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Sistem Pendukung Keputusan Dengan Simple Additive Weighting Dalam Pemilihan Calon Penerima Bantuan Rumah Tidak Layak Huni Sudin Saepudin; Dudih Gustian; Heri Firmansyah
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 10 No. 2 (2019): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (449.41 KB) | DOI: 10.31849/digitalzone.v10i2.2237

Abstract

Bantuan rumah tidak layak huni adalah salah satu program pemerintah untuk menekan angka kemiskinan di Indonesia, namun permasalahan yang ada bahwa proses yang selama ini dilakukan oleh pihak Kelurahan masih dilakukan secara subyektif dengan hanya mempertimbangkan hasil survey. Oleh karena itu, bagi pihak kelurahan diperlukan suatu sistem pendukung keputusan agar seleksi dapat dilakukan secara efisien secara sistemik. Adanya metode Multiple Attribute Decission Making, menjawab semua permasalahan tersebut. Dari beberapa metode Multiple Attribute Decission Making, Simple Addictive Weighting dipilih untuk diterapkan kedalam sistem pendukung keputusan. Sistem pendukung keputusan dibuat menggunakan metode air terjun. Tujuan penelitian ini agar pihak kelurahan dapat menyalurkan bantuannya kepada yang berhak menerimanya, sehingga dengan adanya sistem pendukung keputusan berbasis web untuk memilih penerima bantuan perumahan sesuai dan objektif. Penelitian ini memberikan hasil yang cukup akurat dimana proses penyaluran yang tepat sasaran dengan data yang diperoleh dari pihak kelurahan. Sistem yang dibuat cukup memnatu pihak kelurahan dengan nilai sekitar 73.6% yang diuji oleh 10 orang responden. Kata Kunci: Rumah Tidak Layak Huni, Multiple Attribute Decission Making, Simple Addictive Weighting, Sistem Pendukung Keputusan. Abstract The help of the home is not habitable is one of the government programs to suppress the poverty rate in Indonesia, but the problem exists that the process that was done by the village is still in subjectively Consider the survey results. Therefore, the town needs a decision support system so that the selection can be made by systemic efficiency. There is a method of Multiple Attribute Decision Making, answering all the problems. Of the multiple Attribute Decision-Making methods, Simple Addictive Weighting is chosen to be applied to the decision support system. The decision support system was made using a waterfall method. The purpose of this research is so that the village can distribute its help to the right to receive it, so it is expected by the Web-based decision support system to select the recipient of appropriate and objective housing assistance. This research provides entirely accurate results were the right distribution process targets with data obtained from the village. The system was made enough to inform the town with a value of about 73.6% tested by ten respondents. Keywords: Unqualified Houses, Multiple Attribute Decision Making, MADM, Simple Additive Weighting, Decision Support Systems.
A SENTIMENT ANALYSIS OF EMPLOYEE COMPETENCE IN BPR (PEOPLE'S ECONOMIC BANK) SUKABUMI Heri Firmansyah; Slamet Sutrisno; Dana Budiman
Multidiciplinary Output Research For Actual and International Issue (MORFAI) Vol. 5 No. 4 (2025): Multidiciplinary Output Research For Actual and International Issue
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/morfai.v5i4.4182

Abstract

This study aims to analyze sentiment towards employee competency at BPR Sukabumi using a text mining approach based on sentiment analysis. Employee competency is one of the key factors in determining the effectiveness and productivity of an organization, especially in the banking sector which is highly dependent on service quality and customer trust. The data used in this study were obtained from various sources, such as internal surveys, customer reviews, and comments on social media related to BPR Sukabumi employee service. The analysis method used is sentiment analysis based on text mining with Orange software on qualitative data in the form of open responses, comments, and testimonials collected through interviews to identify patterns of public perception towards aspects of employee competency, such as communication skills, technical expertise, responsibility, and service orientation. The results of customer research and interview results show a positive view towards employee competency, with 55% satisfied responses, 35% neutral, and 10% negative. The analysis focuses on speed of service, ease of access, improvement of technical competency, and transparency of information. These findings provide important input for BPR Sukabumi management in improving employee training and development programs to strengthen the competencies needed to meet customer expectations and the challenges of the banking industry. This study provides a methodological contribution in the use of sentiment analysis for human resource evaluation in the financial services sector.