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All Journal Journal of Technology and Informatics (JoTI) Jurnal Informatika Teknologi dan Sains (Jinteks)
Pakpahan, Vera Febrianti
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Mechanical Engineering

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Perancangan Aplikasi EMKASADA untuk Penjadwalan Kegiatan Perkuliahan Program Studi Sains Data UPN Veteran Jawa Timur Pakpahan, Vera Febrianti; Afidria, Zulfa Febi; Bhalqis, Anissa Andiar; Hindrayani, Kartika Maulida; Trimono
Journal of Technology and Informatics (JoTI) Vol. 7 No. 1 (2025): Vol. 7 No.1 (2025)
Publisher : Universitas Dinamika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37802/joti.v7i1.835

Abstract

The development of information technology has encouraged innovation in various fields, including education. Lecture scheduling is one important aspect that requires special attention to ensure efficient and effective use of resources. The EMKASADA application improves efficiency in lecture scheduling by automating the process of preparing schedules, thus reducing the time and manual effort in managing schedules. With features such as dashboards, lecturer data, courses, days, sessions, rooms, lecturers, and automatic scheduling, this system is able to speed up the schedule preparation process and optimize the allocation of available resources. In terms of effectiveness, the EMKASADA application ensures that scheduling is more optimal by minimizing the possibility of clashes between lecturer schedules, courses, and rooms. With the waterfall method approach, the system is developed in a structured and systematic manner, following the stages from requirements analysis to maintenance. Testing was conducted using the black box testing method to ensure all application features, such as dashboards, lecturer data, courses, days, sessions, rooms, lecturers, and scheduling, function properly. The test results show that the features in the EMKASADA application function properly and are able to increase efficiency in scheduling lectures.
PERAMALAN MENGGUNAKAN HYBRID SEASONAL ARIMA DAN EXTREME LEARNING MACHINE: STUDI KASUS JUMLAH PRODUKSI BERAS DI PROVINSI JAWA TIMUR Pakpahan, Vera Febrianti; Muhaimin, Amri; Syaifullah, Wahyu
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 7 No 4 (2025): EDISI 26
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v7i4.6673

Abstract

Penelitian ini mengevaluasi performa metode hybrid Seasonal Autoregressive Integrated Moving Average (SARIMA) dan Extreme Learning Machine (ELM) untuk peramalan data deret waktu. Metode SARIMA digunakan untuk menangkap pola musiman dan linier, sedangkan ELM diaplikasikan pada residual prediksi SARIMA untuk mendeteksi pola non-linier yang sulit ditangkap oleh model tradisional. Studi kasus difokuskan pada prediksi produksi beras bulanan di Provinsi Jawa Timur, salah satu lumbung beras nasional dengan fluktuasi produksi yang memengaruhi perencanaan distribusi dan kebijakan pangan. Hasil evaluasi menunjukkan bahwa model hybrid SARIMA–ELM mencapai nilai MAPE sebesar 9,01% dan RMSE sebesar 38.639,93, menunjukkan akurasi prediksi yang baik. Temuan ini menegaskan bahwa kombinasi SARIMA dan ELM dapat menjadi pendekatan yang efektif untuk peramalan deret waktu dengan pola linier dan non-linier, serta memiliki potensi untuk diterapkan pada dataset atau sektor lain yang memiliki karakteristik serupa.
Co-Authors Afidria, Zulfa Febi Bhalqis, Anissa Andiar Hindrayani, Kartika Maulida Muhaimin, Amri Syaifullah, Wahyu Trimono