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All Journal Lontar Komputer: Jurnal Ilmiah Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Journal of Education and Learning (EduLearn) JUTI: Jurnal Ilmiah Teknologi Informasi Journal of Telematics and Informatics Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) JOIV : International Journal on Informatics Visualization JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal RESISTOR (Rekayasa Sistem Komputer) Journal of Computer Science and Informatics Engineering (J-Cosine) EDUMATIC: Jurnal Pendidikan Informatika Jurnal Teknologi Informasi, Komputer, dan Aplikasinya (JTIKA ) Dielektrika : Jurnal Ilmiah Kajian Teori dan Aplikasi Teknik Elektro JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Jurnal Abdi Insani Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika (JUTIF) Jurnal Begawe Teknologi Informasi Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Lontar Komputer: Jurnal Ilmiah Teknologi Informasi

Fitri Bimantoro

Informatics Engineering Dept., Faculty Of Engineering, University Of Mataram

Author-ID : 434100

Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Public Health Social Sciences Transportation Other

Published : 102 Documents Claim Missing Document

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Articles

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Implementasi Modifikasi Kompresi Run-Length Encoding pada Steganografi Suwardiman Suwardiman; Fitri Bimantoro
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 4 No 2 (2020): December 2020
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v4i2.109

RLE is one of the methods to compress data, however it has disadvantages that the compressed data may become twice larger as the original size. Therefore, in this research RLE will be modified to solve the problem. In the experiment we tested 3 file format i.e. JPG, PNG and BMP. The testing on JPG and PNG shows that conventional RLE method is not able to compress all images because it obtained negative compression ratio with an average compression ratio about -97.4%, Meanwhile the compression with RLE modification shows that the all image successfully compress with an average compression ratio about 0.31%. The testing on BMP shows the conventional RLE method successfully compress 5 files out of 11 tested images with average compression ratio about -25.4%, Meanwhile the compression with modified RLE successfully compress all tested images with average compression ratio about 22.4 %.

Predict A Person's Personality Based On The Shape of Handwriting of The Letters "i", "o", and "t" Using The Levenberg Marquardt Backpropagation Method Annisa Mujahidah Robbani; I Gede Pasek Suta Wijaya; Fitri Bimantoro; Heri Wijayanto
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 5 No 2 (2021): December 2021
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v5i2.178

The literature shows that Graphology is common and relatively useful in our life. For example, as one of the job requirements. Professional organizations hire a professional handwriting analyst called Graphologist to analyze the characteristic traits of the candidates by identified their handwriting. However, the accuracy of handwriting analysis depends on how skilled the graphologist is, two graphologists which predict the same handwriting may give us a different result of the prediction. To improve the accuracy, we develop a system that can automatically predict a person’s personality based on the shape of the handwriting of the letters "i", "o", and "t" using the Levenberg Marquardt Backpropagation method. Based on this research we got the maximum accuracy by using 2 hidden layers. We got 71,42% of accuracy for the letter “i”, 76,92% of accuracy for the letter “o”, and 60% of accuracy for letter the “t”.

Pengenalan Pola Tulisan Tangan Suku Kata Aksara Sasak Menggunakan Metode Moment Invariant dan Support Vector Machine Riska Yulianti; I Gede Pasek Suta Wijaya; Fitri Bimantoro
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 3 No 2 (2019): December 2019
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

The research of Javanese and Balinese ancient script have been done by some researches. However, the researches still have problems, such as image scaling, noise reduction and image transformation. This research implemented moment invariant and support vector machine to solve these problems especially on Sasak ancient script. The input data used in this research was 2700 handwritten Sasak ancient script. The testing was done to know the effect of thinning and the number of feature by using zoning on the classification performance. Accuracy is used as performance indicator. The highest average accuracy is 89.76%, on the second scenario, the average accuracy obtained is 92.52%.

