http://jsisfotek.upiyptk.ac.id/index.php/JSisfotek/issue/feed Jurnal Sistim Informasi dan Teknologi 2021-09-30T00:00:00SE Asia Daylight Time Prof. Dr. Jufriadif Na'am jsisfotek@upiyptk.ac.id Open Journal Systems http://jsisfotek.upiyptk.ac.id/index.php/JSisfotek/article/view/137 Prediksi Tingkat Kepuasan dalam Pembelajaran Daring Menggunakan Algoritma Naïve Bayes 2021-03-31T22:06:21SE Asia Daylight Time Abdi Rahim Damanik abdirahimdmk@gmail.com S Sumijan abdirahimdmk@gmail.com Gunadi Widi Nurcahyo abdirahimdmk@gmail.com <p>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%.</p> 2021-09-30T00:00:00SE Asia Daylight Time ##submission.copyrightStatement## http://jsisfotek.upiyptk.ac.id/index.php/JSisfotek/article/view/129 Tingkat Pemahaman Siswa dalam Pembelajaran Daring dan Tatap Muka Langsung dalam Masa Pandemi Covid-19 Terhadap Bimbingan TIK Menggunakan Metode Backpropagation 2021-04-03T14:03:36SE Asia Daylight Time S Salmiati salmi.santi@gmail.com Yuhandri Yunus salmi.santi@gmail.com S Sumijan salmi.santi@gmail.com <p>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.</p> 2021-09-30T00:00:00SE Asia Daylight Time ##submission.copyrightStatement## http://jsisfotek.upiyptk.ac.id/index.php/JSisfotek/article/view/156 Klasifikasi Kualitas Mutu Daun Gambir Ladang Rakyat Menggunakan Metode Convolutional Neural Network 2021-04-03T14:09:46SE Asia Daylight Time Teddy Winanda teddywinanda@gmail.com Yuhandri Yunus teddywinanda@gmail.com H Hendrick teddywinanda@gmail.com <p>Indonesia is one of the countries which have the best Gambier quality in the world. Those are a few areas in Indonesia which have best gambier quality such as Aceh, Riau, North Sumatera, Bengkulu, South Sumatera and West Sumatra. Kabupaten 50 Kota is one of the regencies in west Sumatra that supplies gambier in Indonesia. The gambier leaf selection is mostly done by manual inspection or conventional method. The leaf color, thickness and structure are the important parameters in selecting gambier leaf quality. Farmers usually classify the quality of gambier leaves into good and bad. Computer Vision can help farmers to classify gambier leaves automatically. To realize this proposed method, gambier leaves are collected to create a dataset for training and testing processes. The gambier image leaves is captured by using DLSR camera at Kabupaten 50 Koto manually. 60 images were collected in this research which separated into 30 images with good and 30 images with bad quality. Furthermore, the gambier leaves image is processed by using digital image processing and coded by using python programming language. Both TensorFlow and Keras were implemented as frameworks in this research. To get a faster processing time, Ubuntu 18.04 Linux is selected as an operating system. Convolutional Neural Network (CNN) is the basis of image classification and object detection. In this research, the miniVGGNet architecture was used to perform the model creation. A quantity of dataset images was increased by applying data augmentation methods. The result of image augmentation for good quality gambier produced 3000 images. The same method was applied to poor quality images, the same results were obtained as many as 3000 images, with a total of 6000 images. The classification of gambier leaves produced by the Convolutional Neural Network method using miniVGGNet architecture obtained an accuracy rate of 0.979 or 98%. This method can be used to classify the quality of Gambier leaves very well.</p> 2021-09-30T00:00:00SE Asia Daylight Time ##submission.copyrightStatement## http://jsisfotek.upiyptk.ac.id/index.php/JSisfotek/article/view/133 Tingkat Korelasi Prestasi Akademik terhadap Siswa SMP Menggunakan Metode Backpropagation 2021-04-14T07:04:18SE Asia Daylight Time Nasma Yeni nasmayeni74@gmail.com Yuhandri Yunus nasmayeni74@gmail.com <p>Student academic achievement plays an important role in determining the quality of a school. Student scores sometimes change each semester, there are increases and decreases. There is an assumption that students who scored well in the previous semester will be good in the next semester and vice versa. This method is expected to make it easier for educators to see the extent of changes in student academic achievement. The data tested were data from 60 grade VII students in 2 semesters. Furthermore, it will be tested using the MatLab application, then the results of the changes that will occur will appear. The results of this study found that the correlation between semester 1 scores and semester 2 TP scores. 