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Journal of Computer Science and Informatics Engineering (J-Cosine)

jcosine
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Published by Universitas Mataram

ISSN : 25408895 EISSN : 25410806 DOI : -

Core Subject : Science,

Computer Science & IT

Journal of Computer Science and Informatics Engineering (J-Cosine) is a journal that is published by Informatics Engineering Dept., Faculty of Engineering, University of Mataram (Program Studi Teknik Informatika, Fakultas Teknik Universitas Mataram) under online and print ISSN: 2541-0806 and 2540-8895, respectively J-Cosine is also blind and peer-reviewed journal, which the reviewer processes are carried out by at least 2 reviewers who are decided by associate editor. The J-Cosine is published bi-annually.

Arjuna Subject : -

Articles 159 Documents

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Sistem Pakar Diagnosis Penyakit pada Ayam dengan Menggunakan Metode Dempster Shafer Salsabila Putri Rajani Said; I Gede Pasek Suta Wijaya; Fitri Bimantoro
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 4 No 1 (2020): June 2020
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Chicken is one type of poultry that has many benefits, so the chicken can be an option for livestock. This research was conducted to create an expert system that helps provide information to farmers about poultry diseases, especially broilers. This expert system is built on the Android platform and uses the Dempster Shafer calculation method to get the diagnosis of chicken disease. The data used in this study consisted of 38 symptoms and 10 diseases data which were limited to diseases caused by bacteria and viruses. Each symptom has the value of belief given by 3 veterinarians. This study used four types of testing in the form of black-box testing, questionnaire testing, theoretical testing, and accuracy testing. The results of the accuracy testing of the 30 cases given are 92.22% and the system accuracy is 93.33% if the system diagnosis results are assumed to be valid because it is a subsection of expert diagnosis. For questionnaire testing using the MOS, parameters obtained 4.58 results from a scale of 5, as well as theoretical calculation tests that get the same calculation results between the results of expert diagnoses and system diagnoses. Based on the test results, the system built is good and appropriate.

Rancang Bangun Sistem Conditioining Udara Berbasis IoT pada Studi Kasus Tanaman Selada Hidroponik Anak Agung Angga Dwipa; I Gede Putu Wirarama Wedashwara W; Ariyan Zubaidi
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 4 No 1 (2020): June 2020
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Air temperature and humidity as well as water temperature are very important environment variables in planting DFT hydroponic lettuce plants in a greenhouse. Controlling and monitoring the temperature and humidity generally still done manually by farmers. This problem can be solved by building an air conditioning system that implements the concept of the Internet of Things, which plays a role in automation control of actuators, and MQTT protocols as its data communication medium. Based on the test results, the system has been able to perform measurement and conditioning of air temperature and humidity, as well as water temperature in the greenhouse automatically. Comparison of observation and test result data with sunny weather conditions, showing that the average and maximum value of air and water temperature on test, lower compared to observation data. While the average and minimum value of humidity in the test are higher than the observation data.

Expert System of Diagnosing Building Damage due to Earthquake using Backpropagation Artificial Neural Network Method Topan Khrisnanda; Ida Bagus Ketut Widiartha; I Gede Pasek Suta Wijaya
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 4 No 1 (2020): June 2020
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Earthquake is one of the most destructive natural disasters. After the earthquake, experts were deployed to survey the damage that occurred. One of the main objectives of the assessment task carried out by experts is to evaluate and classify buildings into several categories based on the level of damage that occurs. In this study, an expert system that could facilitate the assessment of building damage due to the earthquake was made using Backpropagation neural network method. The testing techniques used in this system are blackbox, accuracy and Mean Opinion Score (MOS) testing. MOS testing conducted by 30 respondents produced an MOS value of 4.54 from a scale of 5. While the average accuracy of the system obtained is 82.22% of the 30 case cases tested by 3 building damage experts.

