scholarly journals Penentuan sistem antrean dengan pertimbangan biaya dan kontrol kedatangan pasien: Studi kasus di Puskesmas Ungaran Semarang

2021 ◽  
Vol 15 (2) ◽  
pp. 165-177
Author(s):  
Albert Hosea Santoso ◽  
Hanifa Reygina Fajrin ◽  
Akhmad Sultoni ◽  
Dwi Ertiningsih
Keyword(s):  
Steady State ◽  
System Analysis ◽  
Queuing System ◽  
Queue System ◽  
Number Of Patients ◽  
Patient Arrival ◽  
Doctor's Office ◽  
Patient Service ◽  
And Control

Penelitian ini bertujuan untuk menentukan sistem antrean yang efektif dengan mempertimbangkan biaya dan kontrol kedatangan pasien pada fasilitas kesehatan: Puskesmas Ungaran, Semarang. Penelitian ini menggunakan data kuantitatif berupa waktu kedatangan pasien, waktu pelayanan pasien, jumlah pasien, dan jumlah pelayan. Tahapan-tahapan yang dilakukan dalam penelitian ini adalah menganalisis steady state dari sistem antrean, ukuran kinerja pada sistem antrean, keefektifan sistem antrean dengan pertimbangan biaya (cost), dan keefektifan sistem antrean dengan pertimbangan kontrol pada kedatangan pasien. Hasil analisis sistem antrean pada kedatangan pasien di loket pendaftaran, ruang dokter, dan loket apotek merupakan proses Poisson, sedangkan pelayanan pasien berdistribusi eksponensial. Jumlah pelayan dan biaya yang efektif pada masing-masing sistem antrean adalah dua pelayan dengan biaya Rp59.513 pada loket pendaftaran; empat pelayan dengan biaya Rp141.864 pada ruang dokter; dan satu pelayan dengan biaya Rp23.885 pada loket apotek. Rerata jumlah pasien dalam antrean dan sistem antrean masing-masing adalah dua pasien dan lima pasien. Rerata waktu pasien menunggu di dalam antrean maupun sistem antrean adalah 1,937 menit dan 8,883 menit. Lebih lanjut, ketika dilakukan kontrol pada kedatangan pasien, maka jumlah pasien yang diterima akan meningkat ketika biaya yang dibutuhkan puskesmas dalam menerima pasien diperbesar. Determination of the queuing system by considering costs and patient arrival control: A case study at Puskesmas Ungaran SemarangAbstractThe study aimed to determine an effective queuing system by considering costs and control of patient arrival at a health facility: Puskesmas Ungaran, Semarang, Indonesia. The study used quantitative data in patient arrival time, patient service time, number of patients, and number of servants. The stages carried out were analyzing the steady-state of the queuing system, performance measures of the queuing system, the effectiveness of the queuing system by considering costs, and the effectiveness of the queuing system by considering control of patient arrival. The result of the queuing system analysis at the arrival of the patient at the registration counter, doctor’s office, and pharmacy counter was a Poisson process, while patient service has an exponential distribution. The number of servants and costs in each of the effective queuing systems was two servants with costs 59,513 IDR at the registration counter; four servants with costs 141,864 IDR at the doctor’s office; and one servant with costs 23,885 IDR at the pharmacy counter. The average number of patients in the queue and queue system was two patients and five patients, respectively. The average time for patients to wait in the queue and queue system was 1.937 minutes and 8.883 minutes. Furthermore, when the patient arrival was controlled, the number of patients accepted will increase when the health center's costs to receive patients were increased. 

scholarly journals OPTIMASI SISTEM ANTRIAN PADA LAYANAN KESEHATAN MASYARAKAT MENGGUNAKAN PENDEKATAN SIMULASI

2019 ◽  
Vol 3 (1) ◽  
pp. 14-22
Author(s):  
Widya Setia Findari ◽  
Yohanes Anton Nugroho
Keyword(s):  
Waiting Time ◽  
Six Sigma ◽  
Waiting Times ◽  
Community Health Center ◽  
Observation Data ◽  
Simulation Approach ◽  
Simulation Test ◽  
Queue System ◽  
Number Of Patients ◽  
Patient Service

