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Journal : Journal of Information Systems Engineering and Business Intelligence

Sistem Pendukung Keputusan Pemilihan Siswa Berprestasi di Sekolah Menengah Pertama dengan Metode VIKOR dan TOPSIS Rivanda Putra; Indah Werdiningsih; Ira Puspitasari
Journal of Information Systems Engineering and Business Intelligence Vol. 3 No. 2 (2017): October
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (302.173 KB) | DOI: 10.20473/jisebi.3.2.113-121

Abstract

Abstrak— Penelitian ini bertujuan merancang dan membangun sistem pendukung keputusan untuk pemilihan siswa berprestasi di SMP Taruna Jaya I Surabaya dengan metode VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) dan Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS). Sistem pendukung keputusan ini dibangun melalui 6 tahap. Tahap pertama adalah pengumpulan data dan informasi melalui wawancara dan analisis dokumen. Tahap kedua adalah pengolahan data dan informasi untuk mendapatkan rancangan sistem yang akan dibangun. Tahap ketiga adalah analisis sistem yang meliputi input data siswa, pembobotan kriteria dengan metode AHP, serta perankingan alternatif dengan metode VIKOR dan TOPSIS. Tahap keempat adalah perancangan sistem menggunakan konsep Object Oriented Design. Tahap kelima adalah implementasi sistem berbasis web. Tahap terakhir adalah evaluasi sistem dengan membandingkan tingkat akurasi antara metode VIKOR dan TOPSIS. Berdasarkan hasil uji konsistensi, terdapat 7 percobaan yang tidak konsisten dan 13 percobaan yang konsisten. Hasil yang diperoleh adalah tingkat akurasi yang tertinggi sebesar 80% dengan menggunakan TOPSIS. Berdasarkan hasil tersebut maka metode TOPSIS dapat digunakan pada kasus pemilihan siswa berprestasi di SMP Taruna Jaya I Surabaya dengan derajat kepentingan antar kriteria adalah nilai aktivitas sedikit lebih penting dari nilai rapot, nilai aktivitas lebih penting dari nilai prestasi, nilai aktivitas sangat kuat penting dari nilai sikap, nilai rapot sedikit lebih penting dari nilai prestasi, nilai rapot lebih penting dari nilai sikap, dan nilai prestasi sedikit lebih penting dari nilai sikap.Kata Kunci— AHP, Pemilihan Siswa Berprestasi, Sistem Pendukung Keputusan, TOPSIS, VIKORAbstract— This research proposes a solution to create a decision support system of student achievement selection using VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS) method. The decision support system would resolve the problem of big data processing which needs more effort and more time. The development of decision support system of student achievement selection consisted of 6 phases. The first phase was collecting the data and information via interviews and document analysis. The second phase was data processing to create system design. The third phase was analyzing the system that includes the input of student data, weighing the criteria using AHP method, and rank the alternatives using VIKOR and TOPSIS method. The fourth phase was designing the system using Object Oriented Design. The fifth phase was implementing the system using a web-based. The sixth phase was the evaluation of system by comparing the level of accuracy between VIKOR and TOPSIS methods. Based on the result of consistency test, there were 7 inconsistent experiments and 13 consistent experiments. The result obtained is the highest accuracy rate of 80% by using TOPSIS. Based on these results, TOPSIS method can be used in case of selection of outstanding students in SMP Taruna Jaya I Surabaya with degree of importance among the criteria is activity value was slightly more important than report value, activity value was more important than achievement value, activity value was very important from attitude value, report value was slightly more important than achievement value, report value was more important than attitude value, and achievement value was slightly more important than attitude value.Keywords— AHP, Decision Support System, Student Achievement Selection , TOPSIS, VIKOR
The Continuance Intention of User’s Engagement in Multiplayer Video Games based on Uses and Gratifications Theory Ira Puspitasari; Elzha Odie Syahputra; Indra Kharisma Raharjana; Ferry Jie
Journal of Information Systems Engineering and Business Intelligence Vol. 4 No. 2 (2018): October
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (575.69 KB) | DOI: 10.20473/jisebi.4.2.131-138

Abstract

One of the key success factors in video game industry, including multiplayer video game (MVG), is the user’s continuance intention. The MVG industry runs in a highly competitive market. Users can shift to another game as soon as they discover a slightly inconvenient issue. Thus, maintaining the user’s enthusiasm in playing MVG for a long time is challenging for most games. The solution to prolong the users’ engagement can be initiated by identifying all factors that facilitate the continuance use of playing MVG. This study applied uses and gratifications theory to examine seven variables (enjoyment, fantasy, escapism, social interaction, social presence, achievement, and self-presentation) and the moderating effects of age and gender on the MVG continuance intention. The data analysis and the model development were tested based on Partial Least Square method using the responses of 453 MVG users. The results revealed that enjoyment, fantasy, social interaction, achievement, and self-presentation significantly affected the continuance intention of playing MVG, with enjoyment being the strongest variable. The result also demonstrated the moderating effect of age and gender on the relation between independent variables and continuance intention. The results and findings offered additional insights into the system development to enhance the information system application.
Clustering of Drug Sampling Data to Determine Drug Distribution Patterns with K-Means Method : Study on Central Kalimantan Province, Indonesia Wahyuri Wahyuri; Umi Athiyah; Ira Puspitasari; Yunita Nita
Journal of Information Systems Engineering and Business Intelligence Vol. 5 No. 2 (2019): October
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1970.953 KB) | DOI: 10.20473/jisebi.5.2.208-218

Abstract

Background: Drug sampling and testing in the context of post-marketing control is an important component to ensure drug safety in the supply chains. The results are used by the Indonesian National Agency for Drug and Food Control (NA-FDC) for conducting public warnings, evaluating the Good Manufacturing Practice (GMP) and Good Distribution Practice (GDP) implementation, and enforcing the law against drug violation.Objective: This study aimed to identify and analyze drug distribution patterns to provide an overview of drug sampling in the public sector. Methods: The data was collected from Balai Besar Pengawas Obat dan Makanan (BBPOM) Palangka Raya’s database. The collected data were the drug sampling data from Integrated Information Reporting Systems (IIRS) application from 2014 to 2018. Next, we employed CRISP-DM methodology to analyze the data and to identify the pattern. K-means clustering model was selected for data modeling.Results: The dataset contained five attributes, i.e., drug name, therapeutic classes, district/city, sample category, and evaluation of drug surveillance. The drug distribution pattern formed three clusters. First cluster contained 522 drug items in eight therapeutic classes and spread over ten districts, second cluster contained 1542 drug items in five therapeutic classes and spread over five districts, and third cluster contained 503 drug items in eleven therapeutic classes and spread across nine districts.Conclusion: To conclude, the applied data mining technique has improved the decision on the drug sampling planning. It also provides in-depth information on the improvement of drug post-marketing control performance in Central Kalimantan Province.Keywords: Clustering, CRISP-DM, Data Mining, Drug distribution patterns, Drug quality control, Drug sampling