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SemanTIK : Teknik Informasi

semantik
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Published by Universitas Halu Oleo

ISSN : 24601446 EISSN : 25028928 DOI : http://dx.doi.org/10.55679/semantik.v8i1

Core Subject : Science, Engineering,

Computer Science & IT Control & Systems Engineering

Jurnal "semanTIK" merupakan salah satu media publikasi hasil-hasil penelitian dalam bidang teknologi informasi. Kajian penelitian dalam jurnal yaitu Rekayasa Perangkat Lunak, Jaringan Komputer, Sistem Cerdas, Sistem Informasi dan Robotika. Sasaran dalam penerbitan jurnal ini adalah Dosen, Mahasiswa dan para Peneliti dalam bidang TI.

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Articles 22 Documents

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Search results for , issue "Vol 4, No 1 (2018): semanTIK" : 22 Documents clear

APLIKASI PENJADWALAN MENGGUNAKAN ALGORITMA WELCH POWELL (STUDI KASUS : SMA MUHAMMADIYAH KENDARI) Niarma Niarma; Bambang Pramono; LM Tajidun
semanTIK Vol 4, No 1 (2018): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Scheduling teaching and learning activities is a routine work performed by the Head of Curriculum Section each welcoming the new school year. The role of the Head of Curriculum Section in making the schedule of teaching and learning activities is very important and not easy because the schedule to be arranged consists of very much data. Based on the problems that exist in SMA Muhammadiyah kendari where the teacher chose the schedule of willingness to teach sendri. To assist the processing of subject schedules at SMA Muhammadiyah Kendari, it is necessary to have a scheduling information system using Welch Powell algorithm. Welch Powell algorithm is one of the methods used to solve optimization problems by performing staining based on the highest degree of Largest Degree Ordering or LDO nodes. The LDO method is considered appropriate for scheduling problems because it prioritizes the highest-level nodes that are connected by multiple patterns so they should take precedence for scheduling.By entering the necessary data, such as class data, subjects, teachers, time, school year, and willingness to teach. The system will generate lesson schedules based on teachers' willingness to teach and automatically schedule teachers who have not chosen a willingness to teach without clashing.Keywords— Welch Powell, Application, SchedulingDOI : 10.5281/zenodo.1343344

PENERAPAN OPERASI HIMPUNAN DAN FUNGSI AGREGASI PADA PERANCANGAN BASIS DATA ALUMNI UNIVERSITAS HALU OLEO Aswani Aswani; Natalis Ransi; Rahmat Ramadhan
semanTIK Vol 4, No 1 (2018): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Halu Oleo University is building an integrated university database with a centralized database system. One of the data that is integrated is the alumni database. The alumni database can be designed using a relational database system. According to [1] the relational database can be an alternative because it has the advantage of storage capacity. Some basic mathematical theories such as set operations can be used to design and develop a database. Furthermore, the agreement function can be used to retrieve information from a database. In this research will be done on the database design alumni of Halu Oleo University by applying the approach of set operation and aggregation function.Keywords— Set Operation, Aggregation Function, Alumni DatabaseDOI : 10.5281/zenodo.1343370

APLIKASI PENENTUAN MINAT STUDI SISWA MENGGUNAKAN METODE SINGLE LINKAGE CLUSTERING (STUDI KASUS : SMK NEGERI 1 KENDARI) Nurfinasari Nurfinasari; Sutardi Sutardi; Mutmainnah Muchtar
semanTIK Vol 4, No 1 (2018): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

The process of determining the areas of interest (specialization) in Vocational Schools in Indonesia is organized to match the ability and interests of learners to the field of their choosing. SMK Negeri 1 Kendari is one of the institutions engaged in the field of education, especially vocational which stood under the auspices of Education Department of Kendari City and is located at Jl. Jend. A. Yani No. 17 Kota Kendari. This school has 4 majors that can be selected by students, among others: Accounting, Office Administration, Trade, Computer Engineering and Network (TKJ). The process of determining the program of expertise SMK Negeri 1 Kendari still using the manual way, if done by manual it will require extra precision because the data is quite a lot and has many weaknesses that allow errors in the process of majors. Therefore, proper classification of majors is required, one of them using technology in the field of data mining. In this research, single linkage clustering method is chosen, which is where the distance between clusters will get shorter time between clusters to achieve the final result and as media optimization in terms of facilitating the school in determining the majors of interest students. From the results of research and implementation note that the system can classify the data of student interest in SMKN 1 Kendari by using Single Linkage Clustering, Make it easier to clustering data by calculating the closest distance of each cluster object and student interest in SMKN 1 Kendari shows that 35.7 % Accounting and Finance, 28.6% Business and Marketing, 28.6% Office Management and 7.1% Computer & Network Engineering, from 438 student data.Keywords—Data Mining, Single Linkage Clustering, Interest in Studies DOI : 10.5281/zenodo.1402386

