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Yeni Kustiyahningsih
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ykustiyahningsih@trunojoyo.ac.id
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kursor@trunojoyo.ac.id
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Informatics Department, Engineering Faculty University of Trunojoyo Madura Jl. Raya Telang - Kamal, Bangkalan 69162, Indonesia Tel: 031-3012391, Fax: 031-3012391
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INDONESIA
Jurnal Ilmiah Kursor
Published by Universitas Trunojoyo Madura
ISSN : 02160544     EISSN : 23016914     DOI : https://doi.org/10.21107/kursor
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Jurnal Ilmiah Kursor is published in January 2005 and has been accreditated by the Directorate General of Higher Education in 2010, 2014, 2019, and until now. Jurnal Ilmiah Kursor seeks to publish original scholarly articles related (but are not limited) to: Computer Science. Computational Intelligence. Information Science. Knowledge Management. Software Engineering. Publisher: Informatics Department, Engineering Faculty, University of Trunojoyo Madura
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol 10 No 1 (2019)" : 5 Documents clear
ALGORITHM A* FOR THE NEAREST ROUTE TRACKING SYSTEM IN THE MODE OF TRASNPORTATION Febri Ramanda; Eko Sediyono; Catur Edi Widodo
Jurnal Ilmiah Kursor Vol 10 No 1 (2019)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v10i1.212

Abstract

Transport as a basic services industry as the basis of national economic development, it is the foundation of a nation's progress. With increasing in the standard life society, transportation needs for the whole society have also increased. Online transportation service needs are influenced by various factors such as cost, quality of service, income and ownership that modes of transport used. The purpose of this study is to apply the A* algorithm to find paths or routes, because it is quite flexible and works better than the algorithm dijakstra in all cases (barriers and without obstacles). The results showed that the A* algorithm is able to provide the information than other algorithms that are best finding the shortest path.
THE IMPLEMENTATION OF SYSTEM DYNAMICS IN HOSPITAL SERVICES FOR IMPROVING THE INPATIENT ROOMS UTILIZATION Heri Supriyanto; Erma Suryani
Jurnal Ilmiah Kursor Vol 10 No 1 (2019)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v10i1.206

Abstract

Hospitals are an important part of the health system. This agency consists of several main services, namely Outpatient, Emergency, and Inpatient services. One type of main service that is quite complex and needs to be considered is service at inpatient installations. Regarding this inpatient service, hospitals must make a structural and functional utilization effort to be further improved by increasing the utilization of service space regarding the number of available beds. To measure the level of utilization of hospital facilities at inpatient services, hospital service indicators are needed to measure it. These indicators include BOR (Bed Ocupanccy Rate), which is the percentage of beds filled, LOS (Length of Stay), namely the average length of stay, TOI (Turn Over Interval), which is the average free time of bed, BTO (Bed Turn Over), namely the productivity of the bed. These indicators will be presented in graphical form, namely Barber Johnson Graph. From the values ​​produced by the hospital management, later it can be used as material for planning and decision-making in determining service facility policies in the future. The purpose of this study is to make modeling with a system dynamics so that the value of the indicator can have ideal parameter values. The result of this study is that a scenario is needed to increase the number of patient visits, because patient visits are too low. This is evidenced by the value of the BOR which is less than the ideal value. In addition, the duration of patient care, day of care was influenced by the variable number of patient visits. The results of the scenario show that in 2019 to 2030 the values ​​of BOR, LOS, TOI, and BTO were produced according to the ideal indicator value. Keywords: Inpatients, Room Utilization, Service Indicators, System Dynamics.
THE IMPLEMENTATION OF HEART RATE SENSOR AND MOTION SENSORS BASED ON INTERNET OF THINGS FOR ATLETE PERFORMANCE MONITORING Sritrusta Sukaridhoto; Muhammad Aksa Hidayat; Achmad Basuki; Riyadh Arridha; Andi Roy; Titing Magfirah; Agus Prasetyo; Udin Harun Al Rasyid
Jurnal Ilmiah Kursor Vol 10 No 1 (2019)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v10i1.208

