Articles
Analisis Sistem Antrian dalam Meningkatkan Efektivitas Pelayanan Menggunakan Metode Accidental Sampling
Rakhmad Pribowo Hariputra;
Sarjon Defit;
Sumijan
Jurnal Sistim Informasi dan Teknologi 2022, Vol. 4, No. 2
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang
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DOI: 10.37034/jsisfotek.v4i2.127
Queue is a process of waiting to be served if a service facility (server) is still busy. After getting service, the queue is left to get service facilities. One of the busy places of service and the existence of services is the Solok City Hospital. Services at the hospital always have a queuing process. This process starts from registration to completion, namely making payments at the cashier. Currently, mobile media has become one of the important aspects in supporting queue services. Technological advances that use mobile media have provided many advantages and conveniences in saving time and reducing the number of workers and costs in service. One method of improving services with mobile media is the Accidental Sampling method. This method is very effective in using queue time. So this research was carried out to improve hospital services so that visitors and the hospital could save time in getting services and serving. The data processed in this study was carried out in 30 days with measurements using the calculation of the probability of no visitors, the average number of visitors, the average number of visitors waiting in the queue, and the average time waiting in line. The result of this study is to add 1 waiter per counter, so the optimal time to overcome the queue at the hospital. So that this research can be used as a reference in improving services to overcome the problem of queuing visitors
EVALUATION OF THE QUALITY OF ONLINE LEARNING USING THE ROUGH SET METHOD IN THE COVID 19 ERA
Ramdani Bayu Putra;
Sarjon Defit;
Hasmaynelis Fitri
Jurnal Ipteks Terapan (Research Of Applied Science And Education ) Vol. 15 No. 2 (2021): Vol. 15 No. 2 (2021): Jurnal Ipteks Terapan ( Research of Applied Science and
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah X
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DOI: 10.22216/jit.v15i2.256
The occurrence of the Covid 19 pandemic around the world has changed all human physical activities in all lines of life, including activities in carrying out the teaching and learning process in educational institutions. This study seeks to analyze and evaluate the quality of online learning in the Covid 19 era. Measuring the quality of online learning is carried out using the rough set method, where the aspects or attributes used to consist of learning motivation, cognitive and self-efficacy. This research was conducted on students of the Putra Indonesia University YPTK Padang during the Covid 19 pandemic. By using the rough set algorithm technique, it is expected that the pattern or combination between attributes can produce knowledge or information in predicting the quality of online learning in the Covid 19 era. The results of testing with the Rosetta application found that The combination of cognitive and self-efficacy is an attribute that directly determines the quality of online learning in the Covid 19 era
Menentukan Pola Pembelian Produk Dengan Rule Mining Algoritma Apriori Pada Ud. Pelita Kita Padang
Susriyanti -;
Sarjon Defit;
Nanik Istianingsih
Jurnal Administrasi Sosial dan Humaniora Vol 5, No 2 (2021): Desember
Publisher : Institut Administrasi dan Kesehatan Setih Setio
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DOI: 10.56957/jsr.v4i3.185
Penelitian ini merupakan penelitian kuantitatif menggunakan data sekunder dari transaksi penjualan perusahaan menggunakan rule asosiasi Apriori. Tujuannya adalah untuk melihat pola perilaku pembelian pelanggana terhadap produk-produk UD. Pelita Kita Padang secara kombinasi. Dari hasil pengujian rule asosiasi Apriori, didapat 5 rule asosiasi yang terbentuk. Pola asosiasi yang terbentuk dalam hasil pengujian menggunakan nilai minimum support 30% dan nilai minimum confidence 70% menghasilkan 5 aturan rule asosiasi. Dan strong rules tertinggi didapatkan pada rule asosiasi J → P dengan nilai support 38% dan nilai confidence 86,4%. Artinya pelanggan yang membeli produk J (Jendela) dan P (Pintu) secara bersamaan sebanyak 38% dari semua transaksi yang ada, dengan tingkat kebenaran atau keyakinan mereka akan membeli keduanya secara bersamaan adalah 86,4%.
