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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.
Arjuna Subject : -
Articles 413 Documents
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Strategi caching aplikasi berbasis in-memory menggunakan Redis server untuk mempercepat akses data relasional Mulki Indana Zulfa; Ari Fadli; Arief Wisnu Wardhana
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 2, Year 2020 (April 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.8.2.2020.157-163

Abstract

Utilization of an in-memory database as a cache can overcome relational database latency problems in a web application, especially when using a lot of join queries. This study aims to model the academic relational data into Redis compatible data and analyze the performance of join queries usage to accelerate access to relational data managed by RDBMS. This study used academic data to calculate student GPA that is modeled in the RDBMS and Redis in-memory database (IMDB). The use of Redis as an in-memory database can significantly increase Mysql database system performance up to 3.3 times faster to display student data using join query and to shorten the time needed to display GPA data to 52 microseconds from 61 milliseconds.
Navigasi robot bergerak berdasarkan landmark garis menggunakan kontroler Braitenberg dan pengolahan citra Ali Rizal Chaidir; Gamma Aditya Rahardi; Khairul Anam
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 3, Year 2020 (July 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2020.13643

Abstract

Line following and lane tracking are robotic navigation techniques that use lines as a guide. The techniques can be applied to mobile robots in the industry. This research applied the Braitenberg controller and image processing to control and obtain line information around the mobile robot. The robot was implemented using Arduino Uno as a controller. A webcam was connected to a computer that performs image processing using canny edge detection and sends the data to the robot controller via serial communication. The robot can navigate on the side of the line, and the success rate of the system is 100 % at a turn of 135 ° and 80 % at a turn of 90 °.
Sistem kendali kestabilan attitude quadrotor dengan metode self-tuning Fuzzy-PD Sumardi Sumardi; Hadha Afrisal; Wisnu Dyan Nugroho
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 2, Year 2020 (April 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.8.2.2020.164-170

Abstract

This research aims to develop a quadrotor control system for maintaining its position and balance from disturbance while hovering. A fast and reliable control technique is required to respond to high maneuverability and high non-linearity of six degrees of freedom system. Hence, this research focuses on designing a Self-Tuning Fuzzy-PD control system for quadrotor’s attitude. The designed control system utilizes input data from the Inertial Navigation System (INS). Then the quadrotor’s attitude is controlled by passing the PWM signal to the flight controller APM 2.6. The result shows that the average absolute error for the roll, pitch, and yaw angles are relatively small, as mentioned consecutively 2.079o, 2.266o, and 1.528o, while the maximum absolute errors are 6.314o, 6.722o, and 3.82o.
Segmentation of university customers loyalty based on RFM analysis using fuzzy c-means clustering Syahroni Hidayat; Ria Rismayati; Muhammad Tajuddin; Ni Luh Putu Merawati
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 2, Year 2020 (April 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (81.531 KB) | DOI: 10.14710/jtsiskom.8.2.2020.133-139

Abstract

One of the strategic plans of the developing universities in obtaining new students is forming a partnership with surrounding high schools. However, partnerships made does not always behave as expected. This paper presented the segmentation technique to the previous new student admission dataset using the integration of recency, frequency, and monetary (RFM) analysis and fuzzy c-means (FCM) algorithm to evaluate the loyalty of the entire school that has bound the partnership with the institution. The dataset is converted using the RFM approach before processed with the FCM algorithm. The result reveals that the schools can be segmented, respectively, as high potential (SP), potential (P), low potential (CP), and very low potential (KP) categories with PCI value 0.86. From the analysis of SP, P, and CP, only 71 % of 52 school partners categorized as loyal partners.
Perbandingan kinerja RSA dan AES terhadap kompresi pesan SMS menggunakan algoritme Huffman Laurentinus Laurentinus; Harrizki Arie Pradana; Dwi Yuny Sylfania; Fransiskus Panca Juniawan
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 3, Year 2020 (July 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2020.13468

Abstract

Improved security of short message services (SMS) can be obtained using cryptographic methods, both symmetric and asymmetric, but must remain efficient. This paper aims to study the performance and efficiency of the symmetric crypto of AES-128 and asymmetric crypto of RSA with message compression in securing SMS messages. The ciphertext of RSA and AES were compressed using the Huffman algorithm. The average AES encryption time for each character is faster than RSA, which is 5.8 and 24.7 ms/character for AES and AES+Huffman encryption and 8.7 and 45.8 ms/character for RSA and RSA+Huffman, from messages with 15, 30, 60, and 90 characters. AES decryption time is also faster, which is 27.2 ms/character compared to 47.6 ms/character in RSA. Huffman compression produces an average efficiency of 24.8 % for the RSA algorithm, better than 17.35 % of AES efficiency for plaintext of 1, 16, 45, and 88 characters.
Temu kembali dokumen sumber rujukan dalam sistem daur ulang teks Nathaniel Clarence Haryanto; Lucia Dwi Krisnawati; Antonius Rachmat Chrismanto
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 2, Year 2020 (April 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (613.945 KB) | DOI: 10.14710/jtsiskom.8.2.2020.140-149