APLIKASI FORECASTING MENGENAI ANGKA KELAHIRAN DI KOTA KENDARI MENGGUNAKAN METODE REGRESI LINEAR BERGANDA (STUDI KASUS : DINAS KESEHATAN KOTA KENDARI) Nike Syafitri; Sutardi Sutardi; LM Tajidun
semanTIK Vol 4, No 1 (2018): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Birth rate is a very useful indicator not only of health status but also of overall population status, and the economic conditions in which the population lives. Population density in Kendari city in 2015 reached 1,174 people / km2. Population density in 10 sub-districts is quite diverse with the highest population density located in Kadia with the lowest density of 6,180 people / km2 in Baruga of 472 people/ km2. The purpose of this application is to predict the birth rate in Kendari by using multiple linear regression method.The Multiple Linear Regression Method is the most appropriate approach to predict future birth rates. An analysis that has more than one independent variable is called multiple linear regression analysis. The result of this system in the form of forecasting applications that can predict the birth rate in every month from all sub-districts in the Kendari and provide information about how strong the relationship between the factors that affect the birth rate.Keywords— Forecasting, Birth Rate, Multiple Linear Regression, Correlation DOI : 10.5281/zenodo.1402398

APLIKASI DATA MINING UNTUK PENILAIAN KREDIT MENGGUNAKAN DECISION TREE ALGORITMA ID3 STUDI KASUS PT. MANDALA MULTI FINANCE CABANG KENDARI Ilayani, Ilayani; Nangi, Jumadil; Pasrun, Yuwanda Purnamasari
semanTIK Vol 4, No 1 (2018): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2928.389 KB)

Credit is one of the most common payment mechanisms in the community. Data mining can search the pattern and new knowledge of these data so that it can facilitate in determination of debtor candidate. For that required a data mining applications that can process and provide the decision of the prospective debtor's eligibility status automatically. One method of data mining used for the classification of prospective borrowers is the decision tree using Iterative Algorithm Dichotomiser 3 (ID3).ID3 is one of the most popular types of Decision trees that attempt to build a decision tree top-down, starting with the first attribute to be checked and placed as root. The ID3 or Iterative Dichotomiser 3 algorithm is a method used to produce decision trees that are able to classify an object. Attributes used are file, job, character, address, pay slip, and motor price.Based on the test results, ID3 method can be implemented in credit appraisal application for the determination of eligibility with 100% accuracy value for 10 data testing from 100 training data and 30 data testing from 60 training data.Keywordsâ€”Credit, Data Mining, Decision Tree, ID3Â DOI :Â 10.5281/zenodo.1402830

APLIKASI ENKRIPSI DAN DEKRIPSI DATA MENGGUNAKAN TINY ENCRYPTION ALGORITHM (TEA) BERBASIS JAVA Liana Liana; Sutardi Sutardi; Nur Fajriah Muchlis
semanTIK Vol 4, No 1 (2018): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

The need for data security is increasing along with the development of digital technology. Almost all communication and transaction activities are now done digitally so that worries about missing data will increase. Data is very important, so accuracy and precision of data is needed in the decision-making process. The importance of the value of a data causes the availability of data security, therefore data falls precisely and accurately to the right partyIn this study designed a data security application. Encryption method is used to secure data by applying algorithm of Tiny Encryption Algorithm (TEA). In the encryption process performed 16 rounds where each round consists of; additions, key substitutions, and data, and XOR.The results of the study built a data security application that can secure data by applying the algorithm Tiny Encryption Algorithm (TEA). From the test results prove that application is able to secure extension txt and docx. The larger the size of the encrypted data the more time it takes for the encryption process. Keywords— Data, TEA, Encryption, Decryption DOI : 10.5281/zenodo.1402400

RANCANG BANGUN APLIKASI PERHITUNGAN RENCANA ANGGARAN BIAYA (RAB) PEMBANGUNAN RUMAH TINGGAL Muhammad Ridwan; Sutardi Sutardi; Bambang Pramono; Laode Muh. Golok Jaya
semanTIK Vol 4, No 1 (2018): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