2019/2020 is very good with an architectural pattern of 10-10-1 with an accuracy value of 95.3%. So students who excel in semester 1 are likely to excel in the next semester, so that they can help the school see the Correlation Level of Student Academic Achievement at SMPN 3 Lengayang.</p> 2021-09-30T00:00:00SE Asia Daylight Time ##submission.copyrightStatement## http://jsisfotek.upiyptk.ac.id/index.php/JSisfotek/article/view/135 Identifikasi dalam Penetapan Staf Dosen dan Karyawan Berprestasi dengan Menggunakan Metode SMART 2021-04-14T07:04:17SE Asia Daylight Time Nur Azizah azizahd03@gmail.com Gunadi Widi Nurcahyo azizahd03@gmail.com <p>STMIK Indonesia Padang annually selects the best lecturers and employees to give appreciation for the performance of lecturers and employees. Lecturers and employees who take the assessment to appreciate the Performance Appraisal must meet the requirements and participate in the assessment process. The purpose of this research is to identify in determining the staff of lecturers and staff with achievement who are shorter in terms of calculations and also in accordance with the criteria. The sample in this study consisted of 4 lecturer data and 3 employee data taken randomly from 36 lecturer data and 26 employee data sourced from LP3M STMIK Indonesia Padang. Based on the analysis of lecturer and employee data, several criteria were obtained for processing these criteria, namely for lecturers the suitability of teaching materials with RPS (K) (Q1) teaching materials (Q2), teaching time (Q3), research (Q4) and GPA (Q5). ) then for employees, namely attendance (R1), performance (R2) and loyalty (R3). The method in this research is SMART (Simple Multi - Attribute Rating Technique) because this method is able to solve problems with multi-criteria. The results of the data testing obtained were Lecturers with achievements, namely DHD lecturers with a value of 0.8521 and outstanding employees, namely ARD employees with a value of 0.9998. The results of this study are expected to provide solutions for the identification of outstanding lecturers and staff at STMIK Indonesia Padang based on predetermined criteria.</p> 2021-09-30T00:00:00SE Asia Daylight Time ##submission.copyrightStatement## http://jsisfotek.upiyptk.ac.id/index.php/JSisfotek/article/view/149 Prediksi Hasil Belajar Siswa Secara Daring pada Masa Pandemi COVID-19 Menggunakan Metode C4.5 2021-07-14T18:20:13SE Asia Daylight Time Yetti Fitriani yetti.fitriani@gmail.com Sarjon Defit yetti.fitriani@gmail.com Gunadi Widi Nurcahyo yetti.fitriani@gmail.com <p>Student learning in schools has changed since the Covid-19 pandemic. Student learning in normal conditions is carried out face-to-face and turns into online or online learning. The research was conducted to predict student learning outcomes during the COVID-19 pandemic so that the results of this study can be used as a reference in policymaking in schools. The C4.5 method was used in the study to classify the data for class XII of the Multimedia Department at SMKN 2 Padang Panjang and the classification results could predict student learning outcomes during the pandemic. Processed student value data were taken from 1 (one) subject as the research data sample. Analysis of the value of student learning outcomes using the C4.5 Method to obtain new knowledge from student learning outcomes data carried out during the COVID-19 pandemic. The data analyzed consisted of attributes of attendance, assignments, daily tests, and test scores which influenced the decision criteria for student learning outcomes in online learning. The learning outcome decision criteria consist of "Satisfactory" and "Not Satisfactory" which refer to the Minimum Completion Criteria. Tests conducted on the training data of learning outcomes show that the value of the Daily Test is the most influential attribute in decision making. Implementation of the results using the RapidMiner Studio 9.2.0 software and produces an accuracy of 83.33% of the test data testing with the rules of data analysis training results. The results of the C4.5 classification testing method in this study can be used to predict student learning outcomes. The test results with an accuracy of 83.33% can be recommended to help schools in making policies.</p> 2021-09-30T00:00:00SE Asia Daylight Time ##submission.copyrightStatement## http://jsisfotek.upiyptk.ac.id/index.php/JSisfotek/article/view/152 Akurasi Klasifikasi Pengguna terhadap Hotspot WiFi dengan Menggunakan Metode K-Nearest Neighbour 2021-04-15T01:18:20SE Asia Daylight Time Raemon Syaljumairi remon17@gmail.com Sarjon Defit raemon@pnp.ac.id S Sumijan raemon@pnp.ac.id Yusma Elda raemon@pnp.ac.id <p>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%.