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SINTECH (Science and Information Technology) Journal
Published by STMIK STIKOM Indonesia
ISSN : 25987305     EISSN : 25989642     DOI : -
Core Subject : Science,
Computer Science & IT
SINTECH (Science and Information Technology) Journal merupakan jurnal yang dikelola dan diterbitkan oleh Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK STIKOM Indonesia, dengan e-ISSN 2598-9642 dan p-ISSN: 2598-7305. SINTECH Journal diterbitkan pertama kali pada bulan April 2018 dan memiliki periode penerbitan sebanyak dua kali dalam setahun, yaitu pada bulan April dan Oktober. Bidang keilmuan dari SINTECH Journal mencakup bidang ilmu : Data analysis, Natural Language Processing, Artificial Intelligence, Neural Networks, Pattern Recognition, Image Processing, Genetic Algorithm, Bioinformatics/Biomedical Applications, Biometrical Application, Content-Based Multimedia Retrievals, Augmented Reality, Virtual Reality, Information System, Game Mobile, dan IT Bussiness Incubation.
Arjuna Subject : -
Articles 166 Documents
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SISTEM PENDUKUNG KEPUTUSAN PENERIMAAN KARYAWAN DENGAN METODE AHP TOPSIS (Studi Kasus: PT. Global Retailindo Pratama) Putu Praba Santika; I Putu Susila Handika
SINTECH (Science and Information Technology) Journal Vol. 2 No. 1 (2019): SINTECH Journal Edition April 2019
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v2i1.321

Abstract

To get good employees, a good selection process is needed. From the results of the interview, PT. Global Retailindo Pratama uses four criteria for the selection of new employees, education, intelligence, experience, and interviews. All prospective employees must take an exam to measure the criteria of education and intelligence and also have to send a photocopy of proof of their experience. The first stage selection is done to determine the prospective applicants who will take part in the interview. The second stage is conducted to determine the prospective employees who are accepted. The process of assessment and selection is still done by humans, so it takes a lot of time and energy. This problem can be solved by providing an information system for submitting applications and conducting examinations online. All documents are sent in digital form, also automaticlly checking answers from prospective employees. To select prospective employees, a method is needed that can recommend potential prospective employees based on specified criteria. The TOPSIS method is a decision support method that can provide recommendations in accordance with the criteria. The disadvantage of the TOPSIS method is that it requires weighting in the ranking process. The Analytical Hierarchy Process (AHP) method can be used to determine the criteria weight. Combining AHP and TOPSIS methods can produce more objective ranking results. Combining the AHP and TOPSIS methods can produce better recommendations.
KORELASI INDIKATOR PENILAIAN PEMERINGKATAN WEBSITE PERGURUAN TINGGI WEBOMETRICS DAN 4ICU Putu Andhika Kurniawijaya; Dewa Made Wiharta; Nyoman Putra Sastra
SINTECH (Science and Information Technology) Journal Vol. 2 No. 1 (2019): SINTECH Journal Edition April 2019
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v2i1.325

Abstract

Colleges in Indonesia as part of an educational institution that seeks to improve the competitiveness of globally through the utilization of ICT (information and communication technology) has been aware of the importance of the website as a key component of the assessment in an effort to align ourselves as a global standard of the College. The instruments most frequently used by universities as reference materials to evaluate performance and productivity based on his/her website is through a college assessor database world, including Webometrics and 4ICU. Correlation between linking Webometrics and 4ICU are aimed to assist colleges in analyzing the quality of traffic services in the field of scientific publications in order to be able to compete in the global sphere and certainly for the better. The methodology used by using spearman rank correlation against major # 29 University according to the webometrics ranking based on 4ICU and 29 top-rated website 4ICU. The results of the research there is a relationship or a significant correlation between the webometrics ranking indicator with indicator correlation value 4ICU ranking of 0.591 contains the category strong enough.
PREDIKSI PRODUKTIVITAS JAGUNG DI INDONESIA SEBAGAI UPAYA ANTISIPASI IMPOR MENGGUNAKAN JARINGAN SARAF TIRUAN BACKPROPAGATION Anjar Wanto
SINTECH (Science and Information Technology) Journal Vol. 2 No. 1 (2019): SINTECH Journal Edition April 2019
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v2i1.355

Abstract

Corn is a staple food that is still widely consumed by the population of Indonesia. Based on data from the Indonesian Statistics Agency, corn productivity in Indonesia from 2005 to 2015 calculated an unstable curve. Therefore this research was conducted to predict and see the large growth of maize in Indonesia for the following years so that the government has a reference to continuously strive to increase corn productivity in Indonesia in order to remain stable in order to meet the needs of Indonesian people to minimize corn imports. This study uses data on corn productivity in Indonesia in 2005-2015 sourced from the Indonesian Central Bureau of Statistics. The prediction algorithm used is the Backpropagation Neural Network. This algorithm is able to predict data well, especially data that is maintained for a certain period of time. To facilitate data analysis, the author uses the Matlab 2011b application. In this study, a training and testing process will be carried out using 5 network architecture models, namely 5-25-1, 5-43-1, 5-76-1, 5-78-1 and 7-128-1. Of the 5 architectural models, the best is 5-25-1 with the percentage of 88% and the MSE value of 0.00992433.
RANCANG BANGUN SISTEM REKOMENDASI DESTINASI WISATA DI BALI Dwi Putra Githa; Desy Purnami Singgih Putri
SINTECH (Science and Information Technology) Journal Vol. 2 No. 2 (2019): SINTECH Journal Edition October 2019
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v2i2.388