Analisis Efektifitas Metode Weighted Product dan TOPSIS dalam Mendiagnosa Serangan Asma Ade Ragil Purwandani; Ario Yudo Husodo; Fitri Bimantoro
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 3 No 1 (2019): June 2019
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

To diagnose asthma attack we use Weighted Product and TOPSIS method to analyze the data. The lack of Weighted Product for the expert system is there are no cost and benefit for the criteria. We use combined it with TOPSIS to determining an alternative preference based on the ideal positive and ideal negative solution. WP methods have advantages where it has an initial weight which is TOPSIS don’t have. Combining the two methods aims to determine the effectiveness of the method. We use 40 data test on two different experts and compare it with our proposed method in this research. The result shows that, for the first expert, we gain accuracy for Weighted Product, TOPSIS and combined of WP and TOPSIS are 12,5%, 12,5%, and 60% respectively and for the second expert, we gain 30%, 30%, and 70%. Its show that the combined methods are better used compared to the WP and TOPSIS methods.

Sistem Pakar Diagnosa Penyakit Kulit pada Manusia dengan Metode Dempster Shafer Anita Rosana MZ; I Gede Pasek Suta Wijaya; Fitri Bimantoro
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 4 No 2 (2020): December 2020
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v4i2.285

Skin is the broadest organ in the human body that covers the entire surface of the body and acts as a support for human life. Because of its outermost location, the skin is often attacked by various diseases. This research aims to build an expert system to diagnose 10 types of skin diseases caused by viruses, fungi, bacteria, and parasites based on the knowledge of 3 experts using the Dempster Shafer method to obtain conclusions of skin diseases. Each symptom of skin disease has a value of belief that is used to calculate conclusions in the Dempster Shafer method. Expert system applications that are built can run Android-based smartphones. Testing techniques used in this research are black-box testing, theoretical calculations, system accuracy and MOS (Mean Opinion Score). Comparison of the calculation on the system has been appropriate based on the theoretical calculations. System accuracy testing in 30 sample cases resulted in an accuracy of 90%, but if it was seen as a subsection of expert diagnosis, it resulted in a system accuracy of 92.22%. MOS testing on 30 respondents results in a MOS value of 4.24 from a scale of 5 which shows that the system is proper to use and categorized into a good system.

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.

Sistem Pakar Diagnosa Awal Penyakit Mata dengan Metode Bayesian Network Novanita Laylatul Husna; Fitri Bimantoro
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 4 No 2 (2020): December 2020
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v4i2.287

Almost every human activity needs an eye to support these activities, therefore it will have a bad effect if the eyes experience interference. Disorders that can be experienced in the eye can occur from minor disorders to disorders that cause loss of vision and even death. Based on the results of the Rapid Assessment Assessment of Avoidable Blindness (RAAB), the blindness rate in districts/cities in NTB was 4%. This is not only due to medical-related problems but also due to social problems related to knowledge from the community, facilities, and resources. To make it easier for the public to make an initial diagnosis of eye disease, one thing that can be done is to use an expert system. Various methods can be implemented for expert systems, one of which is the Bayesian Network method. Based on the results of accuracy testing that has been done, this application provides an accuracy rate of 84.99%. Whereas, if the system diagnosis results are a subset of expert diagnostic results, the accuracy rate is 89.99% and based on the results of the use made by the general public, this application has been running well and has provided clear information related to the diagnosis of eye disease.

Sistem Pakar Diagnosa Kelainan Sistem Ortopedi pada Manusia dengan Metode Forward Chaining dan Dempster Shafer: Expert System for Diagnosing Abnormalities of Human Orthopedics System using forward chaining and Dempster Shafer Method Nurhaini Rahmawati; Fitri Bimantoro
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 5 No 1 (2021): June 2021
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v5i1.382