</p> 2021-09-30T00:00:00SE Asia Daylight Time ##submission.copyrightStatement## http://jsisfotek.upiyptk.ac.id/index.php/JSisfotek/article/view/143 Sistem Pendukung Keputusan bagi Penerima Bantuan Komite Sekolah Menggunakan Metode Topsis 2021-04-16T23:15:08SE Asia Daylight Time Suci Mardayatmi aciemar@gmail.com Sarjon Defit aciemar@gmail.com Gunadi Widi Nurcahyo aciemar@gmail.com <p>Vocational High School Number 3 Mukomuko was the school that has given assistance for the learners. It was by exempting learners from paying committee charge monthly, it called Bantuan Komite Sekolah (BKS). In order to give motivation for the learners who was unfortunate to keep staying at the school, so it can make the learners to keep going on teaching and learning process (KBM). This research used Topsis method by collecting data for the prospective scholarship learners as many as 20 learners by categorizes were parents’ revenue, the total numbers of duties, the distance of residence, the average score of report and the condition of living environment. The result of try out from 20 learners who was obtain BKS by using Topsis Method showed that there were 18 learners who were significant to obtain scholarship by validity score was 90%. It was be a sample, before Topsis Method was used and the data was reliable after using Topsis Method. The development of supporting decision application system used Topsis Method that was getting in more accurated qualification. Futhermore, this system can help the school in constructing decisions to get the result be more advantageous in determining for the next BKS recipients.</p> 2021-09-30T00:00:00SE Asia Daylight Time ##submission.copyrightStatement## http://jsisfotek.upiyptk.ac.id/index.php/JSisfotek/article/view/151 Optimalisasi Penentuan Kriteria Penerima Bantuan Program Indonesia Pintar dengan Metode TOPSIS 2021-04-17T12:39:35SE Asia Daylight Time Dina Ayudia dinaayudia6216@gmail.com Gunadi Widi Nurcahyo dinaayudia6216@gmail.com S Sumijan dinaayudia6216@gmail.com <p>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.</p> 2021-09-30T00:00:00SE Asia Daylight Time ##submission.copyrightStatement## http://jsisfotek.upiyptk.ac.id/index.php/JSisfotek/article/view/142 Tingkat Kepuasan Pasien RSIA Siti Hawa dalam Upaya Peningkatan Kualitas Pelayanan Menggunakan Metode Service Quality (SERVQUAL) 2021-04-17T22:53:44SE Asia Daylight Time Rika Apriani rikaapril7@gmail.com Gunadi Widi Nurcahyo rikaapril7@gmail.com <h1>Patient satisfaction is an important indicator in improving the quality of the hospital. RSIA Siti Hawa always tries to improve the quality of the hospital in order to provide excellent service to patients. One of the efforts made to improve the quality of the hospital is by knowing the level of patient satisfaction. The purpose of this study was to determine the extent of patient satisfaction with the Siti Hawa Hospital service so that it can assist management in evaluating and improving services to improve quality. This research was conducted using the Service Quality (SERVQUAL) method which has five dimensions, namely tangible (physical evidence), reliability (reliability), responsiveness (responsiveness), assurance (assurance) and empathy (empathy). This measurement is carried out to identify the patient's expectations and perceptions so that from the five dimensions of Service Quality, the overall service quality can be seen by looking at the value of the gap that occurs due to the mismatch between patient expectations and perceptions. The data processed in this study were questionnaire data from 30 respondents / patient. The result of this test is that the service quality of the five dimensions of service quality consisting of 14 question attributes has a positive gap value. The highest gap value is 0.47 in the 12th question attribute regarding politeness and friendliness of officers in providing services, and the lowest gap value is in the 6th attribute with a value of 0.27 regarding the timeliness of service schedules. Based on the dimensions, the order of the rank dimensions from the highest is empathy, assurance, responsiveness, tangible and reliability. Based on the results of this study, it can be concluded that the services provided by RSIA Siti Hawa to patients can be said to be good, and the results of these measurements can be used as an evaluation in improving the quality of hospital services.