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Bertha S Djahi
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Computer Science & IT

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DATA MINING UNTUK KLASIFIKASI STATUS GIZI DESA DI KABUPATEN MALAKA MENGGUNAKAN METODE K-NEAREST NEIGHBOR Brigita Fahik; Bertha S Djahi; Nelci D Rumlaklak
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.v6i1.348

Abstract

Classification of village status according to the number of malnourished patients is very important in anticipating malnutrition cases in a region, especially for the areas in the district of Malaka. Cases of malnutrition recorded quite a lot in the District of Malaka demanded the district government of Malaka to immediately anticipate the problem. To overcome this problem, we used k-Nearest Neighbor method to classify the status of villages in Malaka District based on the level of under-five children under the red line into three target classes: low, medium, and high. Prior to the classification process, clustering process is done using K-Means method so that all data can be divided into classes that have been determined. The data used in this study as many as 174 data taken from the year 2013-2015. The final result, after validation of clustering data obtained resemblance to the original data of 98.25%, and the results of system testing of 93.10%. Determination of the best value of k with the test data of 34 pieces and the training data of 140 pieces is at k = 7 with the average percentage of similarity of 95.53%.
SISTEM INFORMASI AKUNTANSI PADA MADRASAH TSANAWIYAH AL-IKHLAS SOE KABUPATEN TTS PROVINSI NTT Mutia Lestari; Emerensye S Y Pandie; Bertha S Djahi
J-ICON : Jurnal Komputer dan Informatika Vol 10 No 2 (2022): Oktober 2022
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v10i2.8124

Abstract

School financial accounting activities are one of the important activities in every educational institution. The Madrasah Tsanawiyah (MTs) Al-Ikhlas Soe, TTS district, NTT province also carried out this activity but it was still done manually which had to be recorded every time a financial accounting transaction was carried out. Therefore, the researchers designed and built a web that aims to enable schools to record accounting transactions through a computerized system which then produces accounting data reports for student tuition payments, school enrollment payments, honorary teacher salaries and school financial cash flows. The method used is the software development life cycle (SDLC) method, which is one method with a characteristic where each phase of work is carried out must be done first before proceeding to phase next, thus the results will focus on each phase so that the work is carried out optimally because there is no parallel work. This study uses two tests of the system, namely blackbox which focuses on testing the functional specifications of the system software, and testing questionnaires to get responses or answers from respondents, namely teachers from MTs Al-Ikhlas Soe regarding the system that has been created. With these two tests, this application system gets a 100% test score percentage using blackbox this is because the functionality of the software runs as expected and also gets an average percentage test value of 83% or 80% using questionnaire testing.
PENERAPAN METODE FUZZY C-MEANS DALAM PENENTUAN PENERIMA BEASISWA PROGRAM INDONESIA PINTAR (PIP) Mardiani Thiaralivta Geraldine Kadja; Nelci Dessy Rumlaklak; Bertha S Djahi
J-ICON : Jurnal Komputer dan Informatika Vol 11 No 1 (2023): Maret 2023
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v11i1.9846

Abstract

The process of selecting scholarship recipients for Program Indonesia Pintar (PIP) at SMA Negeri 2 Kupang is still done manually by comparing student data. That process can cause the emergence of a reasonably high level of complexity and requires a relatively long time to get the results. Therefore, a Decision Support System (DSS) was built using the Fuzzy C-Means (FCM) method in this study. The FCM method groups data on prospective scholarship recipients with almost the exact resemblance into one cluster. Five (5) criteria are used in selecting PIP scholarships: the number of dependents, parents’ income, water bills, electricity bills and the value of the latest report card. The data is from class XI (eleven) students in 2019 at SMA Negeri 2 Kupang, totaling 422 students. The results of the FCM calculation with a maximum iteration of 100 and an error value of 0.00001 get 240 students entering cluster 1, namely eligible to receive scholarships and as many as 182 students entering cluster 2, namely not eligible to receive scholarships. The testing method used in this study is blackbox testing which is divided into 8 (eight) test scenarios and obtains valid results for all of them. The DSS for determining PIP scholarship recipients using the FCM method is more effective and efficient because it can save time, and scholarships can be awarded to the right students.
Co-Authors Brigita Fahik Emerensye S Y Pandie Mardiani Thiaralivta Geraldine Kadja Mutia Lestari Nelci D Rumlaklak Nelci Dessy Rumlaklak