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Sinkron : Jurnal dan Penelitian Teknik Informatika
Published by Politeknik Ganesha Medan
ISSN : 2541044X     EISSN : 25412019     DOI : 10.33395/sinkron.v8i3.12656
Core Subject : Science,
Computer Science & IT
Scope of SinkrOns Scientific Discussion 1. Machine Learning 2. Cryptography 3. Steganography 4. Digital Image Processing 5. Networking 6. Security 7. Algorithm and Programming 8. Computer Vision 9. Troubleshooting 10. Internet and E-Commerce 11. Artificial Intelligence 12. Data Mining 13. Artificial Neural Network 14. Fuzzy Logic 15. Robotic
Arjuna Subject : Ilmu Komputer (semua kategori) - Visi Komputer dan Pengenalan Pola
Articles 1,196 Documents
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Penerapan K-Means Pada Nilai Input Produksi Industri Mikro Dan Kecil Menurut Provinsi Sumarno, Heny
Sinkron : jurnal dan penelitian teknik informatika Vol. 3 No. 1 (2018): SinkrOn Volume 3 Nomor 1, Periode Oktober 2018
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (472.852 KB)

Abstract

Industri Pengolahan adalah suatu kegiatan ekonomi yang melakukan kegiatan mengubah suatu barang dasar secara mekanis, kimia, atau dengan tangan sehingga menjadi barang jadi/setengah jadi, dan atau barang yang kurang nilainya menjadi barang yang lebih tinggi nilainya, dan sifatnya lebih dekat kepada pemakai akhir. Nilai Produksi Industri berkaitan dengan nilai tambah, nilai input dan nilai output. Penelitian ini mengambil data tentang nilai input produksi industri mikro dan kecil. Data yang digunakan dalam penelitian ini adalah data sekunder. Data sekunder yang digunakan adalah penggabungan dari deret waktu (time series) dari tahun 2013- 2015 dan deret lintang (cross section) sebanyak data provinsi di indonesia yang menghasilkan 34 observasi. Sumber data dalam penelitian ini diperoleh dari publikasi Badan Pusat Statistik (BPS). Penelitian ini menggunakan datamining dengan metode K-Means. Varibale yang digunakan (1) jumlah nilai input produksi mikro dan (2) jumlah nilai input produksi mikro. Data akan diolah dengan melakukan clustering dalam 3 cluster yaitu cluster produksi nilai input tinggi, cluster produksi nilai input tinggi sedang dan produksi nilai input tinggi rendah. Cetroid data untuk cluster produksi nilai input tinggi 87899515,0 dan 121258942,3, Cetroid data untuk cluster produksi nilai input sedang 10634113,8 dan 15356152,8 serta Cetroid data untuk cluster produksi nilai input rendah 3044143,6 dan 1507129,8. Sehingga diperoleh 3 provinsi cluster produksi nilai input tinggi, 9 provinsi cluster produksi nilai input sedang dan 22 cluster produksi nilai input rendah.
Sistem Layanan Antrian Dengan SMS Pada Unit Pelayanan Mahasiswa: Studi Kasus : AMIK Tunas Bangsa Pematangsiantar Lubis, Muhammad Ridwan
Sinkron : jurnal dan penelitian teknik informatika Vol. 1 No. 1 (2016): SinkrOn Oktober Volume 1 Edisi 1 Tahun 2016
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (242.434 KB)

Abstract

Sistem Layanan Antrian dengan SMS digunakan untuk memberikan kemudahan kepada Mahasiswa untuk menyelesaikan Masalah administrasi Akademik. Dengan menggunakan Aplikasi SMS Gateway dan Komputer Server maka setiap Mahasiswa yang mengirim SMS Antrian akan mendapatkan Nomor antrian dari Server. Aplikasi ini bertujuan untuk memberikan pelayanan terbaik kepada Mahasiswa dan Bagian Unit Pelayanan Mahasiswa dapat menjalankan tugas melayani mahasiswa dengan sangat baik
ANALISA PENGARUH KUALITAS WEBSITE PPDB TERHADAP KEPUASAN PENGGUNA Utami, Lilyani Asri; Ishaq, Ahmad; Maulidiyah, Nurul
SinkrOn Vol 3 No 1 (2018): SinkrOn Volume 3 Nomor 1, Periode Oktober 2018
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (26.75 KB) | DOI: 10.33395/sinkron.v3i1.10146