</h1> 2021-09-30T00:00:00SE Asia Daylight Time ##submission.copyrightStatement## http://jsisfotek.upiyptk.ac.id/index.php/JSisfotek/article/view/154 Kompetensi yang Optimal Terhadap Penilaian Kinerja Guru dengan Metode Simple Additive Weighting 2021-04-17T22:53:42SE Asia Daylight Time A Alfarisdon alfarisdon@gmail.com S Sumijan alfarisdon@gmail.com Gunadi Widi Nurcahyo alfarisdon@gmail.com <p>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.</p> 2021-09-30T00:00:00SE Asia Daylight Time ##submission.copyrightStatement## http://jsisfotek.upiyptk.ac.id/index.php/JSisfotek/article/view/146 Klasterisasi Tingkat Masa Studi Tepat Waktu Mahasiswa Menggunakan Algoritma K-Medoids 2021-04-18T14:27:15SE Asia Daylight Time Fahmi Firzada fahmifirzada@gmail.com Yuhandri Yunus fahmifirzada@gmail.com <h1>The period of study on time is one of the parameters of a student's success in completing college to obtain a bachelor's degree. A student is said to have completed his studies on time if he is able to complete his studies less than or equal to the predetermined time. Academic Provides facilities to find out the estimated time of student graduation. By providing information on which students are included in the cluster, they can complete their studies on time and which students do not complete their studies on time. In this study, the data processed were data from students who had graduated in the previous year. Then the data is processed using rapidminer software. This study applies the K-Medoids algorithm in clustering. The result of testing this method is to determine the student clusters who can complete the study period on time and the student clusters who cannot complete the study period on time. This research is expected to contribute to the campus in evaluating the tendency of students to complete their studies on time or not. The results of the evaluation of performance can produce information for study programs, lecturers and students in making policies.</h1> 2021-09-30T00:00:00SE Asia Daylight Time ##submission.copyrightStatement## http://jsisfotek.upiyptk.ac.id/index.php/JSisfotek/article/view/147 Identifikasi dalam Penentuan Prioritas Usulan Kenaikan Jabatan Fungsional Pegawai Menggunakan Metode TOPSIS 2021-04-18T17:12:07SE Asia Daylight Time Z Zulvitri zulvitridavid@gmail.com Sarjon Defit zulvitridavid@gmail.com S Sumijan zulvitridavid@gmail.com <h1>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.</h1> 2021-09-30T00:00:00SE Asia Daylight Time ##submission.copyrightStatement## http://jsisfotek.upiyptk.ac.id/index.php/JSisfotek/article/view/144 Prediksi Pencapaian Target Peserta Keluarga Berencana Pasca Persalinan Menggunakan Algoritma Backpropagation 2021-07-14T18:20:15SE Asia Daylight Time Stefani Putri stefanihardiyanti06@gmail.com Y Yuhandri stefanihardiyanti19@gmail.com Gunadi Widi Nurcahyo stefanihardiyanti19@gmail.com <p><em>Population growth in Indonesia continues to increase, so the government makes a program to control the rate of growth of the population, namely the Family Planning Program (KB). The implementation of family planning also has another objective, namely to reduce the risk of maternal death after childbirth. To measure the level of increasing target achievement of postpartum family planning participants. So that it can be a reference for the DPPKBP3A in carrying out the postpartum family planning program. Data from the Population Control, Family Planning, Women Empowerment and Child Protection (DPPKBP3A) District </em><em>Lima Puluh Kota data processed in this study is data on the achievement of postpartum family planning participants from 2018 to 2020. Data processing uses the Backpropagation algorithm through several stages, namely the stage initialization, activation stage, weight training (weight change) and iteration stage. One of the results obtained from the calculation is the comparison of the target with the output gradient error in Suliki District in 2018, namely the target of 0.11311 and the result of the error gradient output is -0.1171. The prediction results obtained from this process become a reference for the Population Control, Family Planning and Women Empowerment and Child Protection Agency (DPPKBP3A) of District </em><em>Lima Puluh Kota to implement the implementation of postpartum family planning programs to the community the following year.</em></p> 2021-09-30T00:00:00SE Asia Daylight Time ##submission.copyrightStatement##