Jiko (Jurnal Informatika dan komputer)
Jiko (Jurnal Informatika dan Komputer) Ternate adalah jurnal ilmiah diterbitkan oleh Program Studi Teknik Informatika Universitas Khairun sebagai wadah untuk publikasi atau menyebarluaskan hasil - hasil penelitian dan kajian analisis yang berkaitan dengan bidang Informatika, Ilmu Komputer, Teknologi Informasi, Sistem Informasi dan Sistem Komputer. Jurnal Informatika dan Komputer (JIKO) Ternate terbit 2 (dua) kali dalam setahun pada bulan April dan Oktober
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<![CDATA[BRAIN TUMOR DETECTION FROM MRI IMAGES USING DISCRETE COSINE TRANSFORM FEATURES AND EXTREME LEARNING MACHINE ]]>
<![CDATA[Simeon Yuda Prasetyo]]>
<![CDATA[ JIKO (Jurnal Informatika dan Komputer) Vol 6, No 1 (2023) ]]>
Publisher : <![CDATA[JIKO (Jurnal Informatika dan Komputer) ]]>
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DOI: 10.33387/jiko.v6i1.5230
<![CDATA[A brain tumor is an abnormal growth of brain tissue and characterized by excessive cell proliferation in certain parts of the brain. One of the current, reliable technologies that can be used to identify brain tumors is Magnetic Resonance Imaging (MRI) scans. The scanned MRI images are then conventionally monitored and examined by a specialist for the presence of tumors. As the number of people suffering from brain tumors is significantly increasing and their corresponding mortality rate has reached 18,600 by 2021, research on designing more effective and efficient tools to assist medical specialists in identifying brain tumors is considered of great importance. In a previous study, a machine learning-based model demonstrated its ability to detect brain tumors with a classification accuracy of 92%. Several hyperparameters were computationally tested using public MRI datasets to obtain the most reliable detection/binary classification accuracy on MRI brain images. Sophisticated model accuracy was achieved by testing various neuronal units and ELM activation functions, followed by inserting a feature map extracted from the Discrete Cosine Transform (DCT). The model obtained the highest testing accuracy of 95% with several 20 ELM neuron units with a tanh activation function.]]>
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<![CDATA[jiko unkhair]]>
<![CDATA[ JIKO (Jurnal Informatika dan Komputer) Vol 6, No 1 (2023) ]]>
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DOI: 10.33387/jiko.v6i1.6069
<![CDATA[SUPPORT VECTOR MACHINE (SVM) ALGORITHM FOR STUDENT SENTIMENT ANALYSIS OF ONLINE LECTURES ]]>
<![CDATA[Abdul Muis]]>;
<![CDATA[Abdul Mubarak]]>;
<![CDATA[Arifandy M Mamonto]]>;
<![CDATA[Satria Dwi Surya]]>
<![CDATA[ JIKO (Jurnal Informatika dan Komputer) Vol 6, No 1 (2023) ]]>
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DOI: 10.33387/jiko.v6i1.5836
<![CDATA[Covid-19 was first discovered in Wuhan City, Hubei Province, China at the end of December 2019. According to the WHO (World Health Organization) as of October 13 2020, the number of positive confirmed cases of Covid-19 reached 38,103,332 cases, while in Indonesia the number of cases exposed to Covid-19 reached 268.85 cases and is likely to increase every day (Covid-19 Handling Task Force, 2020). The formulation of the problem that will be raised from this research is to measure the level of accuracy obtained from the results of classifying sentiments of distance learning during the Covid-19 pandemic using the Support Vector Machine (SVM) method and measuring the impact of implementing online lectures during the Covid-19 pandemic. The data used in this research is in the form of public responses regarding distance learning policies implemented during the Covid-19 pandemic, taken from January to March 2022. The data obtained will then be divided into training data as much as 80% of the the total data and test data is 20% of the total data. Based on the results of testing the previous Support Vector Machine classification model, the accuracy value for the entire system can be calculated at 70.8%. Based on the results of testing the previous Support Vector Machine classification model, the accuracy value for the entire system can be calculated at 70.8%.]]>
<![CDATA[IMPLEMENTATION OF INFORMATION GAIN AND PARTICLE SWARM OPTIMIZATION UPON COVID-19 HANDLING SENTIMENT ANALYSIS BY USING K-NEAREST NEIGHBOR ]]>
