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All Journal Jiko (Jurnal Informatika dan komputer) Jurnal Garuda Pengabdian Kepada Masyarakat
Harahap, Rina Syafiddini
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Humanities Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Social Sciences Other

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IMPLEMENTATION OF THE FUZZY TIME SERIES METHOD FOR FORECASTING BLOOD NEEDS IN THE INDONESIAN RED CROSS (PMI) MEDAN Harahap, Rina Syafiddini; R, Rakhmat Kurniawan
JIKO (Jurnal Informatika dan Komputer) Vol 7, No 2 (2024)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v7i2.8614

Abstract

The primary issue faced by PMI (Indonesian Red Cross) about blood requirements is often associated with insufficient blood supplies to satisfy the demand of patients, particularly during emergencies or significant catastrophes such as natural calamities. Hence, it is essential to use appropriate methodologies to forecast blood requirements accurately and determine the quantity of blood bags required in the future. When forecasting calculations using fuzzy time series, the interval length is established at the start of the calculation procedure. The duration of the gap significantly affects the establishment of fuzzy associations, which in turn affects the difference in forecast computation outcomes. The investigation reveals that Group AB has the lowest Root Mean Square Error (RMSE) value of 136.90, indicating that your model demonstrates superior accuracy in predicting blood group AB compared to other blood groups. The RMSE score for Group O is 819.5, which suggests that your model's accuracy in predicting blood group O is lower compared to other blood groups
Rancang Bangun Alat Pendeteksi Kematangan Buah Sawit Dengan Menggunakan Metode Image Processing Berdasarkan Komposisi Warna Syahira, Melani Alka; Khoiriah, Miftahul; Harahap, Rina Syafiddini
Jurnal Garuda Pengabdian Kepada Masyarakat Vol 1 No 2 (2023)
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/gabdimas.v1i2.827

Abstract

Pemanfaatan citra digital sangat penting untuk mengetahui kematangan buah sawit dengan memanfaatkan sistem yang ada. Dengan adanya citra digital maka untuk menentukan kematangan buah sawit berdasarkan warnanya bisa dilakukan secara computing (berbasis teknologi), yaitu dengan menerapkan pengolahan citra menggunakan metode transformasi ruang warna HSV (Hue, Saturation, Value). Model warna HSV (Hue, Saturation, Value) mengelompokkan komponen intensitas dari informasi warna yang dibawa (hue dan saturation) dalam warna citra. Klasifikasi kematangan buah sawit dari pengujian 30 sampel citra buah sawit, dapat dilihat dari rentang nilai Hue. Ektrasi RGB ke HSV nilai pada kulit buah Sawit menghasilkan dua klasifikasi nilai rentang Hue, yaitu warna hitam kekuningan dengan nilai Hue (0.25604 - 0.59155) untuk sawit mentah, warna orange merah tua dengan nilai Hue (0.06511 - 0.12985) untuk sawit matang. Hasil dari deteksi kematangan dapat dilihat pada masing-masing pengujian dengan nilai presentase 100% untuk kategori buah sawit matang, 100% untuk kategori buah sawit mentah. Nilai presentase untuk pengujian keseluruhan data mempunyai presentase nilai yang baik dimana berpengaruh dalam mendeteksi kematangan sawit yaitu sebesar 100%. Maka dapat disimpulkan, bahwa pendeteksian kematangan buah sawit dapat dilakukan dengan menerapkan metode transformasi ruang warna HSV.
IMPLEMENTATION OF THE FUZZY TIME SERIES METHOD FOR FORECASTING BLOOD NEEDS IN THE INDONESIAN RED CROSS (PMI) MEDAN Harahap, Rina Syafiddini; R, Rakhmat Kurniawan
JIKO (Jurnal Informatika dan Komputer) Vol 7, No 2 (2024)
Publisher : Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v7i2.8614

Abstract

The primary issue faced by PMI (Indonesian Red Cross) about blood requirements is often associated with insufficient blood supplies to satisfy the demand of patients, particularly during emergencies or significant catastrophes such as natural calamities. Hence, it is essential to use appropriate methodologies to forecast blood requirements accurately and determine the quantity of blood bags required in the future. When forecasting calculations using fuzzy time series, the interval length is established at the start of the calculation procedure. The duration of the gap significantly affects the establishment of fuzzy associations, which in turn affects the difference in forecast computation outcomes. The investigation reveals that Group AB has the lowest Root Mean Square Error (RMSE) value of 136.90, indicating that your model demonstrates superior accuracy in predicting blood group AB compared to other blood groups. The RMSE score for Group O is 819.5, which suggests that your model's accuracy in predicting blood group O is lower compared to other blood groups
Co-Authors Khoiriah, Miftahul Rakhmat Kurniawan R Syahira, Melani Alka