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Jurnal Informatika Kaputama (JIK)
Published by STMIK Kaputama Binjai
ISSN : 25489739     EISSN : 26855240     DOI : https://doi.org/10.59697/jik
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering
Jurnal Informatika Kaputama adalah jurnal resmi STMIK kaputama dalam bentuk bunga rampai untuk menyajikan tulisan ilmiah berbagai disiplin ilmu pengetahuan yang ada hubungan atau keterikatan dengan ilmu komputer berupa hasil penelitian lapangan atau laboratorium maupun studi pustaka. Adapun fokus dan ruang lingkup jurnal adalah sebagai berikut 1. Clustering and Classification 2. Document Mining and Text Mining 3. Spatial Data Mining, 4. Multi-Agent Systems, 5. Bayesian Networks and Probabilistic Reasoning, 6. Computational Intelligence, 7. Soft Computing, 8. Database Management and Information Retrieval, 9. Computer Vision Pattern Recognition, 10. Genetic Algorithm, Machine Learning, 11. Neural Networks and Applications, 12. Optimization and Decision Making, 13. Self-Organizing Systems, 14. Fuzzy Logic, 15. Decision Support and Expert System 16. Business Intelligence, 17. Data Mining Application 18. Intelligence System, 19. Web and mobile Intelligence 20. Dan lain-lain
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 386 Documents
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PERANCANGAN APLIKASI GAME 2D KILL GHOST MENGGUNAKAN UNITY Immanuel H G Manurung; Robert Kristianus Gea; Alexander F.K Sibero; Rianto Sitanggang
Jurnal Informatika Kaputama (JIK) Vol 7, No 1 (2023): Volume 7, Nomor 1, Januari 2023
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.1234/jik.v7i1.1349

Abstract

Game is one of the entertainment media that is in great demand by the community, from early childhood to adults. In general, games are divided into 7 (seven) types that are applied, namely, RTS (Real Time Strategy), FPS (First Person Shooter), RPG (Role Playing Game), Construction and Management Simulation Games, Vehicle Simulation, Action, Adventure and Fighting. Action games are a fighting game. This game was created using the C# programming language in the Unity game engine. In designing this game, the writer will implement an action game genre. The game has a two-dimensional appearance. Game testing is carried out using the blackbox method, as well as a user satisfaction survey. The test results show that the gameplay and features provided are interesting enough for an action game.
SISTEM INFORMASI DROPSHIP SI DROP MODEL PROTOTYPE PADA UMKM BINAAN PONTIANAK CREATIVE ASSOCIATION (PCA) Reza Maulana; Yoki Fimansya; Fajar Akbar Wirand
Jurnal Informatika Kaputama (JIK) Vol 7 No 1 (2023): Volume 7, Nomor 1, Januari 2023
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v7i1.1

Abstract

The need for goods has increased drastically, currently there are many online-based trade innovations or e-commerce which is a program created to make this easier. Pontianak Creative Association (PCA) really needs an information system that can support and facilitate coaching for MSME actors, and can open job opportunities for business actors who want to sell with minimal capital. Currently, Pontianak Creative Association (PCA) is only a creative industry association engaged in multimedia, design, animation, and MSME coaching. The existing system at the Pontianak Creative Association (PCA) is still carried out manually, starting from recording MSME data, to storing other data related to the coaching process, and there is no application of the coaching. The system is designed by applying a prototype model and using data collection methods in research. The information system is the best solution to solve the problems that exist in this association / institution, and with a computerized program, an effective and efficient coaching activity can be achieved in supporting coaching at this institution, and it is very possible that in the future this program can solve problems in MSMEs and for dropshipping actors who want to dropship products from MSMEs.
SISTEM INFORMASI PEMESANAN JASA FOTOGRAFI BERBASIS WEB Fitri Pratiwi; Pulla Pandika Widodo
Jurnal Informatika Kaputama (JIK) Vol 7 No 1 (2023): Volume 7, Nomor 1, Januari 2023
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v7i1.2

Abstract

Sistem pengelolaan data yang sedang berjalan pada casamia studio masih menggunakan sistem manual tulis tangan yang rentan terhadap berbagai kekeliruan yang menyebabkan kesalahan perhitungan, sulitnya dalam penentuan harga, kesulitan dalam pencarian data, serta kesulitan dalam mendapatkan laporan yang dibutuhkan. Tujuan dalam penelitian ini adalah agar dapat merancang sebuah sistem informasi berbasis web yang mudah digunakan. Dalam penulisan ini penulis merancang sistem informasi pada casamia studio yang memudahkan user untuk mengelola berbagai data jasa yang ada. Penulis juga menggunakan metode Waterfall untuk memenuhi kebutuhan penelitian ini. Sistem yang baru menghasilkan proses pemesanan online, penyimpanan data-data yang baik dan benar, dan dapat membuat laporan secara cepat dan tepat. Dengan adanya sistem informasi ini mampu membantu aktifitas green photography lebih efektif dan efisien dalam pengolahan data
Analisa Merancang Sistem Informasi Monitoring Perkembangan Proyek Riski Annisa; Firly Annisa Luthfi
Jurnal Informatika Kaputama (JIK) Vol 7 No 1 (2023): Volume 7, Nomor 1, Januari 2023
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v7i1.3