Abstract

Bali is one of the provinces in Indonesia which is famous for its tourism. Bali is visited by many tourists both local and foreign tourists because it is famous for its culture and natural beauty. The problem experienced by tourists is the difficulty in determining the tourism objects to be visited in accordance with the wishes of these tourists. Difficulty in determining tourism objects is caused by limited information about tourism objects in Bali. The tourist destination recommendation system in Bali can be a solution to provide information about tourism objects in Bali and can provide recommendations on tourism objects to be visited according to the criteria entered by the user. This system is a geographic information system that can provide location information and routes to tourism objects chosen by users. This system is created using the concept of mobile web, so that each device is able to use the system only with a web browser. This system was built using the PHP programming language and MySQL database. Based on the tests that have been done, the system has been running according to its function.
ANALISIS DAN DESAIN APLIKASI PEMBELAJARAN METAMORFOSIS KUPU-KUPU BERBASIS AUGMENTED REALITY Fitria Ningsih; Lili Rusdiana; Rudini
SINTECH (Science and Information Technology) Journal Vol. 2 No. 2 (2019): SINTECH Journal Edition October 2019
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v2i2.390

Abstract

Augmented Reality is one of technology that combines virtual world objects with the real world that allows it to be applied to Android-based smartphones because its users have penetrated into the realm of children. The need for analysis and design before building applications that later can help facilitate teachers in learning by displaying 3D objects and animations that make Students more interested in paying attention to the material provided and becoming more active in participating in the learning process. The purpose of this study is to analyze and design learning applications for Butterfly metamorphosis using Augmented Reality as an alternative learning media. Methods of collecting data are literature, observation, and interviews. The results of this study are in the form of application design regarding the metamorphosis phase of Butterflies ranging from caterpillars, larvae, pupae, to cocoons.
PENGEMBANGAN SISTEM PENDUKUNG KEPUTUSAN PENENTUAN PRIORITAS PEMBERIAN BANTUAN BIMTEK KEPADA INDUSTRI KECIL DAN MENENGAH (IKM) DENGAN METODE ANALITYCAL HIERARCHY PROCESS (AHP) DAN SIMPLE ADDITIVE WEIGHTING (SAW) Komang Sudana Yasa Pande; Made Windu Antara Kesiman; Gede Aditra Pradnyana
SINTECH (Science and Information Technology) Journal Vol. 3 No. 1 (2020): SINTECH Journal Edition April 2020
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v3i1.391

Abstract

The Buleleng Regency's Office of Trade and Industry has one of the tasks to develop and empower Small and Medium Industries (IKM) in Buleleng. One of the ways undertaken by the agency is to provide assistance to Bimtek entrepreneurship training or Technical Guidance. Bimtek is technical guidance assistance from government programs to improving and developing small and medium industries. However, sometimes this assistance is inconsistent because decisions are often changed. For this reason a decision support system was developed using AHP and SAW methods with 8 criterias including: number of monthly production, average product prices, number of equipment owned, number of employees, length of business establishment, annual sales value, total annual raw material and distance to Buleleng Government Commerce and Industry Office. The system developed can help the Buleleng Government Commerce and Industry to determine bimtek beneficiaries according to predetermined criterias. The development of this decision support system was built using the SDLC Method with a waterfall model. There are 4 tests performed including: blackbox testing, whitebox testing, accuracy testing, and user response testing. This study successfully developed a decision support system after passing the blackbox test and the whitebox test. Accuracy test showed very good results with an accuracy rate of 86.67%. The user response test conducted on 4 users including: admin, staff, IKM support and the general public has a mean percentage of 92.3% which is in a very good range.
CASE-BASED REASONING PEMBERIAN REKOMENDASI PROFESI BERDASARKAN MINAT DAN BAKAT SISWA MENGGUNAKAN SIMPLE MATCHING COEFFICIENT SIMILARITY Made Hanindia Prami Swari; Rahel Widya Arianti; Faisal Muttaqin
SINTECH (Science and Information Technology) Journal Vol. 3 No. 1 (2020): SINTECH Journal Edition April 2020
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v3i1.505

