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All Journal Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Mitra Mahajana: Jurnal Pengabdian Masyarakat J-Icon : Jurnal Komputer dan Informatika Jurnal Inovatif Wira Wacana
Emerensye S. Y. Pandie
Universitas Nusa Cendana
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Public Health Social Sciences

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IMPLEMENTASI ALGORITMA DATA MINING NAIVE BAYES PADA KOPERASI Emerensye S. Y. Pandie
J-Icon : Jurnal Komputer dan Informatika Vol 6 No 1 (2018): Maret 2018
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v6i1.350

Abstract

One of the factors of failure in the field of credit business is the lack of accurate assessment of the ability of the debtor, thus resulting in errors in credit decisions that culminate in credit congestion. Data mining techniques can be used to assess customer ability based on past data. Debtor data that has been through the stages of data mining is then processed using Naive Bayes data mining algorithm. Naive Bayes is a simple probabilistic based prediction technique based on the application of bayes rules. Implementation using Weka 3.8 with a total of 3018 records yields a truth level of 94%.
SISTEM INFORMASI PELAYANAN PUBLIK KELURAHAN BAKUNASE KOTA KUPANG UNTUK PENINGKATAN KUALITAS PELAYANAN BERBASIS WEB D D Anggiawan; Emerensye Pandie; Meiton Boru
J-Icon : Jurnal Komputer dan Informatika Vol 6 No 2 (2018): Oktober 2018
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v6i2.509

Abstract

Sub district Bakunase Kota Raja District handles public service activities in the form of the data of the population and the creation of the certificate. The system runs in the sub district Bakunase was limited because still using microsoft excel and microsoft word for storage of data so that it cannot provide information on population data quickly and cannot be accessed online. To answer the problem a web-based demographic information system is produced to manage the data of the population and the creation of the nine(9) certificate along with outgoing mail report and demographic data reports which are all based online that can be accessed by the public and the officer at any time. To achieve these goals in building this information system using the method waterfall with methods of analysis system used the diagram context, DFD, ERD and table relationships. Testing system using blackbox method that yields 100% accuracy of the system and to get the response from the user used questionnaire method where the results of the questionnaire distribution obtained the level of satisfaction with an average of 4.205 or 84.1%.
C4.5 Algorithm Implementation to Predict Student Satisfaction Level of Lecturer’s Performance in the Covid-19 Pandemic Ledoh, Juan Rizky Mannuel; Andreas, Ferdinandus Elfanto; Pandie, Emerensye Sofia Yublina; Amos Pah, Clarissa Elfira
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 20, No 2 (2023): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v20i2.8284

Abstract

Implementation of education during the emergency period of Covid-19 in Higher Education was carried out at home through online/distance learning. The lecturer is one of the key holders of success in the learning process. Lecturer performance is a main factor needed to improve education and service quality in online learning. In this study, the authors implemented the C4.5 algorithm using RapidMiner 9.10 app to predict student satisfaction with lecturer performance during the Covid-19 pandemic. The data in this study were obtained from a questionnaire distributed to active students in the Computer Science Study Program (class of 2016 - 2021) at the University of Nusa Cendana with 942 records. The attributes used in this study were the lecturer's age, gender, suitability of learning media (SLM), and the competencies of Pedagogic Competence (PeC), Professional Competence (PrC), Personal Competence (PsC), and social competence (SC), with the level of student satisfaction as the target class divided into two, namely Satisfied and Dissatisfied. The dataset is processed using RapidMiner and produces 11 decision rules which show that the attribute PeC has the most significant influence on the level of student satisfaction with lecturer performance during the Covid-19 pandemic and the test results of the decision tree model using cross-validation. The test results show that the C4.5 algorithm has a good performance in predicting levels of student satisfaction with an accuracy rate of 94.8%, precision for the prediction class Dissatisfied and Satisfied of 92.23 % and 95.52%, and recall of the actual Dissatisfied and Satisfied classes of 85.2% and 97.77%.
Penggunaan Data Mining Algoritma C4.5 dalam Menentukan Klasifikasi Nasabah Potensial di PT. ADIRA Finance Soe Missa, Wanto I; Pandie, Emerensye Sofia Yublina; Widiastuti, Tiwuk
Jurnal Inovatif Vol. 2 No. 2 (2023): Agustus 2023
Publisher : Universitas Kristen Wira Wacana Sumba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58300/inovatif.v2i2.631

