Application Design in Determining the Shortest Route Using Tabu Search Algorithm

This research designed a website application using Tabu Search Algorithm. We applied the Queuing method to find the shortest distance. Applications with this algorithm can provide the fastest route in the experiment of searching the shortest distance. We conducted this research by applying the examination in Rote Island, Indonesia. On the island, we examined the shortest distance from a starting point to another tourism place. In another side, this system utilized Google Map services to retrieve data about the distance between locations to another location with driving mode. The Google Maps service application is received in the form of translated JavaScript Object Notation (JSON), in order to be used as data and parameters in executing tabu search algorithms. The system was built using web-based through Hypertext Preprocessor (PHP) programming language, HyperText Markup Language (HTML), and Javascript, so it can be accessed and run by all devices that run the browser

Implementasi Sistem Pendukung Keputusan Pemilihan Lokasi Lahan Padi Sawah Tadah Hujan Menggunakan Metode Fuzzy Multi Attribute Decision Making (FMADM

Tujuan dari penelitian ini adalah membangun sistem pemilihan lokasi lahan sawah di Kabupaten Kupang Timur. Permasalahan tujuan penelitian adalah membuat sistem seleksi lokal lahan sawah di Kabupaten Kupang Timur. Hal itu menyebabkan petani di Kupang Timur kesulitan dalam menentukan lahan yang akan digunakan untuk menanam padi jenis ini. Sedangkan di wilayah Kupang Timur, pemilihan jenis lahan tetap dilakukan tanpa mengecek kesuburan tanah atau kondisi tanah. Dengan demikian, informasi pendukung keputusan untuk mendefinisikan sawah juga tidak akurat dan membuat petani di Kupang Timur terancam gagal panen. Oleh karena itu, penelitian ini menggunakan sistem pengambilan keputusan fuzzy multi-attribute decision-making (FMADM), yang memiliki 13 alternatif dan 7 kriteria, dimana nilai preferensinya adalah suhu 20%, curah hujan 20%, kelembaban 20%, drainase 13%, tekstur tanah. 13%, kedalaman tanah 7% dan pH H₂O 7%. Data lahan sebanyak 60 orang petani digunakan sebagai data uji untuk perhitungan dan diperoleh persentase tertinggi dari opsi terpilih yaitu lahan Cristovel Ullu dengan kode opsi Desa Oesao yang memiliki hasil tertinggi sebesar 0,966. Hasil pengujian UAT dilakukan terhadap 9 responden dengan total 5 pertanyaan untuk mengetahui kepuasan responden terhadap kegunaan fungsi, kesesuaian antarmuka sistem dan informasi yang disediakan oleh system dan hasilnya adalah 90,212 %

DATA MINING UNTUK KLASIFIKASI STATUS GIZI DESA DI KABUPATEN MALAKA MENGGUNAKAN METODE K-NEAREST NEIGHBOR

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%

PEMILIHAN LAPTOP ATAU NOTEBOOK DENGAN METODE FUZZY MAMDANI DAN SKORING

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

Kajian Machine Learning dengan Komparasi Klasifikasi Prediksi Dataset Tenaga Kerja Non-aktif

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

Penerapan Metode Fuzzy Service Quality (Servqual) untuk Menganalisa Kepuasan Pelayanan Pendidikan pada Jurusan Ilmu Komputer Fakultas Sains dan Teknik Universitas Nusa Cendana

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

DATA MINING UNTUK KLASIFIKASI STATUS GIZI DESA DI KABUPATEN MALAKA MENGGUNAKAN METODE K-NEAREST NEIGHBOR

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 AUDIT MUTU INTERNAL (SI AMI) PERGURUAN TINGGI MENGGUNAKAN METODE USER CENTERED LEARNING

Tujuan dari penelitian ini adalah untuk mengimplementasikan metode User Centered Design (UCD) dalam membangun sebuah Sistem Informasi Audit Mutu Internal (SIAMI) Perguruan Tinggi. Terdapat dua skenario pengujian yang telah dilakukan dalam penelitian ini yaitu: pengujian black box dan pengukuran tingkat kepuasan terhadap sistem menggunakan quesioner. Pengujian black box dilakukan dengan menguji semua fungsi fitur dalam sistem dan hasilnya sistem 95% berfungsi dengan baik. Sedangkan untuk pengujian tingkat kepuasan pengguna terhadap sistem menunjukan bahwa SIAMI dengan metode UCD dapat digunakan karena memiliki tingkat kepuasan sebesar 87%. The purpose of this study is to implement the User Centered Learning (UCD) method in building a Higher Education Internal Quality Audit Information System (SIAMI). There are two test scenarios that have been carried out in this research, namely: black box testing and measuring the level of satisfaction with the system using a questionnaire. Black box testing is done by testing all the function features in the system and the system results in 95% functioning properly. As for testing the level of user satisfaction with the system shows that SIAMI with UCD method can be used because it has a satisfaction level of 87%

Implementation of Apriori Algorithm for Sales Data Analysis (Case Study: Toko Ud. Suryani)

Transaction data owned by a store or supermarket every day is sure to increase, but it is often found that the transaction data is just stored and notused. This is what happened at the UD. Suryani store, where the existing transaction data has not been used properly, even though the collection of transaction data has the potential for information that can be processed to produce useful new knowledge. This transaction data processing can be done with data mining techniques. One of the data-mining techniques that can be used is the association rule method. One of the data retrievalalgorithms with association rules is the Apriori algorithm. This algorithm serves to determine the association relationship of a combination of itemsand is suitable to be applied when there are several item relationships to be analyzed. The purpose of this research is to apply data mining to the transaction data for the last one year in the UD. Suryani store. The data mining processing process is carried out with the rapidminer application and from nine trials with different combinations of minimum support and minimum confidence values for 13,490 transaction data, the results obtained are that the item most purchased by consumers is the Masako Sapi Renteng 10g with a support value of 14,5% and for items that are often purchasedtogether, if you buy Eggs and Blue Band 200g, you will buy Kompas Kemasan 1kg, with the highest confidence value of 66.5%