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All Journal RABIT: Jurnal Teknologi dan Sistem Informasi Univrab METIK JURNAL
Huban Kabir
Universitas Subang
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Engineering

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Perbandingan Algoritma C4.5 dan Naïve Bayes dalam Menentukan Persediaan Stok Rian Pratama; Baenil Huda; Elfina Novalia; Huban Kabir
METIK JURNAL Vol 6 No 2 (2022): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v6i2.379

Abstract

Dalam bisnis ritel, persediaan merupakan faktor penting yang perlu diperhitungkan. Jumlah persediaan yang keluar masuk harus dipeerhitungkan. Alasannya adalah agar stok persediaan tetap stabil dan juga untuk menghindari kerugian yang disebabkan oleh kadaluarsa. Masalahnya adalah setiap item memiliki pembelian yang berbeda. Oleh karena itu, diperlukan perhitungan untuk memprediksi item apa saja yang perlu ditambah atau dikurangi di gudang. Berdasarkan permasalah tersebut, metode klasifikasi data mining digunakan dalam menentukan algoritma yang cocok untuk prediksi persediaan. Dua algoritma yang digunakan adalah algoritma C4.5 dan Naive Bayes. Setelah dilakukan pengujian kedua algoritma tersebut menggunakan tools RapidMiner, didapatkan hasil bahwa algoritme C4.5 memberikan nilai akurasi sebesar 96.80%, sedangkan algoritma Naive Bayes memberikan hasil sebesar 91.20%. Kesimpulannya adalah algoritma C4.5 baik untuk prediksi persediaan.
ANALISIS USER SENTIMENT APLIKASI GOOGLE MAPS, MAPS.ME DAN WAZE MENGGUNAKAN METODE SUPPORT VECTOR MACHINE Ilham Fariz Asya Mubarok; Baenil Huda; Agustia Hananto; Tukino Tukino; Huban Kabir
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 8 No 1 (2023): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v8i1.3020

Abstract

Nowadays, the routing app is often used by many people, this app is very useful for users to find the best route by just entering the address code, this app can provide travel routes which can be taken by different kinds of vehicles. In Indonesia itself, there are several widely used route guidance apps with various positive and negative reviews. In this study, different types of apps namely Google Maps, Maps.me and Waze were used and the data is from user feedback through an online survey. The purpose of this study is to find out the users' ratings for each application which was used as the material for the study. Support Vector Machine method was used to process the data. For each app, 750 comments were received and the final result of maps.me was the app with the highest score based on 86.40% accuracy, 86.55% precision and 99.69% recall. The maps.me app received 68% positive reviews, followed by Waze with 29% and Google Maps with 3%. This makes maps.me the app with the highest score based on positive reviews.
Co-Authors Baenil Huda Baenil Huda Hananto, Agustia Ilham Fariz Asya Mubarok Novalia, Elfina Rian Pratama tukino, tukino