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Journal : JURNAL SISTEM INFORMASI BISNIS

Sistem Informasi Pendukung Keputusan Terhadap Mutu Lulusan dengan Metode Fuzzy Model Tsukamoto Ghozali, Ahmad Lubis; Mustafid, Mustafid; Farikhin, Farikhin
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 4, No 2 (2014): Volume 4 Nomor 2 Tahun 2014
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (921 KB) | DOI: 10.21456/vol4iss2pp87-95

Abstract

The importance of graduate information systems to support leadership in taking a decision related to the development of alumni, so that should make for a graduate information systems implemented in the form of web portals. Analysis of the data processed by the method of OLAP (Online Analytical Processing), KPI (Key Performance Indicators) graduates, and data mining to extract and transform data holds the data will be stored in the warehouse. The process of data analysis using OLAP and Fuzzy method to determine the parameters of the model Tsukamoto graduate performance and quality of college graduates. The process of data analysis is represented in the form of tables, graphs, and dashboards, then used as a prop for academic results. OLAP analysis result data processed using the fuzzification, inference, and defuzzification to produce quality graduates index. These findings form a web-based information systems graduate portal with content features alumni and stakeholders as a graduate performance indicators that can be accessed through an Internet connection. The information system produces graduates index KPI performance and quality of graduates graduated as a decision support by the leadership and the head of the research program carried out at the University, KPI graduates to indicate that the parameters of the specific level of quality graduates and overall views of the dimensions of the year and course of study, such as in 2011 the level of quality of graduates of IT course overall "Good", TM course as a whole "Good", TP courses overall "Good". Keywords: Information systems graduates; OLAP, KPI graduates; Tsukamoto Fuzzy Logic model
Sistem Informasi Forecasting Produksi Padi Menggunakan Metode Least Square Fikri, Moh Ali; Ghozali, Ahmad Lubis; Darsih, Darsih
Jurnal Sistem Informasi Bisnis Vol 15, No 1 (2025): Volume 15 Number 1 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss1pp81-88

Abstract

Agriculture has an important role in the commodity sector of the Indonesian people's economy. Indonesia is an agricultural country with extensive agricultural land. So it is truly ironic that Indonesia, as an agricultural country, has to import several basic food ingredients from abroad. Rice production data from year to year has decreased in Indonesia. If the decline in rice production continues in the future, Indonesia will not be able to cope with the increasing food needs of the people. More than 90% of the rice consumed by Indonesian people is self-produced. About 95% of this production is produced from rice fields. Indonesia's land area and territory are so large, a strategic step is needed that can overcome the problem of decreasing rice production. One step that can be taken is to mitigate rice production data by being able to read the data and process it into an appropriate source of information. One of the methods used is applying parameter estimation in regression analysis based on minimizing the sum of squares of the residuals created in the results of each individual equation, namely least squares. The data processed is rice harvest area, production and productivity by province in 2018-2020 and 2019-2023. The creation of the information system uses the PHP programming language version 8.2.4 which runs on the Apache 2.0 web server and the php-ml library. The research resulted in a forecast for rice production in 2024 of 52,676,827 tons, in 2025 of 51,936,919 tons, and in 2026 of 51,197,011 tons. Forecasting accuracy using the least squares method is very good with a MAPE value of 1.93%.