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Angga Putra Juledi
Universitas Labuhanbatu
Computer Science & IT Economics, Econometrics & Finance Languange, Linguistic, Communication & Media

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Analysis of Simple Additive Weighting (SAW) Methods to Determine The Quality of Student Learning SMK Siti Banun Dhera; Deci Irmayani; Angga Putra Juledi
Jurnal Mantik Vol. 5 No. 1 (2021): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.Vol5.2021.1263.pp51-57

Abstract

It is a daunting challenge to assess the accuracy of student learning quality. Many considerations must be taken into consideration when determining the accuracy of the degree of student learning efficiency. These criteria use to assess students' ability to learn consistently. Since there are so many ways to satisfy this criteria, deciding on the consistency standard of learning scores is problematic. The SAW (Simple Additive Weighting) process solves different parameters of decision-making problems. The SAW method is a multi-criteria decision-making method founded on the idea that the chosen solution must satisfy all criteria. The SAW technique is a multi-criteria decision-making approach based on the optimal option, which would be the nearest to the ideal solution while being the furthest from the negative ideal solution. Calculating the normalization matrix, weighted normalization matrix, comparing the positive and negative ideal solutions, calculating the separation distance for each alternative ideal solution, and calculating the value of each alternative's preference are all steps in the SAW method. The following table displays the results of the SAW process calculation protocol. The information comes from a decision-making framework that distinguishes students who excel in their studies. Bunga Adelia Azahara received a 0.908, while Fadila Dwi Ranti received a 0.932.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN PRODUKTIVITAS TANAMAN TERBAIK DENGAN MENGGUNAKAN METODE TOPSIS Nina Sari Rizki; Angga Putra Juledi; Deci Irmayani
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.1058

Abstract

This research aims to solve the problem of selecting plants that have the best agricultural productivity, especially in the Bagan Sinembah area. The selection of these plants is based on plants that are quick to harvest and easy to cultivate, which is done to support food security and the local economy. To overcome the complexity in decision making related to plant selection, this research designed a Decision Support System (DSS) using the TOPSIS Method. This method was chosen because it can provide plant recommendations that are effective, efficient, and in accordance with the specified criteria. The research method involves preliminary studies, determining relevant criteria, and collecting data through field surveys. The criteria used in this research consist of Growth Time, Ease of Cultivation, High Production Yield, Production Cost, and Adaptation to the Environment. Criteria weights are determined based on preference and relative importance. The data is then processed using the TOPSIS method to rank alternative plant choices. The analysis results show the ranking of plants based on their relative proximity scores to positive and negative ideal solutions. The results of this research showed that the recommendation for the plant with the best productivity was Alternative A5 with a preference value of 0.74732. The existence of this decision support system can make a positive contribution to the development of the agricultural sector, especially in increasing the productivity of crops that are quick to harvest and easy to cultivate in the Bagan Sinembah area.
SISTEM PENDUKUNG KEPUTUSAN PENENTUAN PRIORITAS PELATIHAN PENGGUNAAN ALAT PERTANIAN BERBASIS IOT DENGAN METODE ARAS Adam Wirayuda; Angga Putra Juledi; Ibnu Rasyid Munthe
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.1017

Abstract

The potential benefits of using IoT technology-based tools in agriculture are large, but implementation is still hampered by farmers' lack of understanding. Therefore, training was carried out taking into account the different conditions and needs of farmers in the Bagan Sinembah area. This research aims to build a Decision Support System (DSS) using the ARAS method in determining training priorities for using Internet of Things (IoT)-based agricultural equipment for farmers in the Bagan Sinembah area. Criteria for determining training priorities involve factors such as infrastructure availability, level of technological understanding, local topographic conditions, scale of agricultural business, and availability of funds and resources. The research results obtained consist of 3 groups of farmers who will receive the highest training priority, namely: alternative KTA8 in the first position with a result of 0.85821, alternative KTA4 in the second position with a result of 0.83197, and alternative KTA7 in the third position with a result 0.82643. The highest priority is given to farmer groups with the highest yields. The research results show that the system built can help make it easier for the Faculty of Science and Technology, Labuhanbatu University, to make decisions regarding training priorities for farmers. The results of this research can contribute to the development of a decision support system to increase the efficiency and effectiveness of farmer training in using IoT technology in agriculture in the Bagan Sinembah area.
SISTEM PENDUKUKUNG KEPUTUSAN PEMILIHAN SALON MOBIL TERBAIK DENGAN MENGGUNAKAN METODE WASPAS Afrian Alfariz; Ibnu Rasyid Munthe; Angga Putra Juledi
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.697

Abstract

This research aims to build a Decision Support System (SPK) to choose the best car salon in the Rokan Hilir area. With increasing car ownership, the need for efficient maintenance has become crucial. The Weighted Aggregated Sum Product Assessment (WASPAS) method is used in this SPK. The research stages involve determining criteria, data collection, normalization, determining criteria weights, ranking alternatives, and evaluation. The criteria used in this research consist of price, quality, performance, technology and comfort. Of the nine alternatives, the ranking results show that SM04 is the best salon in the area. The final results of data processing using the WASPAS method in this study obtained 3 alternatives with the largest value, namely rank 1 alternative SM04 with a final result of 0.92715, rank 2 alternative SM02 with a value of 0.92448 and rank 3 alternative SM06 with a value of 0.92101. Through a decision support system for selecting the best car salon using the WASPAS method in the Rokan Hilir area, this design can make a positive contribution in helping vehicle owners make the best decisions, increase decision-making efficiency, and have a positive impact on the car salon industry in the Rokan Hilir area.
Co-Authors Adam Wirayuda Afrian Alfariz Deci Irmayani Dhera Ibnu Rasyid Munthe Nina Sari Rizki