scholarly journals KLASIFIKASI SENTRA INDUSTRI PERIKANAN BERBASIS PELABUHAN PERIKANAN: KASUS DI KABUPATEN BELITUNG

2017 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Marwan Syaukani ◽  
Muhammad Fedi Alfiadi Sondita ◽  
Daniel Monintja ◽  
Akhmad Fauzi ◽  
Victor Petrus Hiliary Nikijuluw
Keyword(s):  
Service Provider ◽  
The Other ◽  
Ideal Solution ◽  
New Classification ◽  
Alternative Formula ◽  
Fishing Capacity ◽  
Order Preference ◽  
Effectiveness And Efficiency ◽  
Multi Criteria Analysis ◽  
Solution Parameter

Klasifikasi pelabuhan perikanan Indonesia yang terdiri atas PelabuhanPerikanan Samudera, Pelabuhan Perikanan Nusantara, Pelabuhan PerikananPantai, dan Pusat Pendaratan Ikan. Klasifikasi tersebut di atas didasari hubungan inti plasma di mana pelabuhan perikanan yang besar ditunjang beberapa pelabuhan perikanan yang lebih kecil (Direktorat Jenderal Perikanan Tangkap, 2008). Hubungan inti plasma tersebut tidak berjalan karena tidak mempunyai pola hubungan yang jelas. Oleh sebab itu diperlukan alternatif klasifikasi pelabuhan perikanan dengan memasukan unsur jaringan industri seperti yang diusulkan oleh Israel & Rouqe (2000) yang mengklasifikasikan pelabuhan perikanan menjadi tiga yaitu penyedia jasa utama, penyedia jasa antara (server), dan client. Penelitian ini bertujuan menentukan klasifikasi sentra industri perikanan berbasis pelabuhan perikanan dalam jaringan industri yang efektifdan efisien dilakukan di Kabupaten Belitung selama 11 bulan sejak Oktober 2007 sampai Agustus 2008. Metode yang dipergunakan adalah multi criteria analysis yang dilanjutkan dengan analisis technique for order preference by similarity to ideal solution. Parameter yang diukur meliputi infrastruktur pelabuhan perikanan, kapasitas kapal perikanan, kemandirian faktor input, dan produksi. Hasil penelitian menunjukan bahwa Pulau Belitung berperan sebagai penyedia jasa utama, Pulau Mendanau, dan Pulau Seliu berperan sebagai penyedia jasa antara (server), dan Pulau Gersik dan Pulau Sumedang berperan sebagai client.Klasifikasi pelabuhan perikanan dalam suatu jaringan industri berimplikasi pada peningkatan efektivitas dan efisiensi pembangunan pelabuhan perikanan tangkap sebagai sentra industri perikanan tangkap.Indonesian government classify fishing port into 4 categories namely Ocean Fishing Port, National Fishing Port, Sea Shore Fishing Port, and Fish Landing Fishing Port. The above classification based on partnership or lingkage industry among fishing ports. However, the lingkage industry do not run effectively due to unappropriate pattern. Improving the condition, Israel & Roque (2000) suggested to classify fishing port into 3 categories namely main service provider, intermediate service provider or server, and client. This paper describes an alternative formula that considers industrial linkage among fishing ports as fishing industrial centers. The research was held on Belitung Regency as long as 11 months from October 2007 to August 2008. There are several factors should be considered in building fishing port namely fishing facilities, fishing capacity, input dependency and fish landing capacity. The 4 factors are analyzed by multi criteria analysis then continued by technique for order preference by similarity to ideal solution analysis. The research concludes that the Belitung is as the main service provider, the Mendanau Island and Seliu Islands are as the intermediate service provider or server, the other 2 islands are as the client. The new classification will increase effectiveness and efficiency of fishing port developments.

