cover
Contact Name
Mesran
Contact Email
jurnal.josh@gmail.com
Phone
+6282161108110
Journal Mail Official
jurnal.josh@gmail.com
Editorial Address
Sekretariat Forum Kerjasama Pendidikan Tinggi (FKPT) Jalan Sisingamangaraja No. 338, Medan, Sumatera Utara
Location
Kota medan,
Sumatera utara
INDONESIA
JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
ISSN : -     EISSN : 2686228X     DOI : -
Core Subject : Science,
Artikel yang dimuat melalui proses Blind Review oleh Jurnal JOSH, dengan mempertimbangkan antara lain: terpenuhinya persyaratan baku publikasi jurnal, metodologi riset yang digunakan, dan signifikansi kontribusi hasil riset terhadap pengembangan keilmuan bidang teknologi dan informasi. Fokus Journal of Information System Research (JOSH)
Articles 737 Documents
Peramalan Persediaan Barang Menggunakan Metode Weighted Moving Average dan Metode Double Exponential Smoothing Muh Latif; Rengga Herdiansyah
Journal of Information System Research (JOSH) Vol 3 No 2 (2022): Januari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (453.675 KB) | DOI: 10.47065/josh.v3i2.1232

Abstract

The management of goods inventory at PT EDS Manufacturing Indonesia (PEMI) is still manual, on the other hand there is no policy that regulates what methods can be used to forecast the inventory of goods and also the absence of an estimate of the number of goods that will be purchased by customers so that the number of goods, inventory is often mistaken and causes a buildup of goods in the warehouse. For that, a method is needed that can be systemized according to sales data in the forecasting of goods inventory. There are several methods that can be implemented including Weight Moving Average and Double Exponential Smoothing. The Weight Moving Average method is a method that gives different weights to each historical while the Double Exponential Smoothing method is a method that has a smoothing value twice at the time before the actual data. The data used in this study is quarterly before the forecasting. This thesis aims to design and build a web-based application using the Weight Moving Average and Double Exponential Smoothing methods, the results of the two methods compared to find out which forecasting results have the smallest error value, where the smallest error value can be referenced for the upcoming inventory of goods
Design of Cloud Computer to Support Independent Information System Servers Universitas Islam Kuantan Singingi Muhammad Hasyim Siregar; Nofri Wandi Al-Hafiz
Journal of Information System Research (JOSH) Vol 3 No 2 (2022): Januari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1002.429 KB) | DOI: 10.47065/josh.v3i2.1234

Abstract

In today's all-digital era, easy access to information systems is needed. Moreover, with the new regulation from the Minister of Education that LKD/BKD must be filled in using the SISTER application from the Ministry of Education and Culture. Previously, sister was used for lecturers who wanted to certify lecturers, so to use the server at the Kuantan Singingi Islamic University, it was enough to use a laptop with all the shortcomings. With a wider demand it is necessary to make independent cloud computing-based servers, to rent cloud computing services according to standards from sisters is very unaffordable for the UNIKS campus so that this solution will make one server machine, several Virtual Machines (VM) will be created in the CPU Server.
Data Mining Menggunakan Metode Asosiasi Apriori untuk Merekomendasi Pola Obat Pada Puskesmas Dewinta Marthadinata Sinaga; Agus Perdana Windarto; Heru Satria Tambunan; Irfan Sudahri Damanik
Journal of Information System Research (JOSH) Vol 3 No 2 (2022): Januari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (540.994 KB) | DOI: 10.47065/josh.v3i2.1237

Abstract

Drugs are one of the most important components in terms of health, both to cure and reduce pain due to illness suffered by everyone, besides that the use of drugs also gives us information about what diseases everyone suffers so that the information is very helpful for health workers. For this reason, drugs need to be managed properly, effectively and efficiently. This study aims to analyze the a priori algorithm on drug output data at the Parsoburan Health Center Pematangsiantar to find out what types of drugs are most needed by patients at the same time. The data used is in the form of drug output data in April 2021. Based on the a priori algorithm calculations, 70 association rules were formed with a number minimum of support 90% and a minimum confidence of 90%. It is hoped that the results of the research can help the Parsoburan Health Center Pematangsiantar optimize quality health services for planning future drug needs and produce useful information for decision making.
Implementasi Market Basket Analysis Menggunakan Assocation Rule Menerapkan Algoritma FP-Growth Desi Asima Silitonga; Agus Perdana Windarto
Journal of Information System Research (JOSH) Vol 3 No 2 (2022): Januari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (566.29 KB) | DOI: 10.47065/josh.v3i2.1239

