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Jurnal Teknologi dan Sistem Komputer
Published by Universitas Diponegoro
ISSN : 26204002     EISSN : 23380403     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Jurnal Teknologi dan Sistem Komputer (JTSiskom, e-ISSN: 2338-0403) adalah terbitan berkala online nasional yang diterbitkan oleh Departemen Teknik Sistem Komputer, Universitas Diponegoro, Indonesia. JTSiskom menyediakan media untuk mendiseminasikan hasil-hasil penelitian, pengembangan dan penerapannya di bidang teknologi dan sistem komputer, meliputi sistem embedded, robotika, rekayasa perangkat lunak dan jaringan komputer. Lihat fokus dan ruang lingkup JTSiskom. JTSiskom terbit 4 (empat) nomor dalam satu tahun, yaitu bulan Januari, April, Juli dan Oktober (lihat Tanggal Penting). Artikel yang dikirimkan ke jurnal ini akan ditelaah setidaknya oleh 2 (dua) orang reviewer. Pengecekan plagiasi artikel dilakukan dengan Google Scholar dan Turnitin. Artikel yang telah dinyatakan diterima akan diterbitkan dalam nomor In-Press sebelum nomor regular terbit. JTSiskom telah terindeks DOAJ, BASE, Google Scholar dan OneSearch.id Perpusnas. Lihat daftar pengindeks. Artikel yang dikirimkan harus sesuai dengan Petunjuk Penulisan JTSiskom. JTSiskom menganjurkan Penulis menggunakan aplikasi manajemen referensi, seperti Mendeley, Endnote atau lainnya. Penulis harus register ke jurnal atau jika telah teregister, dapat langsung log in dan melakukan lima langkah submisi artikel. Penulis harus mengupload Pernyataan Pengalihan Hak Cipta saat submisi. Artikel yang terbit di JTSiskom akan diberikan nomer identifier unik (DOI/Digital Object Identifier) dan tersedia serta bebas diunduh dari portal JTSiskom ini. Penulis tidak dipungut biaya baik untuk pengiriman artikel maupun pemrosesan artikel (lihat APC/Article Processing Charge). Jurnal ini mengimplementasikan sistem LOCKSS untuk pengarsipan secara terdistribusi di jaringan LOCKSS privat.
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Articles 11 Documents
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Search results for , issue "Volume 8, Issue 1, Year 2020 (January 2020)" : 11 Documents clear
Identification of fat-soluble vitamins deficiency using artificial neural network Noviyanti Sagala; Cynthia Hayat; Frahselia Tandipuang
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 1, Year 2020 (January 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.8.1.2020.6-11

Abstract

The fat-soluble vitamins (A, D, E, K) deficiency remain frequent universally and may have consequential adverse resultants and causing slow appearance symptoms gradually and intensify over time. The vitamin deficiency detection requires an experienced physician to notice the symptoms and to review a blood test’s result (high-priced). This research aims to create an early detection system of fat-soluble vitamin deficiency using artificial neural network Back-propagation. The method was implemented by converting deficiency symptoms data into training data to be used to produce a weight of ANN and testing data. We employed Gradient Descent and Logsig as an activation function. The distribution of training data and test data was 71 and 30, respectively. The best architecture generated an accuracy of 95 % in a combination of parameters using 150 hidden layers, 10000 epoch, error target 0.0001, learning rate 0.25.
Pembangkitan interpretasi tekstual berbahasa Indonesia berdasarkan data pemeriksaan kimia darah menggunakan pendekatan berbasis r-template Indra Aulia; Sarah Purnamawati; Junianto Junianto
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 1, Year 2020 (January 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.8.1.2020.44-53

