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Sebastianus Adi Santoso Mola
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Program Studi Ilmu Komputer Universitas Nusa Cendana Jl. Adisucipto - Penfui - Kupang - NTT -Indonesia
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J-Icon : Jurnal Komputer dan Informatika
Published by Universitas Nusa Cendana
ISSN : 23377631     EISSN : 26544091     DOI : -
Core Subject : Science,
Computer Science & IT
J-ICON : Jurnal Komputer dan Informatika focuses on the areas of computer sciences, artificial intelligence and expert systems, machine learning, information technology and computation, internet of things, mobile e-business, e-commerce, business intelligence, intelligent decision support systems, information systems, enterprise systems, management information systems and strategic information systems.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 12 Documents
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Search results for , issue "Vol 7 No 1 (2019): Maret 2019" : 12 Documents clear
ANALISIS METODE SINGLE-POINT CROSSOVER (SPX), TWO-POINT CROSSOVER (TPX) DAN MULTI-POINT CROSSOVER (MPX) PADA FUNGSI NONLINEAR DUA PEUBAH DENGAN BINARY CODING Adriana Fanggidae
J-Icon : Jurnal Komputer dan Informatika Vol 7 No 1 (2019): Maret 2019
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v7i1.872

Abstract

Algoritma genetika merupakan salah satu algoritma evolusioner yang memiliki 4 tahapan penting yaitu pengkodean, seleksi, crossover dan mutasi. Pada tulisan ini, kinerja dari binary coding pada 3 metode crossover SPX, TPX, dan MPX diuji pada 5 fungsi nonlinear dua peubah. Hasil yang diperoleh menunjukkan metode crossover TPX memberikan kinerja yang lebih baik daripada SPX dan MPX.
Analisis Model Verhults kaitannya dengan Ketersediaan Dokter Umum di Kabupaten Timor Tengah Selatan (TTS) Ariyanto Ariyanto
J-Icon : Jurnal Komputer dan Informatika Vol 7 No 1 (2019): Maret 2019
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v7i1.874

Abstract

TTS Regency is the second largest regency with the highest population in East Nusa Tenggara. The ratio of general practitioners from 2015 to 2017 is below national standard. Therefore, the TTS regency has experienced a crisis of general practitioners. The research was conducted by taking the number of TTS population of the last eight years. We use the Verhulst model to predict the number of population and propose the ideal number of general practitioners. We found that the number of TTS population is predicted to be 647.815 in 2027. Furthermore, the ideal number of general practitioners in 2027 is 259 people.
PERBANDINGAN KINERJA METODE DETEKSI TEPI PADA CITRA Kornelis Letelay
J-Icon : Jurnal Komputer dan Informatika Vol 7 No 1 (2019): Maret 2019
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v7i1.875

Abstract

The results of the above analysis it is concluded that edge detection is best resulted from the user of the canny method. Edge detection using the canny method is the best edge detection because the line morphology generated by edge detection is better visible on the border of the image both on the inside and the edges of the image appear thick, vertical or horizontal lines on the front of the house is very clear when compared with the two methods above.
KLASIFIKASI SPAM E-MAIL MENGGUNAKAN METODE TRANSFORMED COMPLEMENT NAÏVE BAYES (TCNB) Hanna Florenci Tapikap; Bertha Selviana Djahi; Tiwuk Widiastuti
J-Icon : Jurnal Komputer dan Informatika Vol 7 No 1 (2019): Maret 2019
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v7i1.878

Abstract

Classification is one of the ways to organize text so that the texts with the same contents can be grouped in the same category. One of the famous text classification methods is the Naïve Bayes Method. Naïve Bayes has efficient computation and good prediction result however the performance of Naïve Bayes is not really good in classifying unbalanced dataset. This Naïve Bayes method is then modified to overcome the weakness, this modified method is then known as Transformed Complement Naïve Bayes (TCNB) method. In this research, TCNB method was used to the spam e-mails whose dataset were unbalanced and were consisted of 481 dataset in spam e-mail class, and 2412 dataset in legitimate e-mail class (in total, there are 2893 dataset). The classification was done with and without cross validation. The classification with cross validation was done starting from k=2 until k=10. The classification without cross validation was done by dividing the training data by 80% and testing data by 20%. The result showed that the classification by using TCNB with cross validation had its best accuracy level on k=10 by 93,917% and the classification without cross validation had its best accuracy by 92,760%. Thus it can be concluded that TCNB can handle unbalanced dataset with good prediction accuracy.
PENERAPAN METODE TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) DALAM PENENTUAN UANG KULIAH TUNGGAL DI UNIVERSITAS NUSA CENDANA Benyamin Libing; Dony M Sihotang; Meiton Boru
J-Icon : Jurnal Komputer dan Informatika Vol 7 No 1 (2019): Maret 2019
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v7i1.879