Comparison of railway lines in Poland concerning use in freight transport

2021 ◽  
Author(s):  
Wojciech Kamiński
Keyword(s):  
Solution Method ◽  
Freight Transport ◽  
Ideal Solution ◽  
Transit Traffic ◽  
Analysis Methods ◽  
Order Preference ◽  
Multi Criteria Analysis

AbstractThis article considers factors of number of sidings and the occurrences of transit traffic and presents a comparison of selected railway lines in Poland. Multi-criteria analysis methods were used, like the zero unitarization method and the technique for order preference by similarity to ideal solution method. The comparison made it possible to arrange the selected railway lines in the order from the most to the least useful. The obtained results showed also that zero unitarization method is limited only to the analysis of all lines on which transit traffic occurs or all lines without transit traffic. The comparison of all lines is possible using the technique for order preference by similarity to ideal solution method.

scholarly journals The Challenges Faced in Technology-Driven Classes During COVID-19

2021 ◽  
Vol 19 (1) ◽  
pp. 17-39
Author(s):  
Sangeeta Sharma ◽  
Arpan Bumb
Keyword(s):  
Structural Model ◽  
Traditional Classroom ◽  
The Other ◽  
Primary Data ◽  
Ideal Solution ◽  
Computer Based Learning ◽  
Online Lectures ◽  
Order Preference ◽  
Computer Based ◽  
Interpretive Structural Model

In the wake of coronavirus pandemic, social distancing became a mandate that led to the transition from traditional classroom-based lectures to computer-based learning. This paper extensively deals with the ranking of the challenges faced by instructors and students. Primary data from 624 participants (399 students and 225 instructors) is collected through a questionnaire. To assign the ranking to the challenges, Technique of Order Preference Similarity to Ideal Solution (TOPSIS) is deployed. A contextual model is developed by using Interpretive Structural Model (ISM) technique that further provides recommendations for prioritizing the challenges that need to be addressed to mitigate the problems faced in online lectures in coronavirus situation. The number of variables is reduced to simplify the interpretation by exploratory factor analysis. The study also provides the basis to formulate the strategies for policymakers and administration after identifying which challenges need to be addressed first for mitigating all the other challenges.

scholarly journals Sistem Pendukung Keputusan Kenaikan Jabatan Menggunakan Metode Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)

2019 ◽  
Vol 1 ◽  
pp. 69
Author(s):  
Rahmat Doni ◽  
Faisal Amir ◽  
Dicky Juliawan
Keyword(s):  
Decision Making ◽  
Career Path ◽  
The Other ◽  
Ideal Solution ◽  
Topsis Method ◽  
Accuracy Rate ◽  
Learning Evaluation ◽  
Order Preference ◽  
Leadership Decisions ◽  
And Training

Promotion is one way to Rumah Bermain Bilal to improve the performance of tutors in educating their students. The problem of leadership in decision-making still uses the choice of methods and assessment processes subjectively so that the process is not in accordance with the goals of the career path. Therefore, it is necessary to make a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Method to help make decisions. In this study, using the criteria set by the company, namely planning, learning, evaluation, and training. The ranking results obtained from testing the calculations that the alternative Tutor F is the best tutor with the results of the calculation of 0.804 when compared to the other twelve alternatives. The TOPSIS method has a data accuracy rate of 85% from thirteen alternatives and can be used as a support for leadership decisions to make recommendations for increasing the career path of tutors.

scholarly journals Adding value to satisficing decisions using TOPSIS in service provider selection problems

2016 ◽  
Vol 7 (1) ◽  
pp. 34-39
Author(s):  
Solly Matshonisa Seeletse
Keyword(s):  
Service Provider ◽  
Selection Process ◽  
Decision Makers ◽  
Added Value ◽  
Ideal Solution ◽  
Scientific Methods ◽  
Selection Problems ◽  
Selection Processes ◽  
Order Preference ◽  
Reduced Costs

Selection processes of credible candidates in competitions are often flawed. The flaws may be deliberate when there is corruption. In other cases the flaws occur because of the decision makers’ inadequacies. Many competitors do their best in developing exceptional proposals, but unfairness of the decision makers undermines these efforts. Ideally, undeserving candidates should be disqualified, and deserving ones be allowed to contest. Systematic methods should be used in the proposal evaluation, and the process should be verifiable. This paper discusses scientific methods proposed for use to select a criterion-based worthy competitor in service provider selection problems. The method is a technique for order preference by similarity to ideal solution (TOPSIS). TOPSIS is a mathematically-derived statistical method useful to offset the biases in the selection process. Features that address both added value and reduced costs are incorporated in the TOPSIS selection process. A numerical example is included to demonstrate TOPSIS fortes

scholarly journals Multi-Criteria Analysis of Pollution Caused by Auto Traffic in a Geographical Area Limited to Applicability for an Eco-Economy Environment