The bones and skeleton are very important parts of orthopedics and are the most vulnerable parts of the body. One of the obstacles in the diagnosis of orthopedic disorders is the distance from the hospital and the few orthopedic doctors. This study developed an expert system that runs on an Android-based smartphone to diagnosa 13 types of abnormalities in the orthopedic system with 92 symptom input based on the knowledge of 3 experts using the forward chaining and dempster shafer methods to obtain conclusions about the type of orthopedic disorder suffered. Based on the test results with theoretical calculations, it is found that the system calculation results are in accordance with the results of manual calculations. In testing the accuracy of the system, from 30 examples of cases tested on 3 experts, the accuracy value was obtained based on the average expert weight of 81.11%, the weight of each expert in sequence is 80.00% for expert 1, 83.33% for expert 2, and 73.33% for expert 3, where this accuracy value shows that the performance of the dempster shafer method in diagnosing orthopedic disorders is good and it can be said that the dempster shafer method suitable to be applied in cases of orthopedic disorders. The MOS (Mean Opinion Score) test on 30 respondents resulted in an MOS value of 4.45 from a scale of 5 which indicates that the system is feasible to use and is categorized into a good system

Pengenalan Pola Tulisan Tangan Aksara Bima menggunakan Ciri Tekstur dan KNN: Handwriting Recognition of Bima Script using Texture Features and KNN Fitri Bimantoro; Arik Aranta; Gibran Satya Nugraha; Ramaditia Dwiyansaputra; Ario Yudo Husodo
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 5 No 1 (2021): June 2021
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v5i1.387

As the fact, that is Bima script did not familiar to bimanese, Bima script as a cultural heritage needs to be preserved. Pattern recognition has been used to recognize several of ancient script. Gray Level Co-occurence Matrix (GLCM) as features exctraction and K Nearest Neighbour (KNN) as a classifier show the good performance to recognize of an ancient script. so, in this research we use GLCM and KNN to recognize Bima script. we use 2640 images of handwritting bima Script that is collected from 10 volunter. Each volunter write 22 of Bima script twelve times each script. The experimental result show that the performance of our model is good enough, with 60.86% of accuracy that is obtained by manhattan distances.

Ekstraksi Fitur Citra Radiografi Thorax Menggunakan DWT dan Moment Invariant: Feature Extraction of Thorax Radiography Image Using DWT and Moment Invariant I Gede Pasek Suta Wijaya; Ditha Nurcahya Avianty; Fitri Bimantoro; Rina Lestari
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 5 No 2 (2021): December 2021
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v5i2.423

COVID-19 is an infectious disease caused by the coronavirus family, namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The fastest method to identify the presence of this virus is a rapid antibody or antigen test, but confirming the positive status of a COVID-19 patient requires further examination. Lung examination using chest X-ray images taken through X-rays of COVID-19 patients can be one way to confirm the patient's condition before/after the rapid test. This paper proposes a feature extraction model to detect COVID-19 through chest radiography using a combination of Discrete Wavelet Transform (DWT) and Moment Invariant features. In this case, haar wavelet transform and seven Hu moments were used to extract image features in order to find unique features that represent chest radiographic images as suspected COVID-19, pneumonia, or normal. To find out the uniqueness of the proposed features, it is coupled with the kNN and generic ANN classification techniques. Based on the performance parameters assessed, it turns out that the wavelet-based and moment invariant thorax radiographic image feature model can be used as a unique feature associated with three categories: Normal, Pneumonia, and Covid-19. This is indicated by the accuracy value of 82.7% in the kNN classification technique and the accuracy, precision, and recall of 86%, 87%, and 86% respectively with the ANN classification technique.