Abstract

Uang Kuliah Tunggal (UKT) merupakan kebijakan pemerintah untuk membantu masyarakat kurang mampu memperoleh pendidikan sampai ke perguruan tinggi. Dalam penentuan UKT, Universitas Nusa Cendana menggunakan metode wawancara. Banyaknya jumlah mahasiswa baru yang diwawancarai untuk menetapkan UKT maka mempengaruhi tingkat keletihan dari pewawancara dan juga mempengaruhi keputusan yang diambil tidak lagi bersifat objektif, sehingga perlu sebuah Sistem Pendukung Keputusan (SPK) untuk membantu menangani masalah tersebut. Metode TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) merupakan salah satu metode dalam SPK yang dapat membantu menyelesaikan masalah tidak terstruktur. Sistem akan menyeleksi setiap alternatif menggunakan lima kriteria yaitu pendapatan orang tua, rekening air dan listrik, aset, jumlah tanggungan dan pekerjaan. Hasil dari pengujian senstifitas perubahan bobot, yang paling besar yaitu pada rekening air dan listrik dengan 91.66% dan yang paling sedikit yaitu pada pekerjaan dengan 35%. Sedangkan pengujian akurasi standar memperoleh hasil 26.66%.
KAJIAN MACHINE LEARNING DENGAN KOMPARASI KLASIFIKASI PREDIKSI DATASET TENAGA KERJA NON-AKTIF Derwin Rony Sina; NEUTRINO KUSRORONG SAE BELAUDIN KUSRORONG; Nelci Dessy Rumlaklak
J-Icon : Jurnal Komputer dan Informatika Vol 7 No 1 (2019): Maret 2019
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v7i1.880

Abstract

Comparative studies of machine learning are carried out with the aim of determining the best method base based on the ability to predict with true data. The study carried out on the labor dataset aims to extract information on the choice of agency employees to exit or not. The method used in the comparative study is K-Nearest Neighbors (KNN) from the basis of similarity, Naïve Bayes (NB) from the probability base, and C4.5 from the basis of the decision tree. Application design and construction is done by receiving input labor data, the dataset is divided into training data and test data, training data for training and models while the test data is used when classifying by model. The classification process is carried out using supply training scenarios and cross validation of 14,999 data. The initial hypothesis C4.5 is the best method with an accuracy measure. Proof of the initial hypothesis will be true if the best accuracy majority is owned by the C4.5 method with supply trainning scenarios and cross validation. The results of the classification data analysis found that the C4.5 accuracy was superior in each parameter of the inventory training scenario data distribution and the k-fold parameter was 3. 5. 7, and 9 of the cross validation scenario so that the best method of non-active labor classification was C4.5.
ANALISIS METODE CYCLE CROSSOVER (CX) DAN METODE PARTIAL MAPPED CROSSOVER (PMX) PADA PENYELESAIAN KASUS TRAVELING SALESMAN PROBLEM (TSP) Theresia Kolo; Adriana Fanggidae; yelly y nabuasa
J-Icon : Jurnal Komputer dan Informatika Vol 7 No 1 (2019): Maret 2019
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v7i1.882

