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<![CDATA[Sistem Pakar Metode Case Based Reasoning untuk Mengidentifikasi Penyakit Psoriasis ]]>
<![CDATA[Syahputra, M]]>;
<![CDATA[Defit, Sarjon]]>;
<![CDATA[Sumijan, S]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 1 ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i1.123
<![CDATA[Proriasis is a type of chronic disease of the human skin.problem of psoriasis At the end of the day, theis becoming more interesting because the main cause of this disease has not been found, which has only been found while the cause of psoriasis is genetics. Because the cause is not known for sure, this disease is difficult to cure. Although this disease is not contagious and life-threatening to sufferers, it can damage internal organs if not handled properly. This study aims to determine the level of accuracy in identifying psoriasis in humans. There are several types of symptoms that refer to psoriasis. Furthermore, the data is processed manually with themethod Case Based Reasoning and continued by using a-based expert system software website. The processing stage is to use theprocess, which retrieve is a process of finding the similarities between new cases and existing cases in the knowledge base. The results of the data processing are continued with the calculation of the level of accuracy. The result of testing this method is that there are 100% of the 12 test data. Based on the accuracy of the identification results of this system, this study is very precise in the level of identifying the level of accuracy of psoriasis in humans. Expert testing system has been able to identify thedisease psoriasis specific. Through thismethod Case Based Reasoning , the level of accuracy that can be obtained is quite accurate and can help skin and genital specialists in improving accuracy in identifyingdiseases Case Based Reasoning in humans.]]>
<![CDATA[Tingkat Pemahaman Siswa dalam Pembelajaran Daring dan Tatap Muka Langsung dalam Masa Pandemi Covid-19 Terhadap Bimbingan TIK Menggunakan Metode Backpropagation ]]>
<![CDATA[Salmiati, S]]>;
<![CDATA[Yunus, Yuhandri]]>;
<![CDATA[Sumijan, S]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3 ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i3.129
<![CDATA[The Covid-19 pandemic has a major impact on the world of education. Government policies to implement Distance Learning (PJJ) have an impact on learning in schools. Increasing ICT competence is needed to support the smooth running of PJJ. One of them is through ICT guidance activities during the Covid-19 Pandemic. SMP Negeri 1 Lengayang carried out online and face-to-face ICT guidance activities during the Covid-19 Pandemic. However, student learning outcomes in online and face-to-face learning have not shown maximum results. Various obstacles arise that affect student learning outcomes. Teachers have difficulty measuring the level of students' understanding of ICT guidance. Predicting the level of understanding of students is important as a measure of learning success during the Covid-19 Pandemic. This study aims to predict the level of understanding of students in online and face-to-face learning during the Covid-19 period, so that it can also help schools to take the right policies to improve the quality of learning for the future. This study uses the Backpropagation method of Artificial Neural Network (ANN). ANN is a part of artificial intelligence that can be used to predict. The data that is managed is a recap of the value of student cognitive learning outcomes during ICT guidance in online and face-to-face learning during the Covid-19 Pandemic. The results of calculations using the Backpropagation method with the Matlab application produce a percentage value for the level of student understanding, so that the accuracy value in prediction is obtained. With the results of testing the predictive accuracy of the level of understanding online and face-to-face with the 3-10-1 pattern, the best accuracy value is 95%. The prediction results can measure the level of students' understanding of learning during the Covid 19 Pandemic towards ICT guidance.]]>
<![CDATA[Prediksi Tingkat Kepuasan dalam Pembelajaran Daring Menggunakan Algoritma Naïve Bayes ]]>
<![CDATA[Damanik, Abdi Rahim]]>;
<![CDATA[Sumijan, S]]>;
<![CDATA[Nurcahyo, Gunadi Widi]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3 ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i3.137