Abstract

Pharmacy is a medium for selling various kinds of drugs by class and other products related to health. Pharmacies serve transactions in the form of doctor's prescriptions and over-the-counter drugs every day. Drug sales per day can reach dozens of transactions. Sales transaction data in the form of doctor's prescriptions are increasing every day and are stored as archives for bookkeeping without thinking about other benefits. However, this data can produce important information in determining the pattern of goods layout in accordance with consumer buying patterns using the fp-growth algorithm. The data used in this study is based on doctor's prescription transaction data. The results of the association rule can be used as input for the pharmacy in determining the pattern of the location of the goods at the pharmacy
Rancangan E-Commerce Mochpoint Menerapkan User Centered Design Berbasis Web Farid Mukti; Orita Dwi Purbiyanti; Sepitri Daruyani
Journal of Information System Research (JOSH) Vol 3 No 2 (2022): Januari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1060.563 KB) | DOI: 10.47065/josh.v3i2.1242

Abstract

E-commerce is one of the strategies of a trading company to increase sales in the current digital era. Online marketing and transactions have become commonplace in the world of buying and selling. Mochpoint is a store that sells clothing that prioritizes the needs of teenagers to adults. Several obstacles were experienced by Mochpoint when they were still using the old or manual system, namely the promotion of goods still using Instagram, transactions that were not automatic resulted in frequent recording errors and on the customer side it was difficult to find out the stock of goods and the absence of long distance sales which made it easier for the company to expand its marketing area. Mochpoint is a store that implements a B2C (Business to customer) business model, but has not yet used a web-based sales system or e-commerce. Through the use of this website's information system, it is hoped that it will be able to increase the need for data and information to potential customers of ochpoint, where potential customers can exchange data and information to transactions about all products available on mochpoint. . The mochpoint store website was created using the PHP programming language and database processing using MySQL with the website address Http://mochpointweb.epizy.com/. The website design process uses a navigation structure and UML design. The results of the implementation and testing of this website can run well according to the design based on the test results, namely by testing the website on the browser and testing using the black box method
Prototype Sensor Parking Otomatis Pada Area Blind-Spot Kendaraan Menggunakan Mikrokontroler Rafika Sari; Herlawati Herlawati; Fata Nidaul Khasanah; Prima Dina Atika
Journal of Information System Research (JOSH) Vol 3 No 2 (2022): Januari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (677.59 KB) | DOI: 10.47065/josh.v3i2.1245

Abstract

The growth of four-wheeled private vehicle users in Indonesia is quite rapid in the last few years. The problem that then arises from this situation is that not a few vehicle users park their vehicles randomly or not at the right location in the parking area. This is because the driver is a novice driver or an elderly driver so that he is not optimal in predicting the blind-spot area when parking the vehicle. In this study, a prototype of an automatic parking sensor system will be made where the vehicle will receive information on the distance of the vehicle to the surrounding object. The microcontroller in this system uses Arduino UNO R3 and HCR-04 sensor. The software used in this system is designed using the Arduino Uno IDE programming. The system is made with the provisions of placing sensors on the left side of the minibus car (blind-spot area) and a parking system for parallel parking locations (left-right). The system is designed to warn the driver about the distance between the car and surrounding objects by utilizing ultrasonic waves. The distance reading by the sensor is accurate at a distance of 2 – 40 cm. The effective sensor measurement distance is 2-3 cm. With this automatic parking sensor system, it is easier for novice or elderly drivers, as well as other drivers, to park their cars automatically, so that the vehicle parking process becomes faster and more accurate
Optimalisasi dalam Penentuan Keputusan Level Pemberlakuan Pembatasan Kegiatan Masyarakat (PPKM) Menerapkan Metode Preference Selection Index Rohan Kristini Purba; Dendy Frans Gunawan Hutagalung; Ebenezer Maston Sinaga; Agustina Sidabutar; Mesran Mesran
Journal of Information System Research (JOSH) Vol 3 No 2 (2022): Januari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (450.679 KB) | DOI: 10.47065/josh.v3i2.1247