Abstract

Indonesian achievements in the ASEAN Games continued to decline in achievement starting in 1962 with the acquisition of 51 medals and up to 2014 with the acquisition of 20 medals. The decline in achievement was due to the lack of athletic resources due to the absence of media that could record athletes' abilities in the field. Can record the athlete's performance before running, running and after running using the Heart Rate sensor and Motion Capture sensor. The results of the sensor recording will be stored in the database. This system applies the Internet of Things (IoT) concept, using raspberry pi, Arduino microcontroller, T34 polar heart rate sensor to capture and send heartbeat to receivers, gyro-based motion-capture sensors that named wear notch where this sensor serves to capture the movement of athletes, sensors communicate with the system using 4G connectivity, use MQTT as edge computing which acts as a communication medium from sensors to databases, Maria DB and influx DB as accumulation which plays a role in storing heart rate and athlete's movements that have been recorded by sensors, athlete performance monitoring platform with a heart rate sensor and athlete's motion capture is a web-based application that collaborates all processes from the sensor to the system. Sensor heart rate recording results are categorized good because the error margin is only 0.4%. Wearnotch sensor data can be stored in the database, and athletic data can be recorded before sports, while sports, and after sports in real-time
INTELLIGENT SYSTEM FOR AUTOMATIC CLASSIFICATION OF FRUIT DEFECT USING FASTER REGION-BASED CONVOLUTIONAL NEURAL NETWORK (FASTER R-CNN) Hasan Basri; Iwan Syarif; Sritrusta Sukaridhoto; Muhammad Fajrul Falah
Jurnal Ilmiah Kursor Vol 10 No 1 (2019)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v10i1.187

Abstract

In 2018, the Indonesian fruit exports increased by 24% from the previous year. The surge in demand for tropical fruits from non-tropical countries is one of the contributing factors for this trend. Some of these countries have strict quality requirements – the poor level quality control of fruit is an obstacle in achieving greater export yield. This is because some exporters still use manual sorting processes performed by workers, hence the quality standard varies depending on the individual perception of the workers. Therefore, we need an intelligent system that is capable of automatic sorting according to the standard set. In this research, we propose a system that can classify fruit defects automatically. Faster R-CNN (FRCNN) architecture proposed as a solution to detect the level of defect on the surface of the fruit. There are three types of fruit that we research, its mangoes (sweet fragrant), lime, and pitaya fruit. Each fruit divided into three categories (i) Super, (ii) middle, (iii) and fruit defects. We exploit join detection and video tracking to calculate and determine the quality fruit in real-time. The datasets are taken in the field, then trained using the FRCNN Framework using the Tensorflow platform. We demonstrated that this system can classify fruit with an accuracy level of 88% (mango), 83% (lime), and 99% (pitaya), with an average computation cost of 0.0131 m/s. We can track and calculate fruit sequentially without using additional sensors and check the defect rate on fruit using the video streaming camera more accurately and with greater ease.
IMPACT OF IMPUTATION ON CLUSTER-BASED COLLABORATIVE FILTERING APPROACH FOR RECOMMENDATION SYSTEM Noor Ifada; Susi Susanti; Mulaab
Jurnal Ilmiah Kursor Vol 10 No 1 (2019)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v10i1.201

Abstract

The Collaborative Filtering (CF) widely used in Recommendation System commonly suffers the sparsity issue since the unobserved rating entries usually over dominance the observed ones. A clustering technique is an alternative solution that can solve the problem. However, no in-depth work has investigated how the missing entries should be mitigated and how the cluster-based approach can be implemented. In this study, we show how the imputed cluster-based approach deals with the missing entries, improving the recommendation quality. The framework of our method consists of four main stages: rating imputation to replace the missing entries, K-means clustering to group users or items based on the imputed rating data, CF-based prediction model, and generating the list of top-N recommendation. This paper uses three variations of imputation techniques, i.e., null, mean, and mode. The cluster-based approach is employedby using the K-Means as the clustering technique, and either the user-based or the items-based model as the CF approach. Experiment results show that the null imputation technique gives the best results when dealing with the missing entries. This finding indicates that the implementation of the clustering techniqueis sufficient for solving the sparsity issue such that imputing the missing entries is not necessary. We also show that our imputed cluster-based CF methods always outperform the traditional CF methods in terms of the F1-Score metric.

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