<![CDATA[The growth of learning at this time is influenced by advances in data and communication technology. One of the data technologies that functioned in the world of learning during the COVID-19 pandemic was online education. Online education is used as a liaison between lecturers and students in an internet network that can be accessed at any time. The online media used are Whatsapp, Google Classroom, Google Meet, Cloud x and the Zoom application. This research aims to predict the level of student satisfaction in online education as well as to distribute donations to large academies in making policies related to improving the quality of education online. The information used was obtained by distributing questionnaires to 110 students of the 2020/2021 class. The parameters in the questionnaire are lecturer communication, online education atmosphere, student evaluation, module delivery. Naïve Bayes is a prediction method for finding simple probabilities based on the Bayes theorem with a strong assumption of independence. Rapid Miner is one of the tools used for testing information and viewing the results of accuracy based on revolutionary information. The results of testing using 80 training information and 30 testing information display an accuracy of 100%. There were 3 respondents who reported dissatisfaction and 27 respondents reported being satisfied with online education. On the dissatisfied prediction, the precision class has a value of 100%, on the other hand, the prediction of being satisfied is 100%, and the class recall of true, not satisfied, has a value of 100%, whereas the class recall of true is satisfied to have 100%.]]>
<![CDATA[Identifikasi dalam Penentuan Prioritas Usulan Kenaikan Jabatan Fungsional Pegawai Menggunakan Metode TOPSIS ]]>
<![CDATA[Zulvitri, Z]]>;
<![CDATA[Defit, Sarjon]]>;
<![CDATA[Sumijan, S]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3 ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i3.147
<![CDATA[Padang State Polytechnic (PNP) is one of the state universities located in the city of Padang, which has 39 Learning Laboratory Institution Functional Officials, who were later told by PLP. PLP is a Civil Servant (PNS) who is given the task, responsibility, authority and right to carry out activities in the field of learning laboratory management. The problem that occurs is that the PLP does not know the exact time of application for promotion and functional positions of each. Some of the difficulties occur in managing the sub-division of personnel in finding archives. This article is always increasing and accumulating each period of acceptance. So this research aims to process this staffing data to make it easier and to accelerate the promotion process. The method used is the Decision Support System (DSS) in identifying priorities for proposals for functional promotion. The DSS method used is Technique For Order Preference By Similarity to Ideal Solution (TOPSIS). The results of this study have the reliability in considering the shortest distance to the positive ideal solution and also the longest distance to the negative ideal solution. The alternatives and criteria used in this study consisted of 5 alternatives and 3 criteria. The value of ideal positive and negative solutions has a maximum value of K1 which is 0.66, K2 is 0.022, K3 is 0.05 and a minimum value of K1 is 0.1, K2 is 0.017, K3 is 0.022. The highest score in ranking is 2 people with a score of 1 and the lowest is 1 person with a score of 0.0008. So this research is very helpful in identifying promotion priorities appropriately.]]>
<![CDATA[Optimalisasi Penentuan Kriteria Penerima Bantuan Program Indonesia Pintar dengan Metode TOPSIS ]]>
<![CDATA[Ayudia, Dina]]>;
<![CDATA[Nurcahyo, Gunadi Widi]]>;
<![CDATA[Sumijan, S]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3 ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i3.151
<![CDATA[The distribution of scholarships is carried out to assist in the determination of recommending someone who deserves to receive a scholarship, a Decision Support System is needed because the system for selecting scholarship candidates is still manual, and has many weaknesses. The large number of scholarship participant applicants makes schools having difficulty handling manual data processing so that software is needed to simplify the data processing. There for not all students who apply to receive scholarships can be granted, because the number of students who apply is very large, it is very necessary to build an SPK with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method which can help provide recommendation for scholarship recipients. Based on the analysis of the DSS with the TOPSIS method, it was carried out by means of a questionnaire, interview observation and system implementation. In the assessment of scholarship acceptance, it can be used as a basis for facilitating decisions on scholarship recipients because the system will process data and provide information quickly, precisely and consistently to the principal of students to receive the best scholarships to be awarded. Can form a decision that is right, effective and efficient in managing data on student recipients who are truly entitled to receive the scholarship. The TOPSIS method can be used to determine scholarship recipients, SPK in the assessment of scholarship acceptance can facilitate decisions in grade 7 students of SMP Negeri 17 Padang proportionally based on the results of student data processing including family cards, parents 'jobs, parents' income, number of dependents of parents and age parents accurately and accurately because the system can minimize errors in the process of calculating data normalization.]]>