The Budget Plan is one of the main processes in a project because it is the basis for creating a budget framework to be issued. The Budget Plan is indispensable for calculating a building or project with the many costs required for materials and wages, as well as other costs associated with building or project implementation. For that required a careful calculations of the total cost of manufacture, volume of work, type of work, material prices and wage handyman in accordance with Indonesian National Standard (SNI).The results of research that has been done is an application that can facilitate user activity to plan the cost of housing construction. With the menus contained in this application can help users to prepare for the needs of what is needed if you want to build a residence such as materials, wage handyman and the price of materials. In addition, it can reduce the level of human error in the calculation of cost analysis needsKeywords— Homes, Budget Plan, PHP Programming. DOI : 10.5281/zenodo.1402404

Penerapan Algoritma Backpropagation Dalam Memprediksi Produksi Tanaman Padi Sawah Menurut Kabupaten/Kota di Sumatera Utara Meychael Adi Putra Hutabarat; Muhammad Julham; Anjar Wanto
semanTIK Vol 4, No 1 (2018): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

North Sumatra Province is a province well known for its rice field production. But from all regencies and cities in North Sumatra, its rice production is uneven and unstable, sometimes its production goes up, sometimes down. Therefore, it is needed a research in the form of prediction for Production of Rice Field Crops, so that local government of North Sumatra can make policy as early as possible, so that production of paddy rice field can continue to rise in order to support the achievement of food self-sufficiency. In this study data that will be predicted sourced from the Central Bureau of Statistics of North Sumatra Province from 2012 until 2016. The algorithm used to make this prediction is the Backpropagation algorithm. This algorithm has the ability to remember and make generalizations of what has been there before. There are 5 architectural models used in this research, among others 3-5-1 which later will produce predictions with 78% accuracy rate, 3-7-1 = 70%, 3-10-1 = 82%, 3-15 -1 = 82% and 3-9-1 = 91%. The best architecture of the 5 models is 3-9-1 with 91% accuracy and error rate of 0.001-0.05. It is expected that the results of this study can contribute to the government in determining agricultural policy in the future.Keywords—Application, Backpropagation, Prediction, Production, RiceDOI : 10.5281/zenodo.1402832

RANCANG BANGUN DAN MONITORING ALAT JEMUR PAKAIAN BERBASIS WEB MENGGUNAKAN METODE NAIVE BAYES La Ode Ichsan Chumaidi; Isnawaty Isnawaty; Nur Fajriah Muchlis
semanTIK Vol 4, No 1 (2018): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Today's weather changes are unpredictable, caused by global warming. The dry season and the rainy season are unpredictable. Because it is human activity to dry clothes quite disturbed by the arrival of heat and rain are uncertain.The solution of the problem is an automatic drying tool, a clothes drying tool that can move in and out direction and into the home miniature automatically based on weather conditions and ambient light. The working principle of this automatic drying tool is using a switch controlled by a microcontroller that receives input values from three sensors. The value of the calculation of Naive Bayes will be classified into two categories namely drag and drying. At the time of rain classification value > no rain then the clothesline will move automatically into miniature house.This tool is controlled by microcontroller with three sensors namely DHT11 sensor, LDR (Light Dependent Resistor) and water sensor and has a DC motor output. This tool uses NodeMCU L298N is used to drive a DC motor and connect to the Web.Keywords—Automatic Drying Tool, Naive Bayes, Microcontroller, NodeMCU l298N. DOI : 10.5281/zenodo.1402834

Analisis Jaringan Saraf Tiruan Untuk Prediksi Luas Panen Biofarmaka di Indonesia Eko Hartato; Daniel Sitorus; Anjar Wanto
semanTIK Vol 4, No 1 (2018): semanTIK
Publisher : Informatics Engineering Department of Halu Oleo University

Analysis of a prediction is very important to do in a study, so that research becomes more precise and directed. Just as in predicting the extent of biopharmaceutical harvests in Indonesia, it is necessary to study and use appropriate methods to obtain optimal results. This research is expected to be widely used for both local government and biopharmaca farmers as one of the study materials in the development of biopharmaca harvest production, as well as for academics as research material especially related to agriculture and health. The data used in this research is the data of Harvested Area of Biopharmaceutical in Indonesia from National Bureau of Statistics from 2012 until 2016. This research uses the method of artificial neural network Backpropagation using 5 architectural models, namely: 3-3-1 later it will generate predictions with an accuracy rate of 80%, 3-4-1 = 87%, 3-5-1 = 73%, 3-6-1 = 60%, and 3-8-1 = 73% ,. So obtained the best architectural model using 3-4-1 model that yields an accuracy of 87%, MSE 0.062235528 with error rate used 0.001 to 0.05. Thus, this model is good enough to predict the area of biopharmaca harvest in IndonesiaKeywords—Analysis, Prediction, ANN, Backpropagation, BiopharmacaDOI : 10.5281/zenodo.1402402

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