A Smartphone-Based of Wood Identification Using Image Feature Extraction Bambang Sugiarto; Elli A. Gojali; Herlan Herlan; Puji Lestari
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 4 No 1 (2020): June 2020
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Each wood species has their special characteristics which can be differentiated based on their anatomical structures through wood identification. One of the methods is by detecting macroscopic wood image using computer vision. This method is more rapid and accurate to identify wood species compared to the conventional method. In previous work, we have developed a computer vision technique for wood identification by combining Histogram of Oriented Gradient (HOG) and Support Vector Machine (SVM). As smartphone usage increasing worldwide, capturing wood structures using this smart device is very easy to do and can replace the use of digital microscopes. This paper propose a technique for extraction the wood species on smartphone using HOG method as well as the classification method using SVM on android smartphone. SVM was used to classify the extracted wood textures from the HOG features. In our experiments, wood images of 7 wood species were used i.e Mimusops_-elengi, Melanorrhoea wallichii, Acer niveum, Cratoxylon formosum, Agathis endertii, Dyera costulata and Knema glauca. Each species has a total of 100 training images and 100 testing images. The highest accuracy is obtained by Melanorrhoea wallichii and Agathis endertii species with 84.00% score. The Agathis endertii species has the highest sensitivity and the value reaches 86%. Moreover, the Melanorrhoea wallichii species has a highest score for specificity and precision

Rancang Bangun Aplikasi Tes Psikologi Online Berbasis Web untuk Menunjang Keputusan Kelas Peminatan Siswa (Studi Kasus Biro Instrumentasi Bimbingan Konseling Empatik Mataram) Riga Anggraini Putri; Moh. Ali Albar; Nadiyasari Agitha
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 4 No 1 (2020): June 2020
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Decisions of specialization classes in high school students can be made based on the recommendations of the psychology test results. At SMAN 1 Selong in collaboration with a certified institution namely Biro Instrumentasi Bimbingan dan Konseling Empatik Mataram to execute the tests. In this case, the psychological test system is still manual, the manual system of psychological testing activities requires a lot of cost and time. The results of these psychological tests are analyzed manually by institutional experts to obtain results from specialization classes and require a long time. Based on these problems, an online psychology test application was designed and built to streamline time costs. Psychological test results are analyzed automatically using the weighted product method to get the results of recommendations accurately and quickly. The criteria used by the weighted product method to obtain student specialization class recommendations are 13 criteria consisting of sub-tests on psychological tests. The suitability between the results of expert recommendations and weighted product recommendations is 70%. System testing uses the method of BlackBox testing and Mean Opinion Score (MOS). The results of testing the BlackBox method on functions that exist on the system have valid conclusions or the system can run as expected. The results of testing using MOS with 30 respondents on average 4.4 categorized the system running well.

Identifikasi Cyberbullying pada Kolom Komentar Instagram dengan Metode Support Vector Machine dan Semantic Similarity Lintani Afina Hajar Raudhoti; Anisa Herdiani; Ade Romadhony
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 4 No 1 (2020): June 2020
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Instagram is a popular social media platform where users can share photos and videos, and also post comments on other users postings. Although there are many benefits on sharing information and posting comments, the freedom of using a social media platform also has a negative effect. One of non-constructive actions performed by social media users is cyberbullying, a misuse of technology through social media to embarrass or threaten others. Cyberbullying could affect the social media users, especially the target victim, hence we have to build a system that can limit the negative posts. In this research, we tackle the cyberbullying detection on Instagram comments as a classification problem and employ the SVM classifier. As a supervised machine learning approach, the SVM method has limitation on processing new words that never found in the training data. Therefore, we employed a semantic information derived from pre-trained word embeddings to gather similar words that appear in the training data to substitute the unknown words in the testing data. The experimental results show that the use of semantic similarity information improve the classification accuracy by 7%, from 67% to 74%.

