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Jufriadif Na`am
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jufriadifnaam@upiyptk.ac.id
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jsisfotek@upiyptk.ac.id
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INDONESIA
Jurnal Sistim Informasi dan Teknologi
Published by Universitas Putra Indonesia YPTK Padang
ISSN : 26863154     EISSN : -     DOI : https://doi.org/10.35134/jsisfotek
Core Subject : Science,
Computer Science & IT
Jurnal JSisfotek (Jurnal Sistem Informasi dan Teknologi) dimaksudkan sebagai media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian Rekayasa Sistem, Teknik Informatika/Teknologi Informasi, Manajemen Informatika dan Sistem Informasi. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada Masyarakat luas dan sebagai sumber referensi akademisi di bidang Teknologi dan Informasi.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 6 Documents
 1 
Search results for , issue "2019, Vol. 1, No. 3" : 6 Documents clear
Sistim Pakar Konseling Mata Pelajaran Pilihan UNBK Menggunakan Metode Forward Chaining Laidawati, Desi; Yunus, Yuhandri
Jurnal Sistim Informasi dan Teknologi 2019, Vol. 1, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1217.3 KB) | DOI: 10.35134/jsisfotek.v1i3.2

Abstract

The choice of computer-based national exams is a choice of a student that must be adjusted to his interests and talents, so in this case the selection of majors is very important for the future of a student who will continue his studies to college. But in reality the decisions taken in choosing majors often cause problems, because the Majors taken only follow the choice of friends or on the basis of coercion from parents. Causing the large number of students who feel out of line with expectations or abilities and want to change majors. For this reason, an expert system has been made that can make it easy for students to consult early to determine elective subjects for computer-based national examinations. The method used in making this expert system is the Forward Chaining method to determine conclusions. The process of this application is to receive input in the form of types of problems experienced by students. The result of the application is that it can provide early instructions for subjects that match the talents and interests of students. With the application of the forward chaining method that is applied to the system that is governed by the rule type problem. From the accuracy of 89.29%, the system can be said to be good enough to be implemented
Simulasi Pengadaan Barang Menggunakan Metode Monte Carlo Manurung, Kiki Hariani; Santony, Julius
Jurnal Sistim Informasi dan Teknologi 2019, Vol. 1, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (431.087 KB) | DOI: 10.35134/jsisfotek.v1i3.3

Abstract

Inventory is a very important aspect for the development of a company. Inventory management is needed to determine the inventory of goods needed within a certain period so that market demand can be fulfilled. The data used in this study are inventory data 2016. Data processing in this study uses the Monte Carlo algorithm to predict procurement data. In accelerating data processing, this research applies a Web-based program with the PHP (Hypertext Processor) programming language. The results of testing this method are to obtain predictions of the supply of goods in a certain period of time with the right level of accuracy. From the test results obtained the level of accuracy in predicting inventory stock by 93% so that it can help companies in making decisions in the future.
Diagnosa Penyakit Rubella Menggunakan Metode Fuzzy Tsukamoto Febriani, Widya; Nurcahyo, Gunadi Widi; Sumijan, Sumijan
Jurnal Sistim Informasi dan Teknologi 2019, Vol. 1, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (588.723 KB) | DOI: 10.35134/jsisfotek.v1i3.4

Abstract

Rubella or better known as German measles is a viral infection characterized by a red rash on the skin. Lack of general public understanding of this disease makes the number of patients with Rubella increasing. So Fuzzy Tsukamoto's method is used to detect Rubella disease. The purpose of this study is to facilitate the public in understanding about Rubella disease so as to reduce the number of sufferers of this disease. The first step to detecting Rubella disease is to determine the fuzzy set and domain that includes 3 variables: red rash, swollen lymph nodes, and fever. The output of fuzzy calculations is someone experiencing Rubella or normal symptoms. The value obtained from the calculation process using the Tsukamoto method is 6.00. If the value is smaller than 6.00 then Rubella has no potential, if the value is greater than 6.00 then Rubella will be potential.
Analisis Perkiraan Jumlah Produksi Tahu Menggunakan Metode Fuzzy Sugeno Nurdini, Siti; Nurcahyo, Gunadi Widi; Santony, Julius
Jurnal Sistim Informasi dan Teknologi 2019, Vol. 1, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (805.833 KB) | DOI: 10.35134/jsisfotek.v1i3.5

Abstract

Tofu industry XYZ is a small industry that is managed in the form of a home industry, where the process of estimating the amount to be produced is still manual. For that, a calculation process is needed that can be used to save or buy. Of the existing problems used in the Sugeno Fueno Method. In this method uses three variables, namely, demand variables, purchase variables and production variables. Each variable has three sets of Fuzzy, the demand variable consists of down, medium and up. Variables consist of few, medium and many. And the production variable consists of reduction, tolerable and increasing. From the results of the test data conducted by the Sugeno Method there is a difference of error of 2.148% means that the truth level is 97,852%. Determining this method can be applied to the tofu industry XYZ in estimating the amount of tofu production for the next period.
Algoritma K-Means untuk Klasterisasi Tugas Akhir Mahasiswa Berdasarkan Keahlian Sirait, Weri; Defit, Sarjon; Nurcahyo, Gunadi Widi
Jurnal Sistim Informasi dan Teknologi 2019, Vol. 1, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (516.307 KB) | DOI: 10.35134/jsisfotek.v1i3.6

Abstract

School of Information and Computer Management (STMIK) Indonesia Padang is a private university under the auspices of the Higher Education Service Institution (LLDIKTI) Region X, producing graduates who are competent in the field of system analysts and database administrators. Requirements to meet undergraduate graduates (S1) final year students need to complete a final project or thesis.Final year students at STMIK Indonesia Padang often experience confusion in taking the final assignment topic. This is due to the fact that the final year students have not been able to direct their potential in determining the final assignment topic. In this case, researchers conducted the process of grouping final level students using the Data Mining K-means Clustering technique. The process of grouping final-level students is done by utilizing the data of course values from the field mapping system analysts and database administrators. In this grouping two clusters will be produced, namely students taking the final assignment of system analysts and database administrator. So by using this K-means Clustering method, students have direction in taking the final assignment topic. The results obtained from 40 data samples used were students who took the topic of the final project system analysts as many as 20 students and students who took the final assignment of database administrators were 20 students
Implementasi Algoritma K-Means untuk Klasterisasi Peserta Olimpiade Sains Nasional Tingkat SMA Hasanah, Miftahul; Defit, Sarjon; Nurcahyo, Gunadi Widi
Jurnal Sistim Informasi dan Teknologi 2019, Vol. 1, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1934.43 KB) | DOI: 10.35134/jsisfotek.v1i3.7

Abstract

The abundance of students causes student data in the system to also be abundant. Schools often find it difficult to manage large amounts of data manually, especially in selecting National Science Olympiad participants and decisions made are less effective. So this research was conducted with the aim of helping the school in selecting OSN participants appropriately and effectively. The method used is Clustering with K-Means algorithm on the report card grades of students majoring in Natural Sciences at SMA Negeri 5 Sijunjung. The results in this study get 3 clusters of students on the selection of OSN participants, namely students who are Very Competent, Competent and Less Competent. This research can be used as a benchmark used by schools in making decisions on the selection of OSN participants.

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