Abstract

The result of the blood chemistry tests is usually presented in the form of a table written in abbreviations, numbers, and units. Unfortunately, the young doctors often require the time and experience for interpreting the blood chemistry tests into a textual representation, which is easy to read and understand. Therefore, this research aimed at developing a system (BTISys) that can generate the textual representation in the Indonesian language automatically based on the blood chemistry test. BTISys generates the representation using Natural Language Generation (NLG) approach based on the r-template method. The reliability of BTISys is measured by considering the naturalness of generated textual representation. The naturalness can be observed by three criteria, such as readability, clarity, and general appropriateness. The reliability of BTISys is quite good to generate the textual representation automatically. It can be seen from the readability, clarity, and general appropriateness, which reach 73 %, 70 %, and 60 % respectively, that implies the naturalness of generated textual representation.
Reduksi bising seismik secara adaptif menggunakan filter Wiener Sesar Prabu Dwi Sriyanto
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 1, Year 2020 (January 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.8.1.2020.12-20

Abstract

Seismic noise disrupts the earthquake observation system due to the frequency and amplitude of seismic noise similar to the earthquake signal. The filter process is one of the methods that can be used to reduce seismic noise. In this study, the Wiener filter algorithm was designed with the Decision-Directed method for Apriori SNR estimation. This filter was chosen because it is adaptive, so it can adjust to environmental conditions without requiring manual parameter settings. The data used are earthquake signals that occur in the Palu area, Central Sulawesi, which are recorded on PKA29 temporary seismic station from February 3 to April 28, 2015. After each signal data has been filtered, then it is evaluated by calculating SNR differences before and after filtering, the signal's dominant frequency, and the cross-correlation of the signal before and after filtering. As a result, the Wiener filter is able to reduce the noise content in earthquake signals according to noisy frequencies before earthquake signals. The impact is that SNR has increased with an average of 8.056 dB. In addition, this filter is also able to maintain the shape of earthquake signals. This is indicated by the normalization value of the cross-correlation between signals before and after the filter which ranges from 0.703 to 1.00.
Perbandingan penghitungan jarak pada k-nearest neighbour dalam klasifikasi data tekstual Wahyono Wahyono; I Nyoman Prayana Trisna; Sarah Lintang Sariwening; Muhammad Fajar; Danur Wijayanto
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 1, Year 2020 (January 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.8.1.2020.54-58

Abstract

One algorithm to classify textual data in automatic organizing of documents application is KNN, by changing word representations into vectors. The distance calculation in the KNN algorithm becomes essential in measuring the closeness between data elements. This study compares four distance calculations commonly used in KNN, namely Euclidean, Chebyshev, Manhattan, and Minkowski. The dataset used data from Youtube Eminem’s comments which contain 448 data. This study showed that Euclidian and Minkowski on the KNN algorithm achieved the best result compared to Chebycev and Manhattan. The best results on KNN are obtained when the K value is 3.
Optimasi naive Bayes classifier untuk klasifikasi teks pada e-government menggunakan particle swarm optimization Kuncahyo Setyo Nugroho; Istiadi Istiadi; Fitri Marisa
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 1, Year 2020 (January 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (39.269 KB) | DOI: 10.14710/jtsiskom.8.1.2020.21-26

Abstract

One of the public e-government services is a web-based online complaints portal. Text of complaint needs to be classified so that it can be forwarded to the responsible office quickly and accurately. The standard classification approach commonly used is the Naive Bayes Classifier (NBC) and k-Nearest Neighbor (k-NN), which still classifies one label and needs to be optimized. This research aims to classify the complaint text of more than one label at the same time with NBC, which is optimized using Particle Swarm Optimization (PSO). The data source comes from the Sambat Online portal and is divided into 70 % as training data and 30 % as testing data to be classified into seven labels. NBC and k-NN algorithms are used as a comparison method to find out the performance of PSO optimization. The 10-fold cross-validation shows that NBC optimization using PSO achieves an accuracy of 87.44 % better than k-NN of 75 % and NBC of 64.38 %. The optimization model can be used to increase the effectiveness of services to e-government in society.
Sistem deteksi ketepatan pembacaan surah al-Kautsar berbasis kata menggunakan mel frequency cepstrum coefficient dan cosine similarity Jans Hendry; Aditya Rachman; Dodi Zulherman
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 1, Year 2020 (January 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.8.1.2020.27-35