<![CDATA[Riana Riana]]>;
<![CDATA[Muhammad I Mazdadi]]>;
<![CDATA[Irwan Budiman]]>;
<![CDATA[Muliadi Muliadi]]>;
<![CDATA[Rudy Herteno]]>
<![CDATA[ JIKO (Jurnal Informatika dan Komputer) Vol 6, No 1 (2023) ]]>
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DOI: 10.33387/jiko.v6i1.5260
<![CDATA[In early 2020, a new virus from Wuhan, China, identified as the coronavirus or COVID-19, shocked the entire world. (Coronavirus Disease 2019). The government has made various attempts to combat this outbreak, despite the fact that the government's involvement in combating Covid-19 has many benefits and disadvantages. One of the most commonly debated subjects on Twitter is the Indonesian government's response to the Covid-19 virus. This research compares the k-nearest neighbor classification technique, Information Gain feature selection with the K-Nearest Neighbor classification algorithm, and Information Gain feature selection and Particle Swarm Optimization optimization with the K-Nearest Neighbor classification algorithm. Comparisons are performed to determine which method is more accurate. Because it is frequently used for text and data categorization, the K-Nearest Neighbor algorithm was selected. The K-Nearest Neighbor algorithm has flaws, including the ability to be fooled by irrelevant characteristics and being less than ideal in finding the value of k. The selection of the Information Gain feature could indeed solve this issue by decreasing Terms that are less important and to optimize the K-Nearest Neighbor categorization, an optimization method with the Particle Swarm Optimization algorithm is employed to maximize the K-Nearest Neighbor classification. According to the results of this research, the K-Nearest Neighbor categorization with Information Gain feature selection and Particle Swarm Optimization optimization is better than the K-Nearest Neighbor model without selecting features and without optimization and is better than the K-Nearest Neighbor model with Information Gain selecting features, notably 87,33% with a value of K 5.]]>
<![CDATA[Comparison of Forensic Tools on Social Media Services Using the Digital Forensic Research Workshop Method (DFRWS) ]]>
<![CDATA[Ghufron Zaida Muflih]]>;
<![CDATA[Sunardi Sunardi]]>;
<![CDATA[Imam Riadi]]>;
<![CDATA[Anton Yudhana]]>;
<![CDATA[Himawan I Azmi]]>
<![CDATA[ JIKO (Jurnal Informatika dan Komputer) Vol 6, No 1 (2023) ]]>
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DOI: 10.33387/jiko.v6i1.5872
<![CDATA[Social media applications currently play a role and become part of various human activities, on the other hand social media is also very vulnerable to various crimes. Some crimes on social media can be in the form of hate speech, defamation, fraud, gambling, pornography, and other harmful actions. This research applies the Digital Forensic Research Workshop (DFRWS) method to search for all data on twitter social media services running on the Android operating system using MOBILedit Forensic Express and Belkasoft Evidence Center tools. Twitter social media services in this research are used for activities by utilizing all the features in it. Activities carried out by twitter users become evidence that will be acquired using MOBILedit Forensic Express and Belkasoft Evidence Center tools. From the two tools used, a comparison was obtained that MOBILedit Forensic Express found more data on twitter social media than Belkasoft Evidence Center, the findings in these two tools made several contributions to social media investigations that run on the android operating system]]>
<![CDATA[EVALUATION OF SPBE SERVICE MATURITY LEVEL IN CENTRAL MALUKU DISTRICT GOVERNMENT USING SPBE 2020 FRAMEWORK ]]>
<![CDATA[arifin La Adu]]>;
<![CDATA[Rudy Hartanto]]>;
<![CDATA[Silmi Fauziati]]>
<![CDATA[ JIKO (Jurnal Informatika dan Komputer) Vol 6, No 1 (2023) ]]>
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DOI: 10.33387/jiko.v6i1.5422