Abstract

One of the applications of technology in psychology is a system for determination of interest and talent systems. The system of determining interests and talents in this case can be applied in determining professional recommendations based on the interests and talents of a high school student who will continue to lectures or jobs in accordance with their fields. A person's interests and talents can be known from habits, preferences and hobbies. The Case-based Reasoning system created in this study uses cases from respondents which is collected using a questionnaire containing some questions about a person's interest in. To match new cases with old cases stored on a case basis, the authors use the Simple Matching Coefficient similarity method. The system will recommend a suitable work after the user inputs his preferences and habits. based on the results of the tests conducted, it was found that the system had produced the same calculation between the values generated by the system and manual calculations. While based on testing that conducted on data test, it was found that the system was able to provide an accuracy value of 83.33%.
PENGEMBANGAN SISTEM CERDAS UNTUK PREDIKSI DAFTAR KEMBALI MAHASISWA BARU DENGAN METODE NAIVE BAYES (STUDI KASUS: UNIVERSITAS PENDIDIKAN GANESHA) Komang Aditya Pratama; Gede Aditra Pradnyana; I Ketut Resika Arthana
SINTECH (Science and Information Technology) Journal Vol. 3 No. 1 (2020): SINTECH Journal Edition April 2020
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v3i1.523

Abstract

Ganesha University of Education or Undiksha is one of the state universities in Bali, precisely in the city of Singaraja. In the admission of new students, Undiksha applies 3 admissions paths, as follows the State University National Admission Selection (SNMPTN), State University Joint Entrance Test (SBMPTN), and Independent Entrance Test (SMBJM) consisting of 2 parts namely Computer Based Test (CBT) and Interests and Talents. Each year the committees are busy with the re-registration of prospective students. In determining the number of students quota for re-registration, they are still using the manual method in form of an excel file, so they want to use a system to do the process. These problems can be overcome by using “Intelligent System for Re-Registration of New Students Prediction using the Naive Bayes Method (Case Study: Ganesha University of Education)”. The Naive Bayes method is used to determine the re-register probability of the new students so that the number of students who re-register can be determining the new students quota. In developing the system, the researcher use the CRISP-DM methodology as a standard of data mining process as well as a research method. The results of this prediction system research show that the system can predict well with the average predictive system accuracy value of 75.56%.
PERBAIKAN KONTRAS CITRA MAMMOGRAM PADA KLASIFIKASI KANKER PAYUDARA BERDASARKAN FITUR GRAY-LEVEL CO-OCCURRENCE MATRIX Febri Liantoni; Agus Santoso
SINTECH (Science and Information Technology) Journal Vol. 3 No. 1 (2020): SINTECH Journal Edition April 2020
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v3i1.528

Abstract

In this era to recognize breast tumors can be based on mammogram images. This method will expedite the process of recognition and classification of breast cancer. This research was conducted classification techniques of breast cancer using mammogram images. The proposed model targets classification studies for cases of malignant, and benign cancer. The research consisted of five main stages, preprocessing, histogram equalization, convolution, feature extraction, and classification. For preprocessing cropping the image using region of interest (ROI), for convolution, median filter and histogram equalization are used to improve image quality. Feature extraction using Gray-Level Co-Occurrence Matrix (GLCM) with 5 features, entropy, correlation, contrast, homogeneity, and variance. The final step is the classification using Radial Basis Function Neural Network (RBFNN) and Support Vector Machine (SVM). Based on the hypotheses that have been tested and discussed, the accuracy for RBFNN is 86.27%, while the accuracy for SVM is 84.31%. This shows that the RBFNN method is better than SVM in distinguishing types of breast cancer. These results prove the process of improving image construction using histogram equalization and the median filter is useful in the classification process.
PENERAPAN SISTEM INFORMASI PENJUALAN DENGAN PLATFORM E-COMMERCE PADA PERUSAHAAN DAERAH APOTEK SARI HUSADA DEMAK Arina Nur Syahputri; Dimas Aryo Anggoro
SINTECH (Science and Information Technology) Journal Vol. 3 No. 1 (2020): SINTECH Journal Edition April 2020
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v3i1.540

Abstract

Sari Husada Pharmacy is one of the regional companies engaged in drug sales in Demak Regency. The company prioritizes innovation in information technology to face globalization and modern business competition in the industrial era 4.0. Improved services are needed so they can add regular customers and provide comfort to the existence of e-commerce. E-commerce solutions will overcome the problem of some customers who do not easily reach the location of the pharmacy because the transaction activities do not have to be in one place and it is difficult to check the stock of the drug, so that information systems are made more effective and efficient. The method used uses SDLC application development, namely waterfall. This method consists of five sequences, including: analysis, design, coding, testing, and implementation. This information system is created using PHP programming with CodeIgniter, Javascript, CSS (Bootstrap) and Sublime Text frameworks and database management using PHPMyAdmin which is installed together in Xampp, Apache Web Server and MySQL. The testing technique uses Blackbox and User Acceptance Test (UAT). The results of calculations from the User Acceptance Test (UAT) is 85,4% determine that the information system is very good to implemented at Sari Husada Pharmacy.

Page 11 of 17 | Total Record : 166

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