Abstract

The architecture of the text-reuse detection system consists of three main modules, i.e., source retrieval, text analysis, and knowledge-based postprocessing. Each module plays an important role in the accuracy rate of the detection outputs. Therefore, this research focuses on developing the source retrieval system in cases where the source documents have been obfuscated in different levels. Two steps of term weighting were applied to get such documents. The first was the local-word weighting, which has been applied to the test or reused documents to select query per text segments. The tf-idf term weighting was applied for indexing all documents in the corpus and as the basis for computing cosine similarity between the queries per segment and the documents in the corpus. A two-step filtering technique was applied to get the source document candidates. Using artificial cases of text reuse testing, the system achieves the same rates of precision and recall that are 0.967, while the recall rate for the simulated cases of reused text is 0.66.
Maturity classification of cacao through spectrogram and convolutional neural network Gilbert E. Bueno; Kristine A. Valenzuela; Edwin R. Arboleda
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 3, Year 2020 (July 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2020.13733

Abstract

Cacao pod's ideal harvesting time is when it is about to be ripe. Immature harvest would result in hard cacao beans not suitable for fermentation, while overripe cacao pods lead to fungal-infected, defective, and poor-quality yields. The demand for high-quality cacao products is expected to rise due to advancing technology in the present. Pre-harvesting needs to provide optimal identification of which amongst the pods are ripened enough and ready for the next stage of the cacao process. This paper recommends a technique to determine the ripeness of cacao. Nine hundred thirty-three cacao samples were used to collect thumping audio data at five different pod's exocarp locations. Each sound file is 1 second long, creating 4665 cacao sound file datasets at 16kHz sample rate and 16-bit audio bit depth. The process of the Mel-Frequency Cepstral Coefficient Spectrogram was then applied to extract recognizable features for the training process. The deep learning method integrated was a convolutional neural network (CNN) to classify the cacao sound successfully. The experimental design model's output exhibits an accuracy of 97.50 % for the training data and 97.13 % for the validation data. While the overall accuracy mean of the classification system is 97.46 %, whether the cacao is unripe or ripe.
Comparative analysis of classification algorithms for critical land prediction in agricultural cultivation areas Deden Istiawan
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 4, Year 2020 (October 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2020.13668

Abstract

Currently, the identification of critical land, that has been physically, chemically, and biologically damaged, uses a geographic information system. However, it requires a high cost to get the high resolution of satellite images. In this study, a comparison framework is proposed to determine the performance of the classification algorithms, namely C.45, ID3, Random Forest, k-Nearest Neighbor, and Naïve Bayes. This research aims to find out the best algorithm for the classification of critical land in agricultural cultivation areas. The results show that the highest accuracy Random Forest algorithm was 93.10 % in predicting critical land, and the naïve Bayes has the lowest performance, with 89.32 % of accuracy in predicting critical land.
Implementasi vigenere cipher 128 dan rotasi bujursangkar untuk pengamanan teks Rihartanto Rihartanto; Riris Kurnia Ningsih; Achmad Fanany Onnilita Gaffar; Didi Susilo Budi Utomo
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 3, Year 2020 (July 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2020.13476

Abstract

Information that can be in the form of text, image, audio, and video, is a valuable asset that needs to be secured from unauthorized parties. This research aims to study the implementation of Vigenere cipher 128 (VC-128) and square rotation to secure text information. The square rotation is applied to increase the security of the encryption results obtained from VC-128. The randomness of the rotation results was measured using Shannon entropy based on the distance between characters, and the Avalanche Effect measured changes in the encryption results compared to the original text. The square rotation can increase the randomness of the VC-128 encryption results, as indicated by an increase in entropy values. The highest increase in entropy of 34.8 % occurs in repetitive texts with the square size that produces optimal entropy was a 9x9 medium-size square. The Avalanche effect for each test data shows inconsistent results ranging from 44.5 % to 49 %.
Discrimination of civet coffee using visible spectroscopy Graciella Mae L Adier; Charlene A Reyes; Edwin R Arboleda
Jurnal Teknologi dan Sistem Komputer Volume 8, Issue 3, Year 2020 (July 2020)
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2020.13734

Abstract

Civet coffee is considered as highly marketable and rare. This specialty coffee has a special flavor and higher price relative to regular coffee, and it is restricted in supply. Establishing a straightforward and efficient approach to distinguish civet coffee for quality; likewise, consumer protection is fundamental. This study utilized visible spectroscopy as a non-destructive and quick technique to obtain the absorbance, ranging from 450 nm to 650 nm, of the civet coffee and non-civet coffee samples. Overall, 160 samples were analyzed, and the total spectra accumulated was 960. The data gathered from the first 120 samples were fed to the classification learner application and were used as a training data set. The remaining samples were used for testing the classification algorithm. The study shows that civet coffee bean samples have lower absorbance values in visible spectra than non-civet coffee bean samples. The process yields 96.7 % to 100 % classification scores for quadratic discriminant analysis and logistic regression. Among the two classification algorithms, logistic regression generated the fastest training time of 14.050 seconds. The application of visible spectroscopy combined with data mining algorithms is effective in discriminating civet coffee from non-civet coffee.

Page 33 of 42 | Total Record : 413

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