<![CDATA[Akurasi Klasifikasi Pengguna terhadap Hotspot WiFi dengan Menggunakan Metode K-Nearest Neighbour ]]>
<![CDATA[Syaljumairi, Raemon]]>;
<![CDATA[Defit, Sarjon]]>;
<![CDATA[Sumijan, S]]>;
<![CDATA[Elda, Yusma]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3 ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i3.152
<![CDATA[The Current wireless technology is used to find out where the user is in the room. Utilization of WiFi strength signal from the Access Point (AP) can provide information on the user position in a room. Alternative determination of the user's position in the room using WiFi Receive Signal Strength (RSS). This research was conducted by comparing the distance between users to 2 or more APs using the euclidean distance technique. The Euclidean distance technique is used as a distance calculator where there are two points in a 3-dimensional plane or space by measuring the length of the segment connecting two points. This technique is best for representing the distance between the users and the AP. The collection of RSS data uses the Fingerprinting technique. The RSS data was collected from 20 APs detected using the wifi analyzer application, from the results of the scanning, 709 RSS data were obtained. The RSS value is used as training data. K-Nearest Neighbor (K-NN) uses the Neighborhood Classification as the predictive value of the new test data so that K-NN can classify the closest distance from the new test data to the value of the existing training data. Based on the test results obtained an accuracy rate of 95% with K is 3. Based on the results of research that has been done that using the K-NN method obtained excellent results, with the highest accuracy rate of 95% with a minimum error value of 5%.]]>
<![CDATA[Kompetensi yang Optimal Terhadap Penilaian Kinerja Guru dengan Metode Simple Additive Weighting ]]>
<![CDATA[Alfarisdon, A]]>;
<![CDATA[Sumijan, S]]>;
<![CDATA[Nurcahyo, Gunadi Widi]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3 ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i3.154
<![CDATA[Professional teachers should be able to improve their quality to achieve the vision and mission of the school where the teacher is carrying out their duty. The main task of an educator is to provide students with the process of learning, educating, training and giving directions to create a better learning process. Besides carrying out the task of teaching, an educator also needs to be able to develop themselves sustainably in order to increase self-competencies. There are four competencies should be owned by an educator they are pedagogic, personality, social and professional. To measure those competencies, school head master have to conduct teacher assessment by pointed assessors. Teacher performance assessment functions to analyses teachers ' professionalism in learning processes at a school, teachers participation on self-empowerment activities as well as capacity building. This study aims to calculate the value of teacher performance assessment optimally based on competence through a decision support system. Simple Additive Weighting method is used in this decision support system. By using Simple additive weighting, the sum of weight ratings performance on each alternative in all the attributes can be collected. This decision support system used to make it easier to take a decision and a supporter of decision in performance evaluations. Dataset treat in this research was collected in SMP Negeri 25 Padang. The data consisting of four different criteria in accordance with teacher competence. The result of the study reaches the level of accuracy of 93%. This study is expected to bring benefits for school leaders as the reference in order to optimize the teacher performance evaluation objectively.]]>
<![CDATA[Prediksi Tingkat Kriminalitas Menggunakan Metode Single Moving Average (Studi Kasus Polres Asahan Sumatera Utara) ]]>
<![CDATA[Lubis, Mustopa Husein]]>;
<![CDATA[Sumijan, S]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4 (Accepted) ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i4.167