Abstract : The purpose of this study is to optimize service time in a community health center. The average number of patients visiting is 100 to 300 per day. In certain units there is a heavy queue of patients which increases service waiting times, including registration units, inspection units, and pharmaceutical units. The initial observation data on the existing system shows the waiting time for patient services is 2,7 hours. This fact shows that the time of patient service on the existing system needs to be optimized so that the waiting time can be accelerated. This study offers a solution to optimize the service queue system using a simulation approach. The DMAIC (Define, Measure, Analyze, Improve, Control) Six Sigma method is used as a basis for analyzing the waiting time for services from an existing system. The results of the analysis are used in the simulation test to obtain improvement factors using several scenarios. The best simulation results are obtained with the scenario of adding operators in all units. Optimizing the waiting time of patient services using the best scenario simulation approach is shown by the decrease in waiting time of the queue system by 1,05 hours or 38,9% faster than the existing system.Keywords: System Optimizing; Public Health; Queue; Simulation; DMAIC Six SigmaAbstrak : Tujuan penelitian ini adalah untuk mengoptimalkan waktu tunggu pelayanan di sebuah pusat kesehatan masyarakat (Puskesmas). Rata-rata jumlah pasien yang berkunjung adalah 100 hingga 300 per hari. Pada beberapa unit tertentu terjadi antrian pasien yang padat sehingga meningkatkan waktu tunggu pelayanan, antara lain unit pendaftaran, unit pemeriksaan, dan unit farmasi. Data pengamatan awal pada sistem yang ada menunjukkan waktu tunggu pelayanan pasien adalah 2,7 jam. Fakta ini menunjukkan bahwa waktu pelayanan pasien pada sistem yang ada perlu dioptimalkan agar waktu tunggu dapat dipercepat. Penelitian ini menawarkan solusi optimalisasi sistem antrian pelayanan dengan menggunakan pendekatan simulasi. Metode DMAIC (Define, Measure, Analyze, Improve, Control) Six Sigma digunakan sebagai dasar analisis waktu tunggu pelayanan dari sistem yang sudah ada. Hasil analisis digunakan pada uji simulasi untuk mendapatkan faktor perbaikan dengan menggunakan beberapa skenario. Hasil simulasi terbaik diperoleh dengan skenario penambahan operator di semua unit. Optimasi waktu tunggu pelayanan pasien dengan menggunakan pendekatan simulasi skenario terbaik ditunjukkan oleh penurunan waktu tunggu sistem antrian sebesar 1,05 jam atau 38,9% lebih cepat dari sistem yang sudah ada.Kata kunci: Optimasi Sistem, Layanan Kesehatan, Antrian, Simulasi, DMAIC Six Sigma

scholarly journals Analisis Sistem Antrian Pada Pelayanan Poli Jantung RSUD Kota Langsa

2021 ◽  
Vol 3 (2) ◽  
pp. 297-308
Author(s):  
Fazrina Saumi ◽  
◽  
Rizki Amalia ◽  
Amelia Amelia ◽  
Nurviana Nurviana
Keyword(s):  
Waiting Time ◽  
System Analysis ◽  
Single Channel ◽  
Time Of Arrival ◽  
City Hospital ◽  
Length Of Service ◽  
Queue System ◽  
Hospital Design ◽  
Number Of Patients ◽  
First In First Out

Queuing is an activity where parties are waiting to get service. A queuing process starts from the time of arrival to the time of service. Queuing problems are often encountered in everyday life, including in Langsa City Hospital, especially in the cardiac clinic, which has the most patients. The majority of patients in the queue system are elderly (elderly), so good service is needed considering the physical condition of patients who have entered a vulnerable age. The queuing system analysis aims to determine the average number of patients waiting in the system and the length of service at the heart clinic of Langsa City Hospital. In addition, the queue system analysis can help the Langsa City Hospital design an operational service system so that the service process can run optimally. The queue structure model used is a single channel-single phase with the discipline type First In First Out (FIFO). From the queue model analysis results obtained, the cardiac poly care system has an average number of patients waiting at most occurs in the period 08.00-10.00, namely 14 people with a waiting time of about 56.28 minutes. This time is the busy working hour at cardiac poly with a busyness rate of 93%. From the simulation results with two servers using the same model, a busy rate of 50% was obtained with a reduction in the number of people waiting by 12.8 people with a waiting time of about 1.2 minutes.

scholarly journals On Steady-State Voltage Stability Analysis Performance in MATLAB Environment

2021 ◽  
Vol 15 ◽  
pp. 73-79
Author(s):  
Jan Veleba ◽  
Tomáš Nestorovič
Keyword(s):  
Steady State ◽  
Power Systems ◽  
Electric Power ◽  
Voltage Stability ◽  
System Analysis ◽  
Power Sources ◽  
Renewable Power ◽  
Network Operation ◽  
Solution Accuracy ◽  
And Control

Nowadays, electric power systems have been often operated close to their limits due to increased electric power consumptions, vast installments of renewable power sources and deliberated power market policies. This poses a serious threat to stable network operation and control. Therefore, voltage stability is currently one of key topics worldwide for preventing related black-out and islanding scenarios. In this paper, modelling and simulations of steady-state voltage stability problems in MATLAB environment are performed using author-developed computational tool implementing both conventional and more advanced numerical approaches. Their performance is compared with Simulink-based library Power System Analysis Toolbox (PSAT) in terms of solution accuracy, CPU time, and possible limitations. Their use for both real-time and off-line monitoring and assessment of system's voltage stability are also discussed.