Abstract

PT. Permata Trikarya Utama adalah perusahaan yang bergerak pada bidang jasa konsultan Design Engineering dan Construction Management. Ditinjau dari sistem monitoring dan juga pengiriman laporan serta pengarsipan berkas laporan yang masih berjalan secara manual, menjadi permasalahan pokok yang perlu dibenahi di dalam perusahaan ini. Untuk memudahkan proses yang sedang berjalan saat ini, penulis mencoba membuat rancangan sistem yang berbasis web mengenai sistem monitoring pada PT. Permata Trikarya Utama. Perancangan sistem informasi ini menjadi solusi yang baik untuk membantu memecahkan permasalahan yang ada pada perusahaan. Dalam perancangan sistem monitoring ini menggunakan metode waterfall dengan tahapan yaitu analisa kebutuhan perangkat lunak, desain, implementasi dan pengujian. Dengan rancangan sistem monitoring yang dapat membuat dan mengarsipkan laporan, menampilkan schedule, serta mengelola data proyek serta karyawan, yang akan memudahkan perusahaan untuk mengelola data dan memonitoring perkembangan proyek serta mengarsipkan file yang ada. Sehingga perusahaan dapat lebih mudah dalam memonitoring perkembangan yang terjadi di dalam proyek serta pengarsipan file atau berkas perkembangan.
SISTEM PENDUKUNG KEPUTUSAN MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING (SAW) UNTUK PEMILIHAN MEKANIK TERBAIK PADA PT GEMILANG BERLIAN INDAH Herrianto Herrianto; Sulistianto Sutrisno Wanda
Jurnal Informatika Kaputama (JIK) Vol 7 No 1 (2023): Volume 7, Nomor 1, Januari 2023
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v7i1.4

Abstract

This study aims to analyze the application of a decision support system on the selection of the best mechanics at PT. Brilliant Beautiful Diamonds. In the assessment process for the selection of the best mechanic, there is no definite system in the assessment so that the process is not optimal and takes a long time. To overcome this problem, it is necessary to renew the existing mechanical selection system, one of the steps taken is to implement a decision support system. The analytical method used in this study is the Simple Additive Weighting (SAW) method which is a weighted summation method of performance ratings on each alternative on all attributes. There are several criteria taken from the selection of the best mechanics, namely Standard Operating Procedure (SOP), performance, responsibility, discipline, cooperation, and skills. The results of this study can be concluded that this system can be used as an auxiliary application for the best mechanical recommendations quickly and efficiently.
PENGELOMPOKKAN MAHASISWA POTENSIAL DROP OUT MENGGUNAKAN METODE CLUSTERING (STUDI KASUS : STMIK KAPUTAMA) Abdur Rahman; Langgeng Restuono; Adek Maulidya; Alex Siregar; Khairul Khairul; Rian Farta Wijaya
Jurnal Informatika Kaputama (JIK) Vol 7 No 1 (2023): Volume 7, Nomor 1, Januari 2023
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v7i1.5

Abstract

Drop out adalah keluar dari sekolah sebelum waktunya, atau sebelum lulus. Drop out demikian ini perlu dicegah,oleh karena hal demikian dipandang sebagai pemborosan bagi biaya yang sudah terlanjur dikeluarkan untuknya. Banyaknyapeserta didik yang drop out adalah indikasi rendahnya produktivitas pendidikan. Tingginya angka drop out juga bisamengganggu angka partisipasi pendidikan atau sekolah. Mahasiswa Drop Out adalah mahasiswa melebihi jangka waktu studidan atau melanggar ketentuan yang berlaku.Penggunaan Data Mining Clustering merupakan pengelompokan record, pengamatan, atau memperhatikan dalambentuk kelas objek – objek yang memiliki kemiripan yang satu dengan yang lainnya dan tidak memiliki rekord – record dalamkluster lain.Maka penulis merancang Data Mining Pengelompokan Mahasiswa Potensial Drop Out, karena sistem yang sedangberjalan pada STMIK Kaputama kurang baik. Hal ini memperlambat mengetahui data mahasiswa drop out.Dari hasil penelitian, hasil pengelompokan Group 1 dari 20 data terdapat sebanyak 5 Program Studi yaitu SI (S1),TI (S1), TI (D3), KA (D3), MI D3 yang terdapat pada STMIK Kaputama. Group 2 dari 20 data terdapat sebanyak 3 Jenis DropOut yaitu Keluar, Pindah, Cuti , Group 3 dari 20 data terdapat 5 Alasan Drop Out yaitu Tidak Mengikuti Kuliah 4 SemesterBerturut-turut, Kuliah Di Luar Kota, Terhambat Biaya, Bekerja , Sakit yang terdapat pada STMIK Kaputama.
THE APPLICATION OF THE TRIPLE EXPONENTIAL SMOOTHING METHOD IN THE PREDICTION OF WAREHOUSE INVENTORY Gusti Firanda; Rika Rosnelly
Jurnal Informatika Kaputama (JIK) Vol 7 No 1 (2023): Volume 7, Nomor 1, Januari 2023
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v7i1.6