Abstract

In this study, a system has been developed to help detect the accuracy of the reading of the Koran in the Surah Al-Kautsar based on the accuracy of the number and pronunciation of words in one complete surah. This system is very dependent on the accuracy of word segmentation based on envelope signals. The feature extraction method used was Mel Frequency Cepstrum Coefficients (MFCC), while the Cosine Similarity method was used to detect the accuracy of the reading. From 60 data, 30 data were used for training, while the rest were for testing. From each of the 30 training and test data, 15 data were correct readings, and 15 other data were incorrect readings. System accuracy was measured by word-for-word recognition, which results in 100 % of recall and 98.96 % of precision for the training word data, and 100 % of recall and 99.65 % of precision for the test word data. For the overall reading of the surah, there were 15 correct readings and 14 incorrect readings that were recognized correctly.
Algoritme penggantian cache proxy terdistribusi untuk meningkatkan kinerja server web Marvin Chandra Wijaya
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 1, Year 2020 (January 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.8.1.2020.1-5

Abstract

The performance of web processing needs to increase to meet the growth of internet usage, one of which is by using cache on the web proxy server. This study examines the implementation of the proxy cache replacement algorithm to increase cache hits in the proxy server. The study was conducted by creating a clustered or distributed web server system using eight web server nodes. The system was able to provide increased latency by 90 % better and increased throughput of 5.33 times better.
Peningkatan quality of experience pada permainan online multiplayer berbasis Arduino dengan menggunakan MQTT server Gabe Dimas Wicaksana; Maman Abdurohman; Aji Gautama Putrada
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 1, Year 2020 (January 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (17.219 KB) | DOI: 10.14710/jtsiskom.8.1.2020.36-43

Abstract

Online multiplayer games require internet networks to play with opposing players more exciting because multiple players can fight each other. The game experiences lag, which is expressed as the quality of experience (QoE), is one of the most common problems for online multiplayer games, causing the games less exciting to play. This study examined the implementation of Message Queue Telemetry Transport (MQTT) as a communication protocol in multiplayer online games using Arduino and compared its performance against HTTP. QoE used data collected using the mean opinion score (MOS) method. The MQTT resulted in an average QoE score of 3.9 (Pingpong) and 4 (TicTacToe) MOS units, while on HTTP 3.8 (PingPong and TicTacToe). The use of the MQTT communication protocol can improve the QoE of multiplayer online game players compared to HTTP.
Model dan prototipe inkubator mobile menggunakan kontroler PID berbasis Arduino Uno Munadi Munadi; R. Andhika Pandu; Rizky Wiradinata; Hari Peni Julianti; Rudy Setiawan
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 1, Year 2020 (January 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.8.1.2020.69-77

Abstract

One of the causes of the high infant mortality rate in Indonesia is the lack of health support facilities in remote areas, including incubators, to keep the baby's body warm at a specific temperature. This research develops a model and prototype of a mobile incubator to carry and maintain the baby's temperature during emergencies to get further treatment to hospitals that have better facilities than incomplete health clinic facilities. The mobile incubator prototype uses a PID controller system with the optimum gain value Kp 1.501, Ki 0.016, and Kd -1,319 from the results of modeling and tuning in Matlab. The results of the bode plot analysis show that system stability was achieved with a gain margin of 109 dB. The incubator's operational mobility can last up to 59.6 minutes with two 12 V, 5 Ah batteries.
Optimasi decision tree menggunakan particle swarm optimization untuk identifikasi penyakit mata berdasarkan analisis tekstur Toni Arifin; Asti Herliana
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 1, Year 2020 (January 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (286.208 KB) | DOI: 10.14710/jtsiskom.8.1.2020.59-63

Abstract

The problem of visual impairment is a serious problem with increasing cases, ranging from visual impairment to the cause of blindness. This study examines the development of an identification application for the classification of patients with eye disorders using the Decision Tree (DT) method, which is optimized using Particle Swarm Optimization (PSO). This study used 311 eye image data, consisting of 233 normal eye images and 78 eye images with glaucoma, cataracts, and uveitis. The feature extraction used Gray Level Co-occurrence Matrix (GLCM), while the feature optimization used the PSO and the learning method used DT. This optimized visual impairment classification application can improve system accuracy to 88.09 %.

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