Segmentasi Otomatis pada citra Cone Beam Computed Tomography Gigi didasari Metode Level Set dengan Operasi dan Polinomial Fitting Fahmi Syuhada Syuhada; Agus Zainal Arifin
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 4 No 1 (2020): June 2020
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Abstract Automatic Segmentation of dental cone beam computed tomography (CBCT) images is challenging due to the intensity of the teeth that have low level intensity. In this paper we proposes a new method for automatic teeth segmentation in slices of CBCT images based on level let method using morphology operators and polynomial fitting. Morphology operators are used to construct the Region of Interest (ROI) area of dental objects in the image slice. ROI is used to focus the analysis process on areas of dental objects which generally have a polynomial pattern distribution. Polynomial fitting is obtained to estimation arc of teeth structure in CBCT images. Level Set is implemented to evolve the ROI to obtain the contours of dental objects. Comparison between proposed method result and the ground truth images shows that the method gives best average accuracy, sensitivity, and specificity value of 99.02%, 95.32%, 99.09%, respectively. This value that the proposed method is promising for accurate segmentation of the entire tooth form on CBCT images.

Rancang Bangun Aplikasi Pelaporan Keadaan Darurat di Kota Mataram(Studi Kasus Nomor Panggilan Darurat 112) I Made Dwi Mahardika; Royana Afwani; Moh. Ali Albar
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 4 No 1 (2020): June 2020
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Emergencies can occur anywhere and anytime, where handling these emergencies must be done quickly. This research was conducted to design and build an emergency reporting system in the city of Mataram. The emergency reporting system that was built took the workflow from the emergency call number 112. The system will be used by 4 users namely the citizen as a emergency reporter, call taker emergency call number 112 from Diskominfo as an information processor, admin as a call taker information processor and units such as ambulances and firefighters as the action takers of the submitted report. The system runs in 2 platforms, namely the web pages used by call takers and Android, which are used by the public and action units. The system is tested using the mean opinion score and black box testing. The results obtained by using the mean opinion score test is 3.6 or the fair category.

Part of Speech Tagging untuk Bahasa Jawa dengan Hidden Markov Model Ryan Armiditya Pratama; Arie Ardiyanti Suryani; Warih Maharani
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 4 No 1 (2020): June 2020
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Indonesia has many cultures and local language, one of the most is Javanese with the Javanese language. The Javanese language is used in the region of Central Java and East Java, the word structure of the Javanese language has a similar to the Indonesian word class. Part of Speech (POS) Tagging is a process for labeling word classes for each input word that corresponding. POS Tag for Indonesian Language has been done a lot and got very good accuracy with various method application. This study aims to provide the word class label for Javanese language and the datasets used was obtained from online news with Javanese Ngoko language. The method used in this study is the Hidden Markov Model (HMM) with use of the HMM method get the highest accuracy is 96.2 %. Keywords: POS Tagging, Javanese Ngoko, Labeling, Hidden Markov Model

Analisa Perbandingan Keakuratan Metode Certainty Factor dan Dempster Shafer untuk Diagnosia Dini Penyakit Hepatitis berbasis Mobile Cynthia Hayat; Amyou Amyou; Marcel Marcel
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 4 No 1 (2020): June 2020
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Hepatitis is an inflammation of the liver due to a viral infection that attacks and causes damage to cells and the function of the liver. Many methods are currently used in building expert systems, including Certainty Factor and Dempster Shafer. The selection of both Certainty Factor and Dempster Shafer methods is very suitable for expert systems. In the previous study there was the Certainty Factor method used to diagnose hepatitis but there was no accuracy, whereas in Dempster Shafer there was an accuracy rate of 90%. This study aims to find out the suitable method to diagnose hepatitis by comparing the method of Certainty Factor and Dempster Shafer. In this study the application is in the form of a mobile base using Android Studio and database storage with MySQL. After that, do the Application Validation Test with experts and accuracy testing is carried out using samples from expert diagnosis results. The results of the test obtained the accuracy of the test using the Certainty Factor method is 95%. While the accuracy of testing using the Dempster Shafer method is 90%.

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Home Page

OAI Link

Editorial Team

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Contact Name I Wayan Agus Arimbawa

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Location Kota mataram, Nusa tenggara barat INDONESIA

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Contact Name
I Wayan Agus Arimbawa

Contact Email
arimbawa@unram.ac.id

Phone
-

Journal Mail Official
jcosine@unram.ac.id

Editorial Address
-

Location
Kota mataram,

Nusa tenggara barat

INDONESIA