Abstract

Website Penerimaan Peserta Didik Baru (PPDB) memberikan kemudahan bagi orang tua dan calon peserta didik baru dalam mengetahui informasi mengenai pelaksanaan seleksi penerimaan peserta didik baru, melakukan pendaftaran serta melakukan pemantauan hasil seleksi karena dapat dengan mudah diakses melalui gadget atau perangkat lain yang terkoneksi dengan internet. Permasalahan yang diangkat dalam penelitian ini adalah apakah kualitas dari website PPDB berpengaruh terhadap kepuasan pengguna pada SMKN 57 Jakarta. Penelitian ini berfokus pada kepuasan pengguna website PPDB menggunakan metode webqual yang terdiri dari 3 variabel yaitu kualitas kegunaan (usability), kualitas informasi (information quality), dan kualitas interaksi (interaction quality). Data yang digunakan dalah data primer, yaitu dengan menyebar kuesioner menggunakan skala likert dengan 20 pernyataan kepada 95 responden. Data yang diperoleh dan diolah menggunakan teknik analisis regresi linier berganda dengan menggunakan software SPSS 16. Berdasarkan variabel webqual, hasil analisis menyatakan kualitas kegunaan tidak berpengaruh terhadap kepuasan pengguna, sedangkan kualitas informasi dan kualitas interaksi berpengaruh terhadap kepuasan pengguna
The Analysis of Adult Autism Spectrum Disorders Screening Using Neural Network Nurfalah, Ridan; Rahayu, Sri; Akbar, Muhammad Faittullah
Sinkron : jurnal dan penelitian teknik informatika Vol. 4 No. 1 (2019): SinkrOn Volume 4 Number 1, October 2019
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (874.302 KB) | DOI: 10.33395/sinkron.v4i1.10148

Abstract

One of the increasing developmental disorders in Indonesia is Autism Spectrum Disorder (ASD), developmental disorder characterized by difficulties to conduct verbal and non-verbal communication and social interaction. This disorder cannot be tolerated and requires early treatment to reduce its development. However, ASD treatments required ineffective treatment costs and waiting times diagnosis were lengthly. One effective alternative diagnosis isto use the screening technology to determine the early symptoms of ASD disorders. The rapid development of the number of ASD cases around the world required researchers to determine a dataset with behavioral properties to update the screening process. Thus, the purpose of this study is to predict the success of screening performed on adults with Autism Spectrum Disorder (ASD) using the researchers’ results dataset, so that the dataset could be used as a benchmark for the success of the ASD screening process. The method used is machine learning neural network method with 100 training cycle, learning rate 0,01 and momentum 0,9 resulted in a classification accuracy of 96.00%
Rancang Bangun “Asitorik” sebagai Media Pembelajaran Praktek Mahasiswa Akuntansi Asmoro, Wiwiek Kusumaning; Izzah, Abidatul
Sinkron : jurnal dan penelitian teknik informatika Vol. 3 No. 1 (2018): SinkrOn Volume 3 Nomor 1, Periode Oktober 2018
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1147.393 KB)