Abstract

Travelling Salesman Problem (TSP) is a form of a problem in optimizing the search for the shortest route by passing through every city in exactly one time. The problem of searching the shortest route of a location can be solved by using many other optimizing algorithms. In this research, genetics algorithm was used by using two crossover methods namely cycle crossover and partial-mapped crossover. The parameters used were crossover probability and mutation probability, the sum of the city, maximum generation, the sum of the population and also threshold. In this research two testing models were used. In the first one, in order to get the generation and the best fitness it used the 80% consistency stopping criteria, and in the second one, in order to get the best testing time, it used the 100 and 500 maximum generation stopping criteria. The result of the first test showed that PMX method is better than the CX one. This was shown through the 8 times of testing which the result was the best PMX generation was 104,0469 and the CX was 350,4563. The second test resulted that the best testing time of the PMX time was 1,1035 second and the CX method was 2,2374 second, thus, it can be concluded that the solution brought by the PMX method is considered better than the CX.
IMPLEMENTASI SISTEM INFORMASI GEOGRAFIS DALAM PENENTUAN INDEKS KESESUAIAN LAHAN TANAMAN PADI DI KOTA KUPANG MENGGUNAKAN METODE SKORING Tiwuk Widiastuti
J-Icon : Jurnal Komputer dan Informatika Vol 7 No 1 (2019): Maret 2019
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v7i1.883

Abstract

Geographic Information System (GIS) is a special information system for managing data that has spatial information. In GIS is often used overlay techniques in merging 2 or more maps in to a unit ofland. In this research, the authors use the scoring method in determining the land suitability index. To get a unit of land done overlay on land type map, slope map, district boundary map, geological map and land cover or land use map. Scoring is done on temperature parameters, rainfall, dry moon, drainage, texture, effective depth, KTK, ground ph, n total, P2O5, K2O, slope, numbers of rock, and rock out crop. The calculationis done by scoring for each parameter based on the predetermined score class, the total of each unit of land will be used to determine the Land Suitability Index based on the classification class. The calculation result is done on 76 land (rice field and rainfed rice field). This test use Simple Linear Regression to find the closeness value between Land Suitability Index and rice produktivity. Linear correlation coeficient (r) obtained value r = 0,77 (positive correlation). The value of this correlation coefficient indicates the degree of closeness of the relationship between the Land Suitability Index and the productivity of the paddy. The value of coefficient of determination R = 0,59 = 59% indicates that 59% of the proposed variation of Y variable (paddy productivity) can be explained by X variable (Land Suitability Index) through linear relationship.
CASE BASED REASONINGUNTUK MENDIAGNOSIS GIZI BURUK PADA ANAKUSIA 0-5 TAHUN MENGGUNAKAN METODE COSINE SIMILARITY Derwin Rony Sina; Meiton Boru; Marselina Elisabeth Soinbala
J-Icon : Jurnal Komputer dan Informatika Vol 7 No 1 (2019): Maret 2019
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v7i1.885

Abstract

Case Based Reasoning (CBR) method is one method to build a system with new case decision based on solution from previous cases by calculating similarity level. The calculation of similarity values ​​using the Cosinr Similarity with threshold 80%. This system can diagnose 3 diseases based on 23 existing symptoms.Based on the results of the test case obtained the results: the system can take back the old case is appropriate and has used the formulation of Naïve Bayes method to distribution of disease class and used the formulation of Cosine Similarity method to calculation correctly indicated with 100% accuracy, and use 122 cases. . Based on the test of 40 new cases obtained system accuracy of 80%.
IMPLEMENTASI PENETAPAN PAJAK KENDARAAN BERMOTOR UBAH BENTUK PADA SAMSAT KABUPATEN TIMOR TENGAH SELATAN Emerensye Sofia Yublina Pandie; Febryan Cornelis Lomi; Sebastianus Adi Santoso Mola
J-Icon : Jurnal Komputer dan Informatika Vol 7 No 1 (2019): Maret 2019
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v7i1.886

Abstract

The problem in doing the majoring in SAMSAT of sub-province of Timor Tengah Selatan can be solved by using information system. In a month SAMSAT of sub-province of Timor Tengah have served 3.131 taxpayer, that means for a day SAMSAT of sub-province of Timor Tengah served approximately reach 150 taxpayer and total vehicles in registration is 39.492 vehicles. The system that is developed to maintain vehicles data, types of vehicle data, vehicles brands data, dumps data, vehicles price data, registration data, and to count vehicles tax determining rightly dan quickly and can gain the report of all registration data, specific report of the vehicles, specific report of vehicles tax determining and receipt tax payments of vehicles transform. This system capable to answered the hypothesis H0 about contentment of service with satisfaction level more than 70% viz 78%.

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