Abstract

Klasifikasi Nasabah Potensial merupakan suatu kegiatan yang dilakukan untuk mendapatkan nasabah yang benar-benar berpotensi dengan memperhatikan beberapa aspek yang menunjang agar penerima kredit layak menerima pinjaman. PT. Adira Finance SoE juga merupakan sebuah lembaga yang memberikan layanan kredit pinjaman terhadap nasabah dan sering kali masalah yang dihadapi ialah adanya penerimaan nasabah yang tidak sesuai prosedur sehingga menyebabkan adanya tunggakan pembayaran kredit oleh para nasabah. Dengan menggunakan algoritma C4.5 diharapkan dapat membantu menyelesaikan masalah yang ada dimana algoritma C4.5 digunakan untuk mempelajari karakteristik berdasarkan data nasabah sebelumnya agar menghindari ada nasabah yang melakukan tunggakan kredit. Pengujian yang dilakukan terhadap 1000 record data dengan menggunakan beberapa atribut sebagai penunjang algoritma C4.5 dimana atribut yang digunakan ialah, penghasilan, jumlah tanggungan, umur, status perkawinan, pekerjaan, tempat tinggal. Hasil pengujian ini mendapatkan pohon keputusan (decision tree) yang menentukan nasabah tersebut layak atau tidak mendapatkan pinjaman berdasarkan atribut-atribut yang ada dari data nasabah sebelumnya. Pengujian system dilakukan dengan menerapkan algoritma K-Fold Cross Validation pada saat telah dihitung dengan menggunakaan algoritma C4.5 dengan hasil dari 1000 record dimana 956 record berada pada kelas klasifikasi yang tepat dan 44 record berada pada kelas klasifikasi yang tidak tepat.
SOSIALISASI KEJAHATAN SIBER DAN PERLINDUNGAN DATA PRIBADI UNTUK MENCEGAH PENIPUAN BERBASIS ONLINE TERHADAP MASYARAKAT Amos Pah, Clarissa Elfira; Mola, Sebastianus Adi Santoso; Ledoh, Juan Rizky Mannuel; Pandie, Emerensye Sofia Yublina; Fanggidae, Adriana; Giri, Imanuel Raja
Mitra Mahajana: Jurnal Pengabdian Masyarakat Vol. 6 No. 1 (2025): Volume 6, Nomor 1 Maret 2025
Publisher : LPPM Universitas Flores

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37478/mahajana.v6i1.4908

Abstract

During 2023, criminals carried out thousands of cyber-attack cases that harmed the community economically. Losses due to cybercrime worldwide in 2023 reached US $ 8 trillion and there have been more than 361 million cyber-attacks in Indonesia from January to October 2023 according to data from the National Cyber and Crypto Agency. Activities that are often reported and become the main target of cybercrime are online buying and selling which ranks 1st, followed by scamming, fictitious online investment, online work fraud, online extortion, and web phishing. Seeing the large number of victims caught in cyber-attacks, as a form of contribution to the community in the field of technology, we conducted a socialization of cyber security and privacy protection to increase public sensitivity to the dangers of cyber-attacks and prevention tips. The stages of implementation that have been carried out are visitation and licensing, observation and information gathering, making cooperation agreements, preparation of presentation materials, technical preparation, and implementation of socialization. This socialization has also been covered in the Pos Kupang electronic media and received a positive response from all participants.
Co-Authors Adriana Fanggidae Andreas, Ferdinandus Elfanto Clarissa Elfira Amos Pah D D Anggiawan Giri, Imanuel Raja Juan Rizky Mannuel Ledoh Meiton Boru Missa, Wanto I Sebastianus Adi Santoso Mola Tiwuk Widiastuti