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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 398 Documents
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Spatial Skyline Query Based on Surrounding Environment Untuk Data Streaming Menggunakan Apache-Spark Raden Muhamad Firzatullah; Taufik Djatna; Annisa Annisa; Andrianingsih Andrianingsih
Jurnal Teknologi dan Sistem Komputer 2022: Publication In-Press
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2022.14268

Abstract

Previous research on Spatial Skyline Query Based on Surrounding Environment left a challenge in finding skyline objects that support the use of mobile devices. This study introduces a method that allows users to search for spatial objects dynamically. Cloud-based streaming data services are currently available to support the dynamic search of spatial skyline objects. Under these conditions, streaming data requires a longer processing time. This study aims to examine the effectiveness and efficiency of Apache-Spark in developing Spatial Skyline Query Based on Surrounding Environment in processing streaming data. Further implementation of the developed algorithm can provide better location access for users on mobile devices. Comparative analysis of algorithm execution time is performed by comparing algorithm processing on a single processor and cluster computing using various evaluation parameters. The test results on each parameter show that the computation time of the proposed algorithm on a single computation is not as good as the previous algorithm. However, in cluster computing, the proposed algorithm is superior
Computer vision for sports Adriyendi Adriyendi
Jurnal Teknologi dan Sistem Komputer 2022: Publication In-Press
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2022.14373

Abstract

We explore theories and applications of Computer Vision (CV) in sports. We use the method proposed included: object, research question, search process, inclusion and exclusion, quality assessment, data collection, data analysis, and characteristics of the article. We review it based on problem, methods, interpretation, finding, and future work. We analyze it based on categories: recognition, motion, detection, classification, identification, and automation. Process CV in sports included computing technology, capture motion, multi-scenarios, application of statistical sports, output prediction, object measurement, performance, and object adjudication. We found that Machine Learning (ML) and Deep Learning (DL) were widely used on CV in sports. DL approach has more advantages than the ML approach because the DL approach is supported by high-performance computing and high-quality image datasets. The implication of this research is an artificial feature-based, multi-scenarios, syntaxis method, rapid prototype, indoor localization, and gaze method as big challenge and new potential research for CV in sports. 
Prediksi Siswa Putus Sekolah Swasta Menggunakan Algoritma Bayesian Network (Studi Pada : SMA Islam Al Wahid Kepung) Rifky Yunus Krisnabayu; Ahmad Afif Supianto; Satrio Agung Wicaksono
Jurnal Teknologi dan Sistem Komputer 2022: Publication In-Press
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2022.14121

Abstract

Masalah siswa putus sekolah di SMA Islam Al Wahidmembawa dampak kepada sekolah antara lain berkurangnya bantuan operasional yang diterima, berkurangnya jumlah rombongan belajar, dan hutang biaya siswa. Mempertimbangkan dampaknya bagi sekolah, penelitian ini bertujuan mengembangkan sistem prediksi dini siswa putus sekolah. Penelitian menggunakan Bayesian Network (BN) dengan tujuan mengetahui faktor yang paling berpengaruh, di mana tugas tersebut tidak dapat diselesaikan menggunakan naive bayes. Jumlah data yang digunakan dalam penelitian ini berjumlah 77 siswa dengan 18 siswa berlabel putus sekolah. Hasil dari penelitian ini menghasilakn sebuah model dengan akurasi bernilai 0,935 dan nilai area under curve sebesar 0,948. Struktur BN memperlihatkan bahwa faktor nilai rerata, mengikuti ekstrakurikuler, dan penghasilan ayah merupakan faktor yang paling berpengaruh terhadap siswa putus sekolah. Struktur BN memperlihatkan bahwa faktor nilai rerata, mengikuti ekstrakurikuler, dan penghasilan ayah merupakan faktor yang paling berpengaruh terhadap siswa putus sekolah.
Sistem Penghitung Jumlah Orang Menggunakan Metode SSD-MobileNet dan Centroid Tracking Afandi Nur Aziz Thohari; Aisyatul Karima; Angga Wahyu Wibowo; Kuwat Santoso
Jurnal Teknologi dan Sistem Komputer 2022: Publication In-Press
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2022.14213

Abstract

Salah satu penerapan kecerdasan buatan untuk mencegah penyebaran virus corona adalah dengan membuat sistem penghitung jumlah orang otomatis untuk mencegah kerumunan di dalam ruangan. Penelitian ini membahas mengenai pembuatan prototipe sistem penghitung jumlah orang menggunakan algoritma deep learning pada single board computer. Tujuan dari penelitian ini adalah untuk menghitung jumlah orang dalam suatu ruangan agar okupansi ruangan dapat ditekan. Kontribusi dari penelitian ini adalah mengkombinasikan dua metode visi komputer yaitu SSD-MobileNet untuk identifikasi objek orang dan centroid tracking untuk menghitung jumlah orang. Berdasarkan pengujian yang telah dilakukan menunjukan bahwa sistem telah dapat menghitung objek orang dengan akurasi 100% apabila jumlah orang yang memasuki ruangan berjumlah satu, dua, atau tiga secara bersama-sama. Kemudian sistem dapat mendeteksi objek dengan jarak maksimal 10 meter dan intensitas cahaya redup atau kurang dari 100 lux. Pada pengujian komputasi menunjukan bahwa sistem dapat memproses video dengan jumlah frame 30 fps dan kualitas video high definition (HD).
Pengaruh Berat Pengguna Terhadap Kontrol Kecepatan Motor DC Menggunakan Kontroler PID Untuk Pergerakan Kursi Roda Pintar Muhammad Iqbal Andreansyah; Sumardi Sumardi; Teguh Prakoso; Munawar A Riyadi
Jurnal Teknologi dan Sistem Komputer 2022: Publication In-Press
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2022.14358