Abstract

Prediction is an attempt to predict or predict something that will happen in the future by utilizing various relevant information in previous (historical) times through a scientific method. One of the applications of prediction in the business world is to predict future warehouse inventory based on the company's usage in the previous period. Prediction (Forecasting) is very helpful in planning and making decisions in an activity. Analysis is very important in learning, because research becomes more precise and focused. The problem faced by the company at this time is that the company has difficulty predicting warehouse inventory in the next period because there is no system that can be used by the company to predict. This predictive information will be very useful for companies in the process of planning clean water production to customers. In overcoming the problems mentioned above, a system is needed that can process data on goods that go in and out of the warehouse every period to get a prediction of warehouse inventory for the next period. To get optimal forecasting results, one method that can be used is the Triple Exponential Smoothing method. Triple Exponential Smoothing Method This method is a forecast method proposed by Brown, using quadratic equations .
USER USER EXPERIENCE TEST MARKETPLACE E-COMMERCE KOPI DENGAN MENGGUNAKAN ISO METRICS PADA UMKM DI ACEH TENGAH Desvina Yulisda; Rahma Fitria; Eka Susanti; Ebi Putra
Jurnal Informatika Kaputama (JIK) Vol 7 No 1 (2023): Volume 7, Nomor 1, Januari 2023
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v7i1.7

Abstract

E-commerce sites have become popular for sellers in promoting their business during the covid-19 pandemic. One of the e-commerce that is used in promoting business is shopee. . This e-commerce website is very often used by Indonesian people in selling goods. In order to make it easier for middle-range businesss to market their products on e-commerce shopee, this website needs to be tested by users to provide feedback on how the website feels after use. The purpose of this research is to test the user experience (UX) on e-commerce shopee as a seller. The UX test was carried out in a room set-up like in a laboratory with 10 users who have never used the Shopee website as sellers. During testing, users are given several tasks related to the website while the facilitator makes observations to analyze usability metrics. The data collected will reveal the weaknesses and strengths of the website. Usability score is measured based on ISO usability metrics including effectiveness, efficiency and satisfaction. The results of this UX test show that the website is quite user-friendly as evidenced by a usability score of around 84% or above average. It is expected that this research can be adopted by software engineers or usability testers to produce user-friendly e-commerce that makes users comfortable and easy to use the website.
PENGUKURAN KINERJA SUPPLY CHAIN CUMI-CUMI DI PPS NIZAM ZACHMAN BERDASARKAN MODEL MATURITY MENGGUNAKAN METODE SCOR Muhajirin Muhajirin; Novi Sofia Fitriasari; Ayang Armelita Rosalia
Jurnal Informatika Kaputama (JIK) Vol 7 No 1 (2023): Volume 7, Nomor 1, Januari 2023
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v7i1.8

Abstract

The supply chain system is an important factor in the commodity process or an effective and efficient logistics system. In the field of the fishing industry, the supply chain system greatly influences the process of activity flow starting from fish availability, productivity, fish quality assurance to distribution to consumers. Effective and efficient supply chain system management will have a huge impact on the commodities of the national fishing industry. Therefore, the purpose of this study is to measure the performance of the supply chain management systembased on the level of maturity so that it can be a benchmark as an improvement in the future. The approach method used in this study is to use the concept of the Supply Chain Operation Reference (SCOR) model which is collaborated with key performance indicators (KPI) andanalytical hierarchy processes (AHP) to produce the maturity value of supply chain performance. This research uses a descriptive method by making observations, distributing instruments in the form of questionnaires, interviews and literature studies in its preparation. The results of the study obtained a level of supply chain performance in PPSNZJ obtained a final value of 84.38 by entering the Good performance category based on the SCOR method and the supply chain maturity level obtained a maturity level of 4.3 on a scale of 0-5 with managed and measurable conditions. Efforts to measure supply chain performance are carried out to realize the improvement of supply chain performance in the national fishing industry which is integrated with suppliers, fishermen, companies, stakeholders and consumers.
KLASIFIKASI OPINI MASYARAKAT DI TWITTER TENTANG KEBOCORAN DATA YANG TERJADI DI INDONESIA MENGGUNAKAN ALGORITMA SVM Desi Arisandi; Tri Sutrisno; Iwan Kurniawan
Jurnal Informatika Kaputama (JIK) Vol 7 No 1 (2023): Volume 7, Nomor 1, Januari 2023
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v7i1.10

Abstract

Personal data is sensitive and private, it can only be seen by an individual. However, as time goes by, data leaks often occur on the internet, especially in Indonesia. This data leak was busy on Twitter social media and was used as a forum for opinions regarding data leaks that occurred in Indonesia. The classification method used for this research is Support Vector Machine (SVM) with TF-IDF feature extraction. The dataset was obtained through the results of scraping Twitter and getting 5000 tweets. The dataset is manually labeled as Positive, Negative, and Neutral before entering the SVM Classification stage. And based on the results of the SVM classification, SVM produces an accuracy of 83%.

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