scholarly journals ANALISIS SISTEM ANTREAN PADA LOKET PENDAFTARAN POLIKLINIK SPESIALIS DI RS BALIMED

2021 ◽  
Vol 10 (2) ◽  
pp. 70
Author(s):  
KADEK DITA SUGIARI ◽  
I WAYAN SUMARJAYA ◽  
KETUT JAYANEGARA
Keyword(s):  
Steady State ◽  
Waiting Time ◽  
Queuing Theory ◽  
Queuing System ◽  
State Condition ◽  
Steady State Condition ◽  
Average Waiting Time ◽  
Number Of Patients ◽  
Measures Of Performance

Hospital is one of the service facilities that is not free from queue problem. One example of this hospital is Balimed Hospital. At certain times, especially in the morning, there is a lineup of patients at the Balimed Hospital’s Specialist Polyclinic. In order to maximize service, it is necessary to analyze the queuing system by applying the queuing theory. This study focuses on queues at the Balimed Hospital’s Specialist Polyclinic in Internal Disease. After conducting the research, it was found that the model used at the Specialist Polyclinic in Internal Disease is . With this model, the queuing system at Balimed Hospital's Specialist Polyclinic in Internal Disease is in steady state condition because ???? < 1. The measures of performance for queuing system at Balimed Hospital’s Specialist Polyclinic in Internal Disease is the average number of patients in queue  is 0,1 patient or it can be said that there is almost no patient in queue because the value of  is close to 0, the average number of patients in system  is 1 patient, the average waiting time for patients in queue  is 1 minute, and the average time spent by patients start from queuing until being served  is 2,5 minutes. The queuing system has been effective, it can be seen from the short waiting time for patients.

Ultrastructural changes in sciatic nerve tissue: Effects of passive maternal smoking

1983 ◽  
Vol 41 ◽  
pp. 650-651
Author(s):  
Amankwah K.S. ◽  
A.D. Weberg ◽  
R.C. Kaufmann
Keyword(s):  
Sciatic Nerve ◽  
Maternal Smoking ◽  
Ultrastructural Level ◽  
Uranyl Acetate ◽  
Nerve Tissue ◽  
Ultrastructural Changes ◽  
Cacodylate Buffer ◽  
And Control ◽  
Spontaneous Delivery

Previous research has revealed that passive (involuntary inhalation) tobacco smoking during gestation can have adverse effects upon the developing fetus. These prior investigations did not concentrate on changes in fetal morphology. This study was undertaken to delineate fetal neural abnormalities at the ultrastructural level in mice pups exposed in utero to passive maternal smoking.Pregnant study animals, housed in a special chamber, were subjected to cigarette smoke daily from conception until delivery. Blood tests for determination of carbon monoxide levels were run at 15-18 days gestation. Sciatic nerve tissue from experimental and control animals were obtained following spontaneous delivery and fixed in 2.5% gluteraldehyde in 0.1M cacodylate buffer pH 7.3. The samples were post-fixed in osmium ferrocyanide (1:1 mixture of 1.5% aqueous OSO4 and 2.5% K4 Fe(CN)6). Following dehydration, the tissues were infiltrated with and embedded in Spurr. Sections were stained with uranyl acetate and lead citrate.

Rancang Bangun Sistem Penerimaan Dan Mutasi Barang Pada PDAM Tirta Kerta Raharja

Sensi Journal ◽  
2020 ◽  
Vol 6 (2) ◽  
pp. 236-246
Author(s):  
Ilamsyah Ilamsyah ◽  
Yulianto Yulianto ◽  
Tri Vita Febriani
Keyword(s):  
System Analysis ◽  
Object Oriented ◽  
Analysis Method ◽  
Web Based ◽  
Visual Modeling ◽  
Long Time ◽  
The Right ◽  
And Control ◽  
Web Based System ◽  
The Web

The right and appropriate system of receiving and transferring goods is needed by the company. In the process of receiving and transferring goods from the central warehouse to the branch warehouse at PDAM Tirta Kerta Raharja, Tangerang Regency, which is currently done manually is still ineffective and inaccurate because the Head of Subdivision uses receipt documents, namely PPBP and mutation of goods, namely MPPW in the form of paper as a submission media. The Head of Subdivision enters the data of receipt and mutation of goods manually and requires a relatively long time because at the time of demand for the transfer of goods the Head of Subdivision must check the inventory of goods in the central warehouse first. Therefore, it is necessary to hold a design of information systems for the receipt and transfer of goods from the central warehouse to a web-based branch warehouse that is already database so that it is more effective, efficient and accurate. With the web-based system of receiving and transferring goods that are already datatabed, it can facilitate the Head of Subdivision in inputing data on the receipt and transfer of goods and control of stock inventory so that the Sub Head of Subdivision can do it periodically to make it more effective, efficient and accurate. The method of data collection is done by observing, interviewing and studying literature from various previous studies, while the system analysis method uses the Waterfall method which aims to solve a problem and uses design methods with visual modeling that is object oriented with UML while programming using PHP and MySQL as a database.

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