<![CDATA[Information and Communication Technology (ICT) utilization in the implementation of government processes is a priority that the government continues to develop. To make it happen, the government, through Presidential Decree No. 95 of 2018 concerning the implementation of an electronic-based government system (SPBE), every government agency must implement SPBE in its services and evaluate the implementation of SPBE periodically. With this urgency, the government issued Panrb Regulation No. 59 of 2020 concerning guidelines for assessing the maturity level of SPBE to correct deficiencies in the previous Panrb Regulation No. 5 of 2018 because there were several mandates of Presidential Regulation No. 95 of 2018 that had not been accommodated in it. One of the domains that received changes is the SPBE Service domain. In the SPBE service domain, there are updates to the assessment questionnaire and the addition of indicators that were originally 11 service indicators to 16 maturity-level service indicators. The purpose of this study is to determine the maturity level of SPBE services using the SPBE 2020 framework through the assessment of aspects of electronic-based Government Administration Services and the value of electronic-based Public Service aspects in Central Maluku regency. The Data in this study were obtained through interviews, observation, and validation of supporting evidence. The results of this study indicate the value of the SPBE Service Domain index of 2.36. The result of this value is used as an assessment of the maturity level of SPBE services in the Central Maluku regency government. From the acquisition of the index value, the maturity level of SPBE services in the Central Maluku regency government is included in the “average” category. To improve the indicators of low-value SPBE services, the Central Maluku regency government needs to implement the improvement recommendations that have been given.]]>
<![CDATA[PUBLIC VALUE BASED E-GOVERNMENT MATURITY MODEL: A LITERATURE REVIEW ]]>
<![CDATA[Titisari Ramadhane]]>;
<![CDATA[Luthfi Ramadani]]>;
<![CDATA[Lukman Abdurrahman]]>
<![CDATA[ JIKO (Jurnal Informatika dan Komputer) Vol 6, No 1 (2023) ]]>
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DOI: 10.33387/jiko.v6i1.5898
<![CDATA[Public value is a means for evaluating the effectiveness and efficiency of public services and an E-Government maturity model that controls the process for developing and maintaining E-Government services. Previous studies have analyzed and discussed public values, maturity models. Therefore, it is necessary to examine what public values should be present in E-Government based on the E-Government maturity model. This study aims to develop public values based on the E-Government maturity model and fill the gaps in the literature research by categorizing the dimensions of public values and the existing E-Government maturity models. This research method uses a systematic literature review (PRISMA). A total of 60 articles were selected, classified, and analyzed according to the criteria of public value and the specified dimensions of the E-Government maturity model. From the results of the literature review analysis, there are similarities between the dimensions of public value and the dimensions of the E-Government maturity model so that some of these dimensions can be combined to form a new public value dimension based on considerations from the dimensions of the E-Government maturity model, namely (1). Public Services in Government (2). Dimensions of Administration in Government, (3). Open Government (OG), (4). Ethical Behavior and Professionalism, (5). Trust and Confidence in Government (6). Social Value in Government. This study aims to strengthen public values based on the E-Government maturity model. It is hoped that implementing sustainable E-Government services will become easier by analyzing public values based on the E-Government maturity model.]]>
<![CDATA[INFORMATION & TECHNOLOGY AUDIT OF E-GOVERNMENT USING COBIT A LITERATURE REVIEW ]]>
<![CDATA[Zitnaa Dhiaaul Kusnaa Washilatul Arba'ah]]>;
<![CDATA[Ema Utami]]>;
<![CDATA[Alva Hendi Muhammad]]>
<![CDATA[ JIKO (Jurnal Informatika dan Komputer) Vol 6, No 1 (2023) ]]>
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DOI: 10.33387/jiko.v6i1.5606
