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Nelci D Rumlaklak
Universitas Nusa Cendana
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%.
PENERAPAN METODE FUZZY SERVICE QUALITY (SERVQUAL) UNTUK MENGANALISA KEPUASAN PELAYANAN PENDIDIKAN PADA JURUSAN ILMU KOMPUTER FAKULTAS SAINS DAN TEKNIK UNIVERSITAS NUSA CENDANA Roswita R Ligoresi; Sebastianus Adi Santoso Mola; Nelci D Rumlaklak
J-Icon : Jurnal Komputer dan Informatika Vol 5 No 2 (2017): Oktober 2017
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v5i2.365

Abstract

In carrying the service of education, Departmen Of Computer Science Faculty Of Science And Technique University Of Nusa Cendana, trying to give the service that can be contented the students. So far the departmen doesn’t know how the assessment of students against the service given. The survey of students statisfaction can be a manner to deliver what they feel and what is the hope of students against the service of education. Fuzzy service quality (servqual) method can be used to analyze the statisfaction of service. The concept of fuzzy is used to help the respondent for giving value that more objective, while the servqual method define the statisfaction of service as how far the difference between the facts and the hope on the service that is received by respondent. This method have five dimention that are tangibles, reliability, responsiveness, assurance dan emphaty. The result of service statisfaction analysis in Computer Science Department using the fuzzy method in the academic year 2016/2017 the value is GAP -14.3197, that means the giving service is not statisfy. Based on the result of analysis gived repair recommendation of each dimention that is the value of GAP is smallest negative.
PEMILIHAN LAPTOP ATAU NOTEBOOK DENGAN METODE FUZZY MAMDANI DAN SKORING Ahmad Taufik; Tiwuk Widiastuti; Nelci D Rumlaklak
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.v6i2.508

Abstract

The Fuzzy Mamdani method is also known as MinMax method, which finding the minimum value of each rule and the maximum value of the combined consequences of each rule. While scoring is a process of changing the answer of the instrument into numbers which is the quantitative value of ananswer to the items in the instrument. In this study, the authors apply Fuzzy Mamdani and Scoring can be implemented in the manufacture of laptops or notebooks selection applications based on the level of accuracy. The calculation of the accuracy level is based on 5 fuzzy inputs which have 70% portion and10 input scores which have 30% portion. The output of the system in the form of a list of recommended levels of accuracy of selection of laptops/notebooks based on the highest order to the lowest. Based on the testing process then obtained the results: The system can provide convenience for consumers in obtaining the information needed to select the laptops/notebooks right and in line with expectations. This can be evidenced by the results of a survey involving 100 consumers and generate 90% which statesassisted by the application selection of the laptops/notebooks.
IDENTIFIKASI TELAPAK TANGAN MENGGUNAKAN METODE EKSTRAKSI CIRI PRINCIPAL COMPONENT ANALYSIS (PCA) DAN IDENTIFIKASI CIRI RESILIENT PROPAGATION Mellanie Lette; Adriana Fanggidae; Nelci D Rumlaklak
J-ICON : Jurnal Komputer dan Informatika Vol 4 No 1 (2016): Maret 2016
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v4i1.5199

Abstract

The palmprint recognation in this research was being held through several stages, which are image acquisition, preprocessing using histogram equalization,edge detection using sobel operation, feature extraction using Principal Componnent Analysis and face identification using Resilient Propagation. This research use Principal Componnent Analysis as its feature extraction method and Resilient Propagation as its recognition method. This research use 40 training data and 20 testing data wich are gained from PolyU. The final result of the research shows that accuration performance of system using Principal Componnent Analysis and Resilient Propagation by using error tolerance as 1,E-06 and neuron hidden output as 10 are giving best performation that is 65% can be recognized as compared with using the othe error tolerance , neuron output and neuron hidden .
SISTEM PAKAR DIAGNOSIS TINGKAT KECEMASAN MAHASISWA DALAM PENYUSUNAN SKRIPSI MENGGUNAKAN METODE CERTAINTY FACTOR Maria Louise Ludgardis Muku; Sebastianus A S Mola; Meiton Boru; Nelci D Rumlaklak; Tiwuk Widiastuti
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.v10i2.7975

Abstract

The level of student anxiety when compiling a thesis impacts the length of the lecture process. The number of clinical psychologists not proportional to the number of students in East Nusa Tenggara causes many students not to consult a psychologist. An expert system for diagnosing student anxiety levels using the certainty factor method with a HARS scale for 14 criteria and 81 symptoms will help students analyze their anxiety levels. The results of the study based on 300 student data obtained that the accuracy of the expert and system results was 100%, where the more extended the study period, the higher the level of anxiety in students.
Co-Authors Adriana Fanggidae Ahmad Taufik Bertha S Djahi Bertha S. Djahi Brigita Fahik Maria Louise Ludgardis Muku Meiton Boru Mellanie Lette Roswita R Ligoresi Sebastianus A S Mola Sebastianus Adi Santoso Mola Tiwuk Widiastuti