Sistem Pakar Metode Backward Chaining untuk Optimalisasi Pelayanan Pemberian Informasi Obat
Surya Dwi Putra;
Dhena Marichy Putri;
Sarjon Defit;
Sumijan Sumijan
JITCE (Journal of Information Technology and Computer Engineering) Vol 7 No 01 (2023): Journal of Information Technology and Computer Engineering
Publisher : Universitas Andalas
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DOI: 10.25077/jitce.7.01.1-7.2023
Drug information service is an assistance service to handle the needs of pharmacists related to medicines consumed by patients at the Lasi Health Center, Agam Regency. Nowadays, most of drug information services always require pharmacists to carry out their services, although there is limited number of pharmacists for providing drug information services at the Lasi Health Center, Agam Regency. This study aims to optimize drug information services so that the services can be carried out without the direct presence of a pharmacist. The data used in this study were drug prescription data available at the Pharmacy of Lasi Health Center Agam for the last 12 months and drug information services provided by pharmacists at the Lasi Health Center Agam Regency. This study used the backward chaining method to identify the drugs prescribed to the patients. The result achieved by this study were 356 Rules that could be applied directly to drug information services, with an accuracy rate of 100%. The rules generated using the backward chaining method can be used to optimize drug information services at the Lasi Health Center in Agam Regency without having to be served directly by pharmacists.
Metode k-means clustering untuk mengukur tingkat kedisiplinan pegawai (studi kasus di pemerintah kabupaten padang pariaman)
Rezki -;
Sarjon Defit;
Sumijan
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau
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DOI: 10.37859/coscitech.v4i1.4728
Knowledge Discovery In Database (KDD) is a process of converting raw data into useful data in the form of information. Data mining is a technique of digging up hidden or hidden valuable information in a very large data collection (database) so that an interesting pattern is found that was previously unknown. Clustering is a method in data mining in which data objects that have similarities or the same characteristics are grouped into one group and those that are different are grouped into another group. One aspect of discipline that can be used to evaluate employee performance is attendance. The k-means method is used to classify employee discipline levels and then describes the values that have been obtained to generate new knowledge regarding data patterns on employee discipline levels. The attendance data is clustered into 3, namely to measure low, medium, and high levels of discipline. After carrying out the calculation process, the 41 employee samples produced 3 iterations, and the final result was 3 clustering, namely cluster 1 of 10 employees with low discipline, cluster 2 of 7 employees with moderate discipline, and cluster 3 of 24 employees with high discipline. This is intended so that leaders can find out which employees have high, medium and low levels of discipline so that they can provide appreciation or rewards and sanctions in order to maintain and improve their discipline so that service to the community can be optimal and the vision and mission of the local government can be achieved. Keywords: KDD, Data Mining, K-Means Clustering Method, Discipline
Sistem Pendukung Keputusan Menggunakan Metode Multi Attribute Utility Theory Untuk Pemilihan Layanan Digital
Ira Nia Sanita;
Sarjon Defit;
Gunadi Widi Nurcahyo
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau
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DOI: 10.37859/coscitech.v4i1.4742
Dinas Komunikasi, Informatika dan Statistik (Kominfotik) Provinsi Sumatera Barat merupakan Dinas yang diberi kewenangan untuk membangun dan mengembangkan layanan digital untuk semua Perangkat Daerah di Pemerintah Provinsi Sumatera Barat. Seluruh Perangkat Daerah dapat mengajukan permintaan pembangunan layanan digital ke Dinas Kominfotik. Akan tetapi, tidak semua layanan digital yang diminta akan difasilitasi dan diakomodir oleh Dinas Kominfotik. Ada beberapa kriteria pemilihan dalam pembangunan Layanan Digital yaitu Layanan Digital yang sesuai dengan Arsitektur Sistem Pemerintahan Berbasis Elektronik (SPBE) Nasional, mendukung Program Unggulan Pemerintahan Provinsi Sumbar, Quick Win Layanan sesuai Peta Rencana SPBE, tujuan pembuatan layanan digital, serta Bahasa Pemograman yang digunakan dalam pembangunan Aplikasi. Penelitian ini menggunakan metoda Multi Attribute Utility Theory (MAUT). Metode MAUT digunakan untuk menentukan pemilihan layanan digital yang akan dibangun berdasarkan bobot dan kriteria yang sudah ditentukan. Kemudian dilakukan proses perankingan yang akan menentukan pilihan yang menjadi prioritas. Dan dari hasil pengujiannya didapatkan penerapan metode MAUT pada Sistem Pendukung Keputusan pemilihan layanan digital menghasilkan alternatif yang menjadi prioritas (rangking 1) adalah Layanan Penerimaan Peserta Didik Baru (PPDB) dengan nilai 0,933. Kata Kunci : Sistem Pendukung Keputusan, Layanan Digital, Multi Attribute Utility Theory (MAUT)
Sistem Pendukung Keputusan dengan Metode AHP dalam Penentuan Pemilihan Minat Siswa
Wenni Afrodita;
Sarjon Defit;
Yuhandri Yuhandri
JUKI : Jurnal Komputer dan Informatika Vol. 5 No. 1 (2023): JUKI : Jurnal Komputer dan Informatika, Edisi Mei 2023
Publisher : Yayasan Kita Menulis
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Senior High School is a level of formal education in selecting student interests selection of specialization is a grouping of learning interests that makes it easier for students to pursue knowledge in further education, especially in tertiary institutions. Specialization is designed to guide students so they can follow certain subjects at the next school level. Decision Support System has many methods that can be used. One of the methods used in this research is the Analytical Hierarchy Process (AHP) method. This decision support model will break down complex multi-factor or multi-criteria problems into a hierarchy, so that the decisions taken can be more objective. Because the concept of the AHP method is to change qualitative values into quantitative values. The Decision Support System uses the Analytical Hierarchy Process method to determine student interest choices in selecting interest in major subjects. This is a decision support system created to determine interest selection for class X students at SMAN 1 Kinali. The specialization that will be selected is taken from various criteria such as the average value of report cards, understanding of the material and students' interests. Test results on the AHP method obtained an accuracy of 90% from 10 test data. With this application, students are expected to get specialization according to their respective interests and abilities.)