<![CDATA[The Indonesian government continues to strive to improve public services to meet global demands, one of which is the development of technology such as a broad and integrated internet known as e-government. In implementing the e-government concept, it is necessary to have an IT audit to align the IT management process with the plans, objectives, and business strategies of government institutions. One framework that can be used as a standard is COBIT. This study uses the Systematic Literature Review research method to answer Research Questions (RQ): RQ1 regarding how the COBIT framework is used in IT audit case studies, especially in the e-government field, RQ2 regarding the COBIT domain used in research. The results of the study obtained 32 journals that were selected through a literature search process, literature selection according to criteria, and quality assessment. The results of the study, especially in the context of the main research question, namely the journals reviewed using the COBIT framework with various versions in evaluating e-government implementation. In COBIT there is a workflow that starts from identifying problems in the organization to analyzing capability level. In this study, it is known that the COBIT 2019 version is more adaptable to organizational conditions and technological developments because this version has more domains and design factors have been added (answer RQ1). The COBIT framework has 5 domains, namely the EDM, APO, BAI, DSS, and MEA domains. The most dominant domains used in assessing e-government implementation in journals are the APO and DSS (answer RQ2).]]>
<![CDATA[DECISION SUPPORT SYSTEM FOR SELECTING THE BEST EMPLOYEE AT PT BANK DIGITAL BCA USING SAW METHOD ]]>
<![CDATA[Angga Ariyanto]]>;
<![CDATA[Muhamad Ryansyah]]>
<![CDATA[ JIKO (Jurnal Informatika dan Komputer) Vol 6, No 1 (2023) ]]>
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DOI: 10.33387/jiko.v6i1.5913
<![CDATA[The selection of the best employees is a long and complicated process. A person's decision is bad because the employee selection process is based on subjectivity. Therefore, we need a decision support system for the employee selection process. This decision support system allows to determine the value of the calculation of all criteria. The method used is Simple Additive Weighting (SAW). This method is a method for finding the weighted sum. In the case study of determining the best employees at PT Bank Digital BCA, there are four criteria, namely attendance, performance, assignment discipline and approval. Each alternative (employee) will have these criteria. In this case, to determine the best employee, we add the weight of the performance score for each alternative to all the attributes. A larger value will indicate that the alternative is more selected. In this case, the SAW method can determine the best employee based on the highest score. Previously, PT Bank Digital BCA did not use the specified method and criteria, it was also uncertain, after being tested with the established method and determined criteria, the results were very good and appropriate. Thus this system is able to handle the calculation of the best employee assessment at PT Bank Digital BCA so that there will be no difficulty in determining the best employee.]]>
<![CDATA[A FUZZY-BASED EXPERT SYSTEM FOR DETERMINANTS OF TEACHER PERFORMANCE ]]>
<![CDATA[dodi nofri yoliadi]]>
<![CDATA[ JIKO (Jurnal Informatika dan Komputer) Vol 6, No 1 (2023) ]]>
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DOI: 10.33387/jiko.v6i1.5796
<![CDATA[Performance is the level of success achieved by a person in carrying out their duties and responsibilities as well as their ability to achieve the goals and standards that have been set. Teachers' performance is evaluated on a regular basis at each school. Teacher performance evaluation is carried out to identify flaws in task execution and to gain an overview of the results to be achieved in the future. So far, teacher performance appraisal is done manually, which is very difficult and time-consuming and feels less objective. Therefore, a fuzzy-based assessment system needs to be designed so that it helps in making decisions more quickly, precisely, and objectively. Rules are designed and tested using the Mamdani fuzzy logic method, which is implemented through the Matlab Toolbox software. To produce a more accurate performance rating, more membership function output is needed so that a more accurate performance rating can be produced.]]>