Co-Authors A.A.Sg. Mas Karunia Maharani Ade Ragil Purwandani Adi Sugita Pandey Afwani, Royana Agitha, Nadiyasari Agus Eko Minarno Ahmad Dia’ul Haqqi Ahmad Zafrullah Mardiansyah Aisyah, Yunda Akhyar, Halil Aldian Wahyu Septiadi Alif Sabrani Anita Rosana MZ Annisa Mujahidah Robbani Anugrah, Febrian Rizky Aohana, Mizanul Ridho Aprilla, Diah Mitha Aranta, Arik Arik Aranta Arik Aranta Ario Yudo Ario Yudo Husodo Ario Yudo Husodo Ario Yudo Husodo Ario Yudo Husodo Ario Yudo Husodo, Ario Yudo Arrie Kurniawardhani arrie kurniawardhany, arrie Ayu Septya Maulani B. Nurwahyu Hairani Bagaskara, Andhika Dwija Baiq Rizki Putri Utami Budi Irmawati Chaerus Sulton Cokro Mandiri, Mochammad Hazmi Daniel Swanjaya Darmawan, Riski dina hastari Dina Juliani U M, Eka Ditha Nurcahya Avianty Dwiyansaputra, Ramaditia Ellysabeth Usmiatiningsih Fachry Abda El Rahman Fadilah . Fahmi Syuhada Faqih Hamami fathin zulian tsany Fernanda Dicky Ivansyah Fiena Efliana Alfian Fuad Fadlila Surenggana Fuad Fadlila Surenggana Gibran Satria Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Gibran Satya Nugraha Grendis, Nuraqilla Waidha Bintang Haidar Rahman Haidra Rahman Hamidi, Mohammad Zaenuddin Hanung Adi Nugroho Heri Wijayanto Hidhayah, Ratu Nisful Laily husnul khotimah I B K Widiartha I Gede Andika I Gede Pasek Suta Wijaya I Gede Putu Wirarama Wadashwara Wirawan I Gede Putu Wirarama Wedashwara W I Gede Wirarama Wedashwara W. I Putu Teguh Putrawan I Putu Teguh Putrawan I Wayan Agus Arimbawa I Wayan Agus Arimbawa, I Wayan Agus Ibrahim, Zaidah Ida Bagus Ketut Widiartha Ida Bagus Ketut Widiartha Imam Tantowi Isye Arieshanti Jatmika, Andy Hidayat Kansha, Lyudza Aprilia Lalu Zulfikar Muslim Lidia Ardhia Wardani Liza Yuliana Khairani Marcellino, Hendy Maulana Surya Negara Maulana, Sutan Fajri Mizanul Ridho Aohana Moh. Ali Albar Moh. Azzam Al Husaini Muhamad Irzan Muhammad Afif Ma'ruf Muhammad Daden Kasandi Putra Wesa Muhammad Edy Kurniawan Basri Muhammad Giri Restu Adjie Muhammad Hadi Muhammad Hadiasri Muhammad Khaidar Rahman Muhammad Sholihul Hamdi Muhammad, David Arizaldi Muntari Muntari Murpratiwi, Santi Ika Nanik Suciati Nazibullah Nazibullah Ni Nyoman Citariani Sumartha Nindya Alita Rosalia Noor Alamsyah Novanita Laylatul Husna Novita Nurul Fakhriyah Nugraha, Gibran Satya Nuraqilla Waidha Bintang Grendis Nurhaini Rahmawati Nurhalimah Nurhalimah Obenu, Juanri Priskila Patriaji Ibrahim Maulana Prof. I Gede Pasek Suta Wijaya Putu Wahyu Pratama Rabbani, Budiman Raihan, Muhammad Dzulhi Ramadhani, Rizky Insania Ramaditia Dwiyansaputra Ramaditia Dwiyansaputra Ramdhani, Ghina Kamilah Ramlah Nurlaeli Rani Farinda Regania Pasca Rassy Rijalul Imam Rina Lestari Riska Yulianti Rival Biasrori rizka amalia Rizki Rahmadi Rizqullah, Muhammad Naufal Robert Silas Kabanga Rosalina Rosalina Salma Nabilla Ulpa Salsabila Putri Rajani Said Satya Nugraha, Gibran Setiawan, Lalu Rudi Susi Rahayu Suwardiman Suwardiman Tazkiya Aulia Rachman Teguh Ardian Samudra Ulandari, Alisyia Kornelia Umbara Diki Pratama Wahyu Alfandi Wildan Suharso Yogi Permana Yudhis, Putu Yudhis Yudo Husodo, Ario Yufis Azhar Yunia Puspita Wulandari Zuhraini, Marlia Zul Rijan Firmansyah

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