Abstract

Learning about ”Public Sector Accounting” is require skills in credit debit transaction theory, recording a ledger, to compiling reports. However, students and lecturers have difficulty in terms of time effectiveness in understanding concepts and evaluating assessments. Thus it takes an e-learning that can help students in understanding the flow of making Public Sector Accounting reports completely. Therefore in this study an accrual-based Public Sector Accounting Application was made in an effort to improve the ease of learning practice of accounting students. This app is built based on the web using the PHP programming language and mySQL database. Firstly, needs analysis has been conducted based on the learning process of Public Sector Accounting Practicum in Accounting Department of Politeknik Kediri. Then, the app has been successfully built and tested so students so that it can manipulate an account, journal, and transaction automatically. Finally, it also prints Ledger, Budget Realization Report, Report on Changes in Budget Balance, Balance Sheet, Operational Report, and Statement of Changes in Equity.
Optimizing Genetic Algorithms for Sentiment Analysis of Apple Product Reviews Using SVM Indrayuni, Elly; Nurhadi, Acmad
Sinkron : Jurnal dan Penelitian Teknik Informatika Vol 4 No 2 (2020): SinkrOn Volume 4 Number 2, April 2020
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (503.377 KB) | DOI: 10.33395/sinkron.v4i2.10549

Abstract

Online reviews have the potential to provide buyers with insights about products such as quality, performance and recommendations. Website is one of the media that contains information or reviews provided by individuals, groups or organizations about an object or topic, one of which is Apple products. This study analyzes consumer sentiment reviews of Apple product users consisting of 200 reviews which will be classified into positive opinions and negative opinions using the Support Vector Machine algorithm and the application of genetic algorithms (GA) to obtain optimal accuracy values. The stages of this research are, firstly collecting a dataset, the second is preprocessing data. Third, the sentiment analysis process uses SVM and GA as optimization techniques. Fourth, do the validation process on the accuracy results obtained using the Confusion Matrix and ROC Curve. The results of this study indicate that Apple product review sentiment analysis produces the best accuracy of 70.00% and AUC 0.924 for SVM algorithm. Whereas the SVM + GA algorithm produces 85.76% accuracy and AUC 0.945, so that the accuracy value increases by 15.76% and the AUC 0.021 on the SVM model when compared before optimization with genetic algorithms (GA) is performed
Performance Comparison of Data Mining Algorithm to Predict Approval of Credit Card Sugiyarto, Ipin; Sudarsono, Bibit; Faddillah, Umi
Sinkron : jurnal dan penelitian teknik informatika Vol. 4 No. 1 (2019): SinkrOn Volume 4 Number 1, October 2019
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (617.118 KB) | DOI: 10.33395/sinkron.v4i1.10181

Abstract

Credit analysis needs to identify and assess the factors that can affect customers in returning credit. Accurate measurement and good management ability in dealing with credit risk is an effort to save the economic operations unit and be beneficial for a stable and healthy financial system. Data mining prediction techniques are used to determine credit risk. Using the Cross-Industry Standard Process for Data Mining (CRISP-DM) method which consists of several stages, namely Business Understanding (dataset), Data Processing (Feature Selection PCA & Dimension Reduce), Algorithm Models (NN+PSO, SVM, LR), Evaluation (Validation and Accuracy). This study has tested the model using a neural network using the PCA selection feature and optimized with the Particle Swarm Optimize (PSO) algorithm to predict credit card approval. Several experiments were conducted to see the best results. The results of this study prove that the use of a single Neural Network method produces an accuracy of 80.33%. whereas the use of PCA + Neural Network + PSO hybrid method has been proven to increase accuracy to 82.67%. Likewise, the AUC NN value of 0.706 increased to 0.749 when the Neural Network was optimized using PSO and used feature selection. The purpose of this study is to implement and compare Support Vector Machine, Logistic Regression and Neural Network algorithms based on PCA and optimize PSO (Particle Swarm Optimization) to improve accuracy in predictions of credit card approvals.
Sistem Informasi Akademik Pada SMK Kesehatan VIA MEDIKA Ramadan, Rino
Sinkron : jurnal dan penelitian teknik informatika Vol. 3 No. 1 (2018): SinkrOn Volume 3 Nomor 1, Periode Oktober 2018
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (511.859 KB)