2018 ◽  
Vol 10 (11) ◽  
pp. 4240 ◽  
Author(s):  
Sorin Borza ◽  
Marinela Inta ◽  
Razvan Serbu ◽  
Bogdan Marza
Keyword(s):  
Analytical Hierarchy Process ◽  
Air Pollutants ◽  
Road Traffic ◽  
Geographical Area ◽  
Ideal Solution ◽  
Order Preference ◽  
Multi Criteria Analysis ◽  
Hierarchy Process ◽  
The City

The pollution caused by road traffic is a significant problem for society in the 21st century. Climate change and mortality among the population, are increasingly influenced by increasing traffic in urban agglomerations. The present study aims at the multi-criteria analysis of the pollution caused by traffic at several busy intersections in the city of Sibiu, Romania. Classification of intersections was done using the Synchro Studio with Warrants software. Air pollutants, noise, and the number of vehicles in the traffic were taken into account. To analyze these criteria as a whole, the analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) methods were used. A comparative study has been undertaken on the results obtained by applying the two multicriteria methods. The paper aims to provide solutions for the eco-economy of the future.

TERAPAN KOMBINASI METODE TOPSIS DAN ANALYTICAL HIERARCHY PROCESS PADA PEREKOMENDASIAN PENERIMA BEASISWA PENINGKATAN PRESTASI AKADEMIK (Studi Kasus pada STMIK PPKIA Tarakanita Rahmawati)

2017 ◽  
Vol 8 (2) ◽  
pp. 663 ◽  
Author(s):  
Muhammad Fadlan ◽  
Muhammad Muhammad ◽  
Hadriansa
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Analytical Hierarchy Process ◽  
Ideal Solution ◽  
Microsoft Excel ◽  
Order Preference ◽  
Hierarchy Process

Beasiswa Peningkatan Prestasi Akademik (PPA) sebagai salah satu bentuk dukungan pemerintah Republik Indonesia terhadap dunia pendidikan. Beasiswa yang disalurkan oleh pemerintah melalui Perguruan Tinggi yang ada di Indonesia ini, penyeleksian dan penetapan penerimanya sepenuhnya diserahkan kepada pihak Perguruan Tinggi yang bersangkutan. Tahap inilah yang sangat rentan terjadinya kecurangan. Pada objek penelitian  yang diteliti hingga saat ini proses penyeleksian masih dilakukan dengan menggunakan Microsoft Excel, hal ini tentu saja kurang efektif dan efisien, serta rentan akan terjadinya kesalahan bahkan kecurangan. Untuk itu, diperlukan suatu metodologi dan aplikasi yang tepat dalam melakukan penyeleksian penerima beasiswa tersebut. Decision Support System digunakan sebagai solusi untuk melakukan perekomendasian penerima beasiswa, khususnya dengan menggunakan Metode Technique  for  Order  Preference  by  Similarity  to  Ideal  Solution  (TOPSIS)  dan  Analytical  Hierarcy Process (AHP). Penggunaan kombinasi dua metode tersebut dilakukan agar memiliki tingkat akurasi yang baik jika dibandingkan  dengan menggunakan satu metode. Hasilnya,  aplikasi  decision support system dengan penerapan kombinasi metode Topsis dan AHP berhasil di rancang dan di ujicoba, serta sukses dalam perekomendasian penerima beasiswa PPA dengan menghasilkan data alternatif mahasiswa yang terurut mulai dari nilai preferensi yang paling tinggi 0.764 hingga terendah 0.189. Hasil ini dapat menjadi rekomendasi bagi pengambil keputusan dalam mengambil keputusan yang efektik, efisien dan dapat dipertanggung jawabkan.