Abstract

The Covid-19 pandemic is a disaster for the entire world, even affecting all aspects of human life, both in terms of economy, social and culture. Therefore, the government enacted a regulation called Large-Scale Social Restrictions (PSBB) to stop the spread of COVID-19. In this case, the government makes a policy to change the Large-Scale Social Restrictions (PSBB) into the Enforcement of Community Activity Restrictions (PPKM) where the PSBB Restrictions are stricter than the Enforcement of Community Activity Restrictions (PPKM). Because the absence of a system makes it difficult for the government and requires a long time in determining the level of implementation of restrictions on community activities (PPKM). In order to assist in determining the level of PPKM, a decision support system is needed. The Preference Selection Index (PSI) method is a method used in a decision support system using simple steps in problem solving. The results of the research obtained that the highest rank is A7 with a value of 0.767 as level 1. By using the range on the PPKM level so that level 1 is Sibolga. Level 2 does not exist in the above alternative. Level 3 is terrain, Binjai, Pematang Siantar, Tebing Tinggi, Gunung Sitoli, Padang Sidimpuan, Tanjung Balai, Samosir and Kisaran and level 4 is not in the alternatives.
Sistem Pakar Kombinasi Metode Certainty Factor dan Dempster Shafer Nelly Astuti Hasibuan; Alwin Fau
Journal of Information System Research (JOSH) Vol 3 No 2 (2022): Januari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (275.821 KB) | DOI: 10.47065/josh.v3i2.1252

Abstract

An expert system is a technique of artificial intelligence that uses certainty techniques to solve problems. There are several techniques that can be used to solve the problem of uncertainty, including the certainty factor method and the mathematical theory of Dempster Shafer. Both methods and techniques can be applied to solve expert system problems. However, each method has advantages and disadvantages in determining the diagnosis. In the expert system, there are 2 values ​​used for the diagnosis process, including the expert value taken from the expert hypothesis and the user value or evidence which is the value obtained based on the facts of an event. Dempster Shafer theory can only use the evidence value in determining the density value, while the certainty factor method can use evidence and hypothesis values. Thus, the combination made to overcome the weakness of one method by using the advantages of the other method is expected to produce a better certainty value.
Analisa Distance Metric Algoritma K-Nearest Neighbor Pada Klasifikasi Kredit Macet Khairul Fadhli Margolang; Muhammad Mizan Siregar; Sugeng Riyadi; Zakarias Situmorang
Journal of Information System Research (JOSH) Vol 3 No 2 (2022): Januari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (468.088 KB) | DOI: 10.47065/josh.v3i2.1262

Abstract

Data mining is a method that can classify data into different classes based on the features in the data. With data mining, non-performance loan categories can be classified based on data on lending from cooperatives to their members. This study uses K-Nearest Neighbor to classify non-performance loan categories with various distance metric variations such as Chebyshev, Euclidean, Mahalanobis, and Manhattan. The evaluation results using 10-fold cross-validation show that the Euclidean distance has the highest accuracy, precision, F1, and sensitivity values ​​compared to other distance metrics. Chebyshev distance has the lowest accuracy, precision, sensitivity, while Mahalanobis distance has the lowest F1 value. Euclidean and Manhattan distances have the highest reliability values ​​for true-positive and true-negative class classifications. Mahalanobis distance has the lowest reliability value for false-positive class classification, while Chebyshev distance has the lowest value for false-negative class classification
Prediksi Pemberian Rekomendasi Kenaikan Pangkat PNS Menggunakan Metode Naïve Bayes Desi Irfan; Irwan Daniel; Adam Sagara; Zakarias Situmorang
Journal of Information System Research (JOSH) Vol 3 No 2 (2022): Januari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (481.889 KB) | DOI: 10.47065/josh.v3i2.1263

Abstract

A civil servant or civil servant (English: civil servant, Dutch: ambtenaar) is a person employed by a government agency to provide public services. As a profession, civil servants are positions that are pursued through career paths and not based on general elections involving the people's vote. Quoted from the Regulation of the Head of BKN No. 35 of 2011 concerning Guidelines for the Preparation of PNS Careers, the career pattern of civil servants is arranged based on the principles of certainty, professionalism, and transparency. One of the requirements to achieve the desired career is through the promotion process. The promotion or class of a civil servant cannot be separated from the recommendation of the leadership. A leader in providing recommendations must look at several important points that must be possessed by employees who will be given recommendations such as Attendance, Integrity, Cooperation and Insight or Knowledge. In the process, there are still problems in terms of technical and effectiveness because manual assessments sometimes still assess subjectively. Therefore, a study was carried out for the classification of the determination of the status of giving recommendations using the Naïve Bayes method. Naive Bayes is one method of probabilistic reasoning. The Naive Bayes algorithm aims to classify data in certain classes, then the pattern can be used to estimate the employee who will be given a recommendation, so that the leader can make a decision to give recommendation or not to the employee

Page 10 of 74 | Total Record : 737