Abstract

Saat ini pengolahan data siswa, pengolahan data guru, pengolahan data kelas, pengolahan informasi nilai(raport), pengolahan jadwal mengajar, dan pengolahan data mata pelajaran di SMK Kesehatan Via Medika sebagian besar belum berjalan secara cepat dan tepat, seperti pencarian data siswa, data guru, data kelas, data nilai masih harus membuka lembaran-lembaran arsip di bagian kesiswaan maupun kurikulum, kertas pengumuman seperti jadwal mengajar dan hal penting lainnya telah memenuhi papan pengumuman sekolah, serta penghitungan nilai masih memakan waktu yang lama, dan belum ada aplikasi pendukung yang tepat, sehingga siswa siswi kurang mendapatkan informasi terbaru dari sekolah. Dengan dibuatnya sistem informasi akademik berbasis website diharapkan mampu meningkatkan kualitas serta kuantitas dalam bidang akademik maupun non akademik, karena dengan keberadaan sistem informasi berbasis website ini hampir semua informasi dapat diketahui masyarakat luas.
Dog Disease Expert System Using Certainty Factor Method Marlinda, Linda; Widiyawati, Widiyawati; Indrarti, Wahyu; Widiastuti, Reni
Sinkron : Jurnal dan Penelitian Teknik Informatika Vol 4 No 2 (2020): SinkrOn Volume 4 Number 2, April 2020
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (441.851 KB) | DOI: 10.33395/sinkron.v4i2.10538

Abstract

Many animal keepers at home who do not know the disease contained in the animal's body. Especially for dogs, the lack of information begins to provide care, hygiene, vaccinations for the health of pet dogs and sickles that will be caused by dogs to their owners. Expert systems can provide solutions to the lack of information obtained by pet dog owners, especially dogs. With this expert system, the owner can know the dog's disease and realize the right prevention in treatment. In this paper 25, physical symptoms of the disease are used and found 8 types of common dog diseases. Five options are given to answer the calculation question using each method: no, quite sure, sure enough, certain, and certainty sure. Accuracy Analysis of each method is tested by assessing the results of each analysis method based on user feedback. The results of this study are the application of an expert system that can diagnose dogs using herbal medicines from plants. The purpose of this study is to implement the certainty factor method in the diagnosis system of canine diseases that can provide space in providing value confidence in knowledge. The conclusion in this study will show some questions as indicators of the characteristics of canine disease, until the final question. The conclusion of the study using the certainty factor method will show the characteristics of the disease in dogs. By being obtained from Rabies (0.9) with easy to get angry refuse nomal food; Hepatitis (0,9) with swelling of the liver occurs; Distemser (0,8) with stomach part blister and festering discharge from the eye; canine parvorius (0,8) with loss of appetite and poop there is blood, herpesvirus (0,8) with often roared and complaints, papilomatosis (0,9) with Smelly dog breath, and leptospirosis (0,7) with complaints, and dirofilaria immitis (0,9) with Unstable body temperature
Analisis Matriks 5x7 Pada Kriptografi Playfair Cipher Azmi, Fadhillah; Anugrahwaty, Rina
Sinkron : jurnal dan penelitian teknik informatika Vol. 1 No. 2 (2017): SinkrOn Volume 1 Nomor 2 April 2017
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (188.104 KB)

Abstract

Kriptografi memiliki peran yang sangat penting di era digitalisasi yang mana bertujuan untuk mengamankan informasi. Informasi yang bersifat privasi dapat terhindar dari orang ketiga dan informasi yang akan disampaikan dapat dilindungi. Salah satu keamanan data yang ditawarkan dengan metode kriptografi playfair cipher yang mana sebelumnya telah dianalisa dengan menggunakan matriks 5x5, 7x4 dan 6x6. Tujuan dari penulisan ini untuk menganalisis matriks 5x7 pada metode kriptografi playfair cipher sejauh mana tingkat keamanan yang dapat diberikan dengan membandingkan hasil analisa yang telah dilakukan sebelumnya yaitu pada matriks 5x5, 7x4 dan 6x6.

Page 21 of 120 | Total Record : 1196

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