An Intuitionistic Fuzzy Based Novel Approach to CPU Scheduler

2020 ◽  
Vol 16 (4) ◽  
pp. 316-328
Author(s):  
Supriya Raheja
Keyword(s):  
Fuzzy Inference ◽  
The Other ◽  
Simulation Environment ◽  
Inference System ◽  
Intuitionistic Fuzzy ◽  
Novel Approach ◽  
Continuous Feedback ◽  
Simulation Results ◽  
Effectiveness And Efficiency ◽  
Unique Capability

Background: The extension of CPU schedulers with fuzzy has been ascertained better because of its unique capability of handling imprecise information. Though, other generalized forms of fuzzy can be used which can further extend the performance of the scheduler. Objectives: This paper introduces a novel approach to design an intuitionistic fuzzy inference system for CPU scheduler. Methods: The proposed inference system is implemented with a priority scheduler. The proposed scheduler has the ability to dynamically handle the impreciseness of both priority and estimated execution time. It also makes the system adaptive based on the continuous feedback. The proposed scheduler is also capable enough to schedule the tasks according to dynamically generated priority. To demonstrate the performance of proposed scheduler, a simulation environment has been implemented and the performance of proposed scheduler is compared with the other three baseline schedulers (conventional priority scheduler, fuzzy based priority scheduler and vague based priority scheduler). Results: Proposed scheduler is also compared with the shortest job first CPU scheduler as it is known to be an optimized solution for the schedulers. Conclusion: Simulation results prove the effectiveness and efficiency of intuitionistic fuzzy based priority scheduler. Moreover, it provides optimised results as its results are comparable to the results of shortest job first.

Exploration of Product Centric Factors in Telecom Industry

2015 ◽  
Vol 8 (1) ◽  
Author(s):  
Swati Ganeti ◽  
Rajat Agarwal ◽  
Murali Krishna Medudula ◽  
Mahim Sagar
Keyword(s):  
Service Quality ◽  
Service Provider ◽  
Service Providers ◽  
Network Connectivity ◽  
Factor Loading ◽  
The Other ◽  
Relative Importance ◽  
Network Connection ◽  
Telecom Service ◽  
Telecom Industry

Telecom industry is one of those industries which has changed dramatically during the past decade. With more and more players entering in this industry, competition is ever increasing. The war between these players is slowly shifting from the price to the augmentation. This paper aims at exploring such factors which influence a customers preference of one telecom service provider (TSP) over the other. It is a descriptive research where study has been conducted among the consumers of different telecom service providers (TSPs). By reviewing the existing literature in this domain, we explored different factors which affect the consumers decision to prefer one telecom service provider over the other. A consumer targeted questionnaire was designed where consumers were asked about the factors they consider (with their relative importance quantified using Likert scale), before buying a new network connection to know the relative importance of the various factors. Factor Analysis was performed to club various variables into distinct factors. Statistical techniques then helped in identifying the relative importance. From the Factor Loading matrix the following five factors were generated:- Overall service quality, Point of Purchase Differentiator, Promotion Measures, Tariff Plans and Size of the Network. Further study in the behavioural perceptions of consumer shows that the most important factor in influencing the customer buying behavior is Service Quality. The second most important factor is cost and various plans offered by the telecom service provider. Network connectivity was considered by almost all the respondents and consumers prefer the largest network player. The study also found that promotional measures dont influence the customers as expected.

Radiator threat evaluation with missing data based on improved technique for order preference by similarity to ideal solution

2021 ◽  
pp. 1-10
Author(s):  
Yu-Heng Xu ◽  
Si-Yi Cheng ◽  
Hu-Biao Zhang
Keyword(s):  
Missing Data ◽  
Prior Knowledge ◽  
Attribute Reduction ◽  
Estimation Algorithm ◽  
Weighted Averaging ◽  
Ideal Solution ◽  
Attribute Weights ◽  
Order Preference ◽  
Improved Technique ◽  
Threat Evaluation

To solve the problem of the missing data of radiator during the aerial war, and to address the problem that traditional algorithms rely on prior knowledge and specialized systems too much, an algorithm for radiator threat evaluation with missing data based on improved Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) has been proposed. The null estimation algorithm based on Induced Ordered Weighted Averaging (IOWA) is adopted to calculate the aggregate value for predicting missing data. The attribute reduction is realized by using the Rough Sets (RS) theory, and the attribute weights are reasonably allocated with the theory of Shapley. Threat degrees can be achieved through quantization and ranking of radiators by constructing a TOPSIS decision space. Experiment results show that this algorithm can solve the incompleteness of radiator threat evaluation, and the ranking result is in line with the actual situation. Moreover, the proposed algorithm is highly automated and does not rely on prior knowledge and expert systems.

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