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All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF APPLIED INFORMATICS AND COMPUTING JOURNAL OF INFORMATICS AND COMPUTER SCIENCE International Journal of Engineering, Science and Information Technology Jurnal Tika Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) TECHSI - Jurnal Teknik Informatika Jurnal Teknologi Terapan and Sains 4.0 INOVTEK Polbeng - Seri Informatika
Risawandi, Risawandi
Universitas Malikussaleh
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Journal : JOURNAL OF INFORMATICS AND COMPUTER SCIENCE

 1 
SISTEM PENDUKUNG KEPUTUSAN MEMPREDIKSI KELULUSAN MAHASISWA INFORMATIKA MENGGUNAKAN METODE SAW Risawandi Risawandi; Lidya Rosnita; Rian Kelana Putra
JOURNAL OF INFORMATICS AND COMPUTER SCIENCE Vol 9, No 1 (2023): April 2023
Publisher : Ubudiyah Indonesia University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33143/jics.v9i1.2944

Abstract

Abstrak— Kelulusan mahasiswa merupakan tanda berakhirnya mahasiswa dalam menyelesaikan pendidikan pada jenjang sarjana. Kelulusan juga merupakan hasil akhir pencapaian yang membanggakan dalam menempuh suatu pendidikan pada jenjang tertentu. Untuk memenuhi standar kopetensi lulusan bagi mahasiswa program sarjana (S1) beban wajib yang harus ditempuh adalah paling sedikit 144 SKS dengan masa studi waktu maksimal 14 semester. Tetapi penulis melihat di lapangan terdapat beberapa mahasiswa yang tidak bisa lulus tepat waktu. Dalam kasus ini, penulis melakukan penelitian di prodi Teknik Informatika. Penulis melihat ada beberapa mahasiswa yang tidak dapat menyelesaikan masa perkuliahannya dengan tepat waktu. Untuk itu, penulis membuat sebuah aplikasi prediksi kelulusan mahasiswa untuk melihat apakah para mahasiswa dapat lulus tepat waktu atau tidak.Dalam penelitian ini, penulis menggunakan metode SAW (Simple Additive Weight) untuk melakukan proses prediksi kelulusan dengan perhitungan kriteria seperti nilai IPK, IP, semester berjalan, dan juga kecukupan SKS. Penelitian ini menguji setidaknya 25 mahasiswa dengan kriteria nilai berupa IPK, 2 nilai IPS terakhir, Semester berjalan dan banyaknya SKS yang diambil. Hasil dari sistem yaitu, V23 dengan nilai 1, mendapatkan peringkat 1, memiliki kemungkinan tinggi untuk bisa menyelesaikan perkuliahan tepat waktu.Kata kunci: Kelulusan, Informatika, SAW, IPK, SKSAbstract— Student graduation is a sign of the end of students in completing education at the undergraduate level. Graduation is also the final result of a proud achievement in pursuing an education at a certain level. To meet graduate competency standards for undergraduate students (S1) the mandatory load that must be taken is at least 144 credits with a maximum study period of 14 semesters. However, the author sees that in the field there are several students who cannot graduate on time. In this case, the authors conducted research in the Informatics Engineering study program. The author sees that there are some students who cannot complete their studies on time. For this reason, the authors created a student graduation prediction application to see whether students could graduate on time or not. In this study, the authors used the SAW (Simple Additive Weight) method to carry out the graduation prediction process by calculating criteria such as GPA, GPA, semester running, and also the adequacy of credits. This study tested at least 25 students with grade criteria in the form of GPA, the last 2 IPS scores, the current semester and the number of credits taken. The results of the system, namely, V23 with a value of 1, get a rank of 1, have a high probability of being able to complete lectures on time.Keywords: Keywords : Graduation, Informatics, SAW, GPA, Credit
ANALISIS SENTIMEN KEPUASAN CUSTOMER TERHADAP EKSPEDISI TIKI, SICEPAT EXPRESS DAN NINJA EXPRESS MENGGUNAKAN ALGORITMA NAIVE BAYES Nurhaliza Bin Aras; Risawandi Risawandi; Lidya Rosnita
JOURNAL OF INFORMATICS AND COMPUTER SCIENCE Vol 9, No 1 (2023): April 2023
Publisher : Ubudiyah Indonesia University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 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 BayesAbstract— 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
Co-Authors Angaw, Mariance Wulan Asrianda Asrianda Asrianda Asrianda Asrul Fahmi Bustami Bustami Bustami Bustami Dahlan Abdullah Eva Darnila Fadlisyah Fadlisyah Fuadi, Wahyu Furqan, Hafizul Gunarwan Gunarwan Gunarwan, Gunarwan Halimatun Sakdiah Halimatun Sakdiah, Halimatun Helmi Naluri Julita, Rina Khainesya, Khainesya Lidya Rosnita Luqman Nul Hakim M. Irsan Maulana Amri Muhammad Fikry Muhammad Iqbal Muhammad Wahyu Pohan Mukti Qamal mulkal razali Mutammimul Ula Nurdin Nurdin Nurhaliza Bin Aras Nursanti Nursanti Nursanti Nursanti Nurul Aflah Nurul Aflah Olivia, Karina Pranidana, Abdi Mulia Rian Kelana Putra Riska Yanti RISKA YANTI, RISKA Rizal S.Si., M.IT, Rizal Rosdian dian rosdian rosdian, Rosdian dian Rozzi Kesuma Dinata Rozzy Rozzy Safwandi Senda, Tito Afwi Tito Afwi Senda Ulfa, Septia Mulya Wahyu Fuadi Wahyu Fuadi Yesy Afrillia Zahrah, Violita Aditya Zainannur Nasution Zakiatul Husna