-ALO. Pada uji coba yang dilakukan, metode optimasi yang diusulkan menghasilkan validitas cluster yang lebih baik sesuai nilai silhouette index pada tiga segmen, yaitu segmen 2, 3, dan 5 akan tetapi signifikan di semua segmen berdasarkan uji statistik Analysis of Variance (ANOVA) dan uji lanjut Least Significant Difference (LSD)