Abstract

Kesulitan mobilitas dialami oleh sebagian populasi. Berbagai kursi roda elektrik telah dikembangkan untuk membantu mobilitas yang dilengkapi dengan motor penggerak. Terdapat banyak faktor yang mempengaruhi kecepatan kursi roda, salah satunya berat badan pengguna. Penelitian ini bertujuan mengembangkan sistem kontrol kecepatan kursi roda dengan memperhitungkan berat badan pengguna. Penelitian ini menggunakan kontroler PID (proportional-integral-derivative) dengan metode tuning Ziegler Nichols I. Parameter optimum diperoleh Kp 7,8 Ki 9,75 dan Kd 0,78, kemudian digunakan untuk kondisi tanpa bebean, dengan beban 42,6 kg , 58,7 kg, dan 65 kg. Hasil pengujian menunjukkan bahwa sistem mampu menanggung beban 65 kg dengan overshoot maksimum 25,80%, rise time 1,2 detik, dan settling time 4,90 detik. Respon transien sistem bertambah secara linear terhadap kenaikan berat beban pengguna.
Evaluations of Emotion Analysis of Tweets using Bidirectional Long Short Term Memory and Conventional Machine Learning Aliyah Kurniasih; Aloysius Kurniawan Santoso; Bagus Dwi Wicaksono; Hilman F Pardede
Jurnal Teknologi dan Sistem Komputer 2022: Publication In-Press
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2022.14141

Abstract

Many ideas are contained in the social media twitter as a form of expression for an event. This review can be used to determine a person's emotions based on text data so that we can determine the next action in addressing and responding to that opinion. Emotion classification on twitter can be done by recognizing the tweet text pattern of the user. In this study, representing emotions using the BiLSTM model and the Conventional Machine Learning model. The amount of learning rate and the number of layers and the optimizer used and the number of epochs in the BiLSTM model can affect the accuracy results. In the conventional machine learning model, the K value of the KNN, the selection of the naive bayes model on probalistic, and the Decision Tree variation in the values of Max-depth, min-leaves, min-split will affect the results of the accuracy value. So that we get a good model for the classification of emotional sentiments based on text data from an opinion on the tweets page. 
Aspect-Based Analysis of Telkomsel User Sentiment on Twitter Using the Random Forest Classification Method and Glove Feature Expansion Aditya Mahendra Zakaria; Erwin Budi Setiawan
Jurnal Teknologi dan Sistem Komputer 2022: Publication In-Press
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2022.14558

Abstract

In this modern era, people certainly very easy to access social media, one of which is Twitter. Twitter is usually used by the public in expressing opinions regarding current issues, product reviews, and many other things positive, negative, or neutral opinions, or can be interpreted as sentiment. This study aims to analyze the aspect-based sentiment of Telkomsel users on Twitter using random forest classification and the extension of the Glove feature. This study uses signal aspects and service aspects with a total dataset of 16988 data. A Random forest can be classified as relevant and accurate for sentiment analysis with the greatest accuracy of 80.37% in the signal aspect and 80.12% in the service aspect, and the expansion feature is proven to be able to increase the performance value of this study by 13.15% in the signal aspect. and 5.37% in the service aspect.
Adaptive Lighting System for Presence Detection and Indoor Room Brightness Control Mia Galina; Joana Victorine Harryanto
Jurnal Teknologi dan Sistem Komputer 2022: Publication In-Press
Publisher : Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jtsiskom.2022.14443

Abstract

According to the survey, 10% of the electricity used is for lights. Adaptive lighting is a term used to describe innovations that reduce energy consumption for lighting. Generally speaking, adaptive lighting is a highly developed system built with built-in sensors to react automatically without the assistance of the people to make a decision. The research aims to develop an adaptive lighting system with two main functions presence detection and fuzzy logic implementations for automatic brightness adjustments. Increased sensitivity in detecting the presence and movement of items, monitoring the lighting conditions in the room, and consideration of the system's energy efficiency, which was not the main emphasis of the previous study, are some improvements over earlier studies. The device was tested for five days to calculate the energy consumption efficiency of a 4.5 W bulb for 10 hours in total. With a 98.4 % accuracy rate, the adaptive lighting system has proven 74% more efficient than regular lighting.

Page 40 of 40 | Total Record : 398

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