<![CDATA[Crime is all kinds of actions and actions that are economically and psychologically harmful that violate the laws in force in the State of Indonesia as well as social and religious norms. Ordinary criminal acts affect the security of the community and endanger their lives and minds. The research location is the Asahan Police which is an agency that can provide security and protection for the community, especially those in Asahan Regency. The problem that occurs in this location is that there is no prediction system in Asahan Regency, due to the lack of knowledge factor in processing crime rate data. So it is difficult to know how much increase or decrease in criminal cases committed at the Asahan Police. The data used is data on cases of murder, sexual monitoring, tracing, violent theft, weight theft, motorcycle theft, fraud and counterfeiting money for the last 5 years in 2016 as many as 2020. Based on these problems, create a system for the crime rate in the Regency. Asahan to anticipate future crimes. The system that will be made uses forecasting or forecasting. With the Single Moving Average forecasting method. The Single Moving Average method is a forecast for the time in the future. The results of the calculation of criminal acts in 2021 found that there were 3 cases of murder, 2 cases of sexual intercourse in 2021, 252 cases of the 2021 return, 27 cases of violent theft in 2021, and 348 cases of bicycle theft in 2021. motorbikes in 2021 which open 90 cases, in 2021 which opens 85 cases, and money counterfeiting in 2021 which opens 1 case.]]>
<![CDATA[Perangkingan Potensi Guru dalam Penentuan Calon Kepala Sekolah Menggunakan Metode TOPSIS ]]>
<![CDATA[Wardana, Bendra]]>;
<![CDATA[Sumijan, S]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4 (Accepted) ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i4.168
<![CDATA[Efforts to increase the value of the quality of education for students as the next generation of the nation require teachers who have competence in providing education to students. The competence of a teacher can be assessed when a teacher has carried out his duties in accordance with the standard provisions he has. The ranking of potential teachers is used to motivate teachers to be active in carrying out each activity and is expected to have a positive effect on their work to face challenges in this era of globalization. The data that is processed for the ranking of teacher potential is the assessment data of elementary school teachers sourced from the korwildik of the Batang kapas sub-district. This ranking is based on several criteria and weights are determined. Furthermore, this ranking is processed using a system created by the researcher. This ranking uses a method called TOPSIS to assist researchers in ranking. The TOPSIS method is a multi-criteria decision support method with the principle that the chosen alternative must have the closest distance from the positive and negative ideal solutions. The results of ranking with the TOPSIS method are able to support the ranking decisions of potential teachers using predetermined criteria. So that the highest value is found in the 5th alternative with a value of 0.7321 and the lowest value is found in the 1st alternative with a value of 0.2218. The ranking of potential teachers has proven to be able to help the South Coast District Education and Culture Office, especially the korwildik of the Batang kapas sub-district in determining prospective school principals.]]>
<![CDATA[Sistem Pakar dalam Mengidentifikasi Gejala Stroke Menggunakan Metode Naive Bayes ]]>
<![CDATA[Karim, Fajri]]>;
<![CDATA[Nurcahyo, Gunadi Widi]]>;
<![CDATA[Sumijan, S]]>
<![CDATA[ Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4 (Accepted) ]]>
Publisher : <![CDATA[Rektorat Universitas Putra Indonesia YPTK Padang ]]>
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DOI: 10.37034/jsisfotek.v3i4.173
<![CDATA[Stroke is a disease caused by brain damage caused by disruption of the blood supply to the brain. At this time in general, people are still not very familiar with how this stroke disease or do not realize the symptoms that may have appeared from the start. People also tend to be hesitant to visit the hospital to check their symptoms and feel they are delaying further examinations. This is certainly a scourge that continues to make the number of strokes increase. In assisting the community in identifying stroke disease, an expert system is needed that is able to identify the type of stroke based on the symptoms felt. The data used in this study were obtained from Brain Hospital. Dr. Drs. M. Hatta Bukittinggi which was later developed into a website-based system using the PHP Framework Laravel programming language and MySQL as the database. The system is built based on the Naive Bayes method which is one of the Expert System methods that has a high accuracy value. The use of this system is expected to be able to provide knowledge to the public about the symptoms that might lead to what type of stroke the user might suffer, so that the user can use the results of the system as a reference to visit the hospital and immediately get more targeted help. This system can perform calculations that match the results of the doctor's diagnosis with an accuracy value of 100% in identifying the type of stroke from 10 data samples used.]]>
