ANALISIS SENTIMEN KEPUASAN CUSTOMER TERHADAP EKSPEDISI TIKI, SICEPAT EXPRESS DAN NINJA EXPRESS MENGGUNAKAN ALGORITMA NAIVE BAYES

Authors

  • Nurhaliza Bin Aras
  • Risawandi Risawandi
  • Lidya Rosnita

DOI:

https://doi.org/10.33143/jics.v9i1.2943

Abstract

Abstrak—Perkembangan ilmu pengetahuan dan teknologi informasi pada masa ini sangat pesat. Adanya pemasaran produk secara global tersebut menjadikan perkembangan ekspedisi barang juga mengalami kemajuan yang signifikan. Kebutuhan penggunaan jasa ekspedisi barang yang dipergunakan masyarakat untuk memenuhi berbagai kebutuhannya sangat meningkat pesat. Hadirnya berbagai jasa ekspedisi barang tidak hanya mempermudah masyarakat namun juga para pengusaha atau seller. Penelitian ini bertujuan untuk menganalisis sentimen terhadap kepuassan customer ekspedisi yaitu tiki, sicepat express dan ninja express pada twitter dengan menggunakan metode Algoritma Naïve Bayes. Beberapa proses dalam melakukan klasifikasi sentimen, yang pertama melakukan koleksi data di twitter menggunakan scraping setalah itu pemberian labelling, kemudian dilakukan text pre-processing pada data yang meliputi cleansing data, case folding, tokenizing, stopword removal, dan stemming. Selanjutnya dilakukan proses klasifikasi pada data. Data yang digunakan dalam penelitian ini berjumlah 3000, setiap objeknya dengan jumlah 1000 data kemudian dibagi menjadi 3 kelas yaitu positif, negatif dan netral. Dari 3000 data dibagi menjadi 2 bagian yaitu 70% data training dan 30% data testing. Berdasarkan hasil evaluasi klasifikasi dengan algoritma Naïve Bayes menghasilkan akurasi yang sangat tinggi. Akurasi Sicepat Express sebesar 89,73%, presisi sebesar 58,81%, recall sebesar 40,1% dan f1-score sebesar 42,6%. Akurasi Ninja Express sebesar 80,66%, presisi sebesar 49,4%, recall sebesar 40,8% dan f1-score sebesar 41,5%. Akurasi Tiki sebesar 74,48%, presisi sebesar 65,42%, recall sebesar 57,14% dan f1-score sebesar 56,81%.

Kata kunci: Ekspedisi, Sentimen, Data, Naïve Bayes

Abstract— The development of science and information technology at this time is very rapid. The existence of global product marketing has made the development of freight forwarding also experience significant progress. The need for the use of freight forwarding services that are used by the community to meet their various needs is increasing rapidly. The presence of various freight forwarding services not only makes it easier for the community but also entrepreneurs or sellers. This study aims to analyze sentiment on customer satisfaction on expeditions, namely tiki, sicepat express and ninja express on twitter using the Naïve Bayes algorithm. There are several processes in classifying sentiments, the first is to collect data on twitter using scraping after that labeling, then text pre-processing is carried out on the data which includes data cleansing, case folding, tokenizing, stopword removal, and stemming. Furthermore, the classification process is carried out on the data. The data used in this study amounted to 3000, each object with a total of 1000 data was then divided into 3 classes, namely positive, negative and neutral. Of the 3000 data is divided into 2 parts, namely 70% training data and 30% testing data. Based on the results of the classification evaluation with the Naïve Bayes algorithm, it produces a very high accuracy. The accuracy of Sicepat Express is 89.73%, precision is 53,5%, recall is 40,1% and f1-score is 42,6%. Ninja Express accuracy is 80.66%, precision is 49,4%, recall is 40,8% and f1-score is 41,5%. Tiki's accuracy is 74.48%, precision is 65,42%, recall is 57,14% and f1-score is 56,81%.

Keywords: Ekspedition, Sentiment, Data, Naïve bayes

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Vol. 9 No. 1 (2023): April 2023

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