Automated model for identification on mastoid of temporal bone image
Syafri Arlis;
Sarjon Defit;
Sumijan Sumijan
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v31.i1.pp570-581
Mastoiditis occurs due to inflammation that can affect the structure of the mastoid bone. The mastoid bone consists of the mastoid air cell system (MACS) which protects the ear structures and regulates air pressure in the ear and has different sizes and characteristics, making it very difficult to identify precisely. This study aims to identify and find the right MACS size by developing an automatic identification model and obtaining the optimal threshold value in the segmentation process using the extended adaptive threshold (eAT) method. The research dataset uses computed tomography (CT)-scan images of 308 slices of 12 patients indicated for mastoiditis. The results of this study provide identification that has the right MACS accuracy and size. Overall, the optimal segmentation process obtained the smallest threshold value of 57 and the largest threshold value of 63, the smallest MACS size is 4.025 cm2 and the largest is 8.816 cm2 with an accuracy rate of 93.4%. The smaller MACS size indicates inflammation in the mastoid area and these patients require more intensive treatment.
Development of natural language processing on morphologybased Minangkabau language stemming algorithm
Rini Sovia;
Sarjon Defit;
Yuhandri Yuhandri;
Sulastri Sulastri
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v31.i1.pp542-552
Minangkabau language (ML) is one of the daily communication tools used by the people of West Sumatra, Indonesia. ML is a challenge in communicating. The ML language translation process is necessary to facilitate communication. This study aims to build a translation system for ML into Indonesian by developing the concept of natural language processing (NLP). NLP development adopts the performance of morphology-based Minangkabau language stemming algorithm (MLSA) which can separate basic words with affixes and endings. The research dataset adopts 600 basic ML words sourced from the big Minangkabau dictionary. The results of this study provide analytic output that can translate ML into Indonesian well. These results are presented based on the testing process on basic word input with an accuracy rate of 97.16% and based on text documents of 91.65%. Thus, the MLSA performance process presents the accuracy of the translation process. Based on these results, this research contributes to developing a stemming algorithm model in carrying out the process of removing prefixes, inserts, and suffixes in the Minangkabau language. Overall, this research can be useful as a tool for translating the ML into Indonesian.
ALGORITMA C4.5 UNTUK PREDIKSI BIMBINGAN SISWA BERDASARKAN TIPOLOGI HIPPOCRATES-GALENUS
Boy Sandy Dwi Nugraha.H;
Sarjon Defit;
Gunadi Widi Nurcahyo
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 11 No 1 (2023): TEKNOIF APRIL 2023
Publisher : ITP Press
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DOI: 10.21063/jtif.2023.V11.1.1-8
The type of personality possessed by a student belived affect their behavior, whether positively or negatively, and if left unattended, it will harm the student. Student guidance is necessary to provide appropriate guidance for the student. This study aims to predict student guidance based on personality by using student data at SMP 1 Negeri Tembilahan. The data collection process was obtained from the BK teacher at SMPN 1 Tembilahan for grade 8 and grade 7. Grade 8 will be used as training data and grade 7 will be used as testing data. 5 parameters were selected for the prediction process and 1 label as the target class. The method used is the C4.5 algorithm to build a decision tree and obtain prediction rules. The results of the study were obtained using Confusion Matrix testing with a prediction accuracy rate of 70%. The ultimate goal of the student guidance prediction process is to have a higher percentage of "Yes" (need guidance) than "No" (don't need guidance) in the prediction results. Therefore, it can be stated that the prediction process model with the C4.5 algorithm is suitable for determining good decision-making results in terms of prediction, and the researcher hopes that after obtaining these results, the BK teacher at SMPN 1 Tembilahan can provide guidance as soon as possible and provide necessary guidance to students who need it.