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All Journal JIKSI (Jurnal Ilmu Komputer dan Sistem Informasi) Computatio : Journal of Computer Science and Information Systems INFORMASI (Jurnal Informatika dan Sistem Informasi) Journal of Sustainable Community Development (JSCD)

bagus Mulyawan

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Author-ID : 470905

Humanities Computer Science & IT Economics, Econometrics & Finance Environmental Science Mathematics Social Sciences Other

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PERANCANGAN APLIKASI PENERIMAAN MAHASISWA BARU PADA UNIVERSITAS TARUMANAGARA BERBASIS WEB Theresia Cynthia Lay; Bagus Mulyawan
Jurnal Ilmu Komputer dan Sistem Informasi Vol 1, No 2 (2013): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v1i2.3157

Program aplikasi penerimaan mahasiswa baru berbasis web merupakan aplikasi yang dapat membantu proses penerimaan mahasiswa baru, yaitu mulai dari pendaftaran yang akan dilakukan secara on-line melalui internet dan ujian on-line melalui intranet. Tujuan dari pembuatan aplikasi adalah untuk mempermudah calon mahasiswa melakukan pendaftaran dan ujian saringan masuk di Universitas Tarumanagara. Prosedur perancangan menggunakan pendekatan System Development Life Cycle (SDLC) dengan metode Waterfall. Pengujian program aplikasi ini dilakukan dengan menggunakan metode Blackbox Testing dan User Acceptance Testing. Hasil dari pengujian ini adalah program aplikasi dapat berfungsi dengan baik, namun masih perlu penyesuaian dengan prosedur dan kebijakan yang berlaku di Universitas Tarumanagara. Kata KunciPenerimaan Mahasiswa Baru, System Development Life Cycle, Ujian On-line, Universitas Tarumanagara

SISTEM PENJUALAN PADA PD. SAHATI BERBASIS WEB MENGGUNAKAN METODE DOUBLE EXPONENTIAL SMOOTHING UNTUK PREDIKSI STOK DAN ALGORITMA APRIORI UNTUK REKOMENDASI PRODUK George Timotius Harefa; Bagus Mulyawan; Tri Sutrisno
Jurnal Ilmu Komputer dan Sistem Informasi Vol 7, No 2 (2019): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

PD. Sahati is a trading business that has been running since 2016. PD. Sahati has not utilized information technology effectively in its business activities. To avoid input errors, improve marketing and help with stock handling, a stock prediction sales system was made using the double exponential smoothing method and product recommendations using the a priori method.Data input for prediction is product sales data. Data used for predictions cannot be less than 3 months to maintain consistency in stock predictions. The test results from the double exponential smoothing method are indicated by the mean absolute error (MAE) and mean square error (MSE). The MAE value obtained is 0.375 and the MSE value obtained is 0.145. Data input for customer product recommendations in the form of customer transaction data are then searched for frequent itemsets based on customer transaction data and will be eliminated with a minimum value of support. The minimum support value is obtained from the number of transactions divided by 2. After that, the confidence percentage will be searched through the association rules table. The product that will be recommended later is a product that has a percentage of confidence above the minimum confidence value. The minimum value of confidence in the system is 70%.

PEMBUATAN APLIKASI CUSTOMER RELATIONSHIP MANAGEMENT BERBASIS WEB MENGGUNAKAN METODE K-MEANS Aryanatta Paramita Tiratana; Bagus Mulyawan; Manatap Dolok Lauro
Jurnal Ilmu Komputer dan Sistem Informasi Vol 7, No 2 (2019): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

PT. Sugi Jaya Mandiri is a company specializing as a vendor of industrial equipment. The company has issues in regard of sales data processing and customer service, where the company manually process. Another point to mention is the company's limitations regarding customer service, where customer's inquiries and/or consultations must be sent manually, either by phone or email, thus customers have virtually no channels in which to voice suggestions, critiques and/or complaints towards the company. Considering the company's substantial amount of customers, the current method proves ineffective to provide an adequate service for the customers. It is hoped to make it easier to process customer and sales transaction data, and improving relations between the company and the customers using the potential customer selection feature using the K-Means method. The data used for customer clustering is the company's sales transaction data covering one year time period, starting from 2017. From the clustering results, it could be shown that there is a group of potential customers, totalling four customers and non-potential customers totalling forty customers. Evaluation results using the Silhouette Coefficient method in figuring the potential customer and non-potential customer using K-Means method is 0.85.

OPINION MINING UNTUK ULASAN PRODUK DENGAN KLASIFIKASI NAIVE BAYES Albert Jeremy; Viny Christanti M; Bagus Mulyawan
Jurnal Ilmu Komputer dan Sistem Informasi Vol 6, No 1 (2018): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Nowadays, micro blogs have become the most used tools for users to share many things: from just updating things to telling their conditions or thoughts. Some popular micro blogs mostly used to give comments and opinions are facebook, instagram, and twitter. Twitter has 259 million active users each month as for January until April 2017. This made twitter one of the best micro blogs to know the most updated opinions.The system uses Naive Bayes Classification to classify opinions about smartphone and computer from twitter. The sentiments are divided to positive, neutral, and negative. After that, Confusion Matrix is used to evaluate the algorithm and count the accuracy. Naive Bayes Classification gives 77.7% accuracy for Unigram, 50.7% for Bigram, and 31.7% for Trigram

WEBSITE SISTEM INFORMASI PEMETAAN PARIWISATA KABUPATEN LEBAK, PROVINSI BANTEN Erica Yewinda; Ery Dewayani; Bagus Mulyawan
Jurnal Ilmu Komputer dan Sistem Informasi Vol 6, No 1 (2018): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Lebak Regency has a variety of natural attractions are exotic, interesting, and need to be visited but in the delivery of information is still only in the form of books, giving brochures and website which explains natural tourism in short description only and map feature through google maps.The purpose of this website is made as an alternative to the promotion of tourist areas of Lebak Regency. In addition, it is expected to facilitate the public and the tourists in getting information about nature tourism in Lebak Regency. The method used in data collection is the method of observation and interview method. Software development method used is System Development Life Cycle (SDLC) and programming language used is PHP and to manage database using PhpMyAdmin.The result of making this website is to use this website easily and natural tourism information presented are complete.

APLIKASI E-COMMERCE BERBASIS WEB MENGGUNAKAN METODE WEIGHTED MOVING AVERAGE DAN K-MEDOIDS Arthian Terry Sammatha Sudarthio; Bagus Mulyawan; Darius Andana Haris
Jurnal Ilmu Komputer dan Sistem Informasi Vol 8, No 1 (2020): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Sugi Jaya Mandiri, Ltd. is a company specializing in sales of industrial equipments, such as cables, pipes, construction materials, machine spareparts et cetera. The company processes data manually by using Microsoft Excel. The process complicates data recapitulation, especially concerning large amounts of data. Another issue is the lack of advertising towards customer. This application aims to solve the problems by implementing data processing feature with Weighted Moving Average timeseries method and favourite product feature to better market products to prospective customers using k-Medoids clustering method.Preliminary evaluations using k-Medoids method shows two products fit to advertise by considering attributes such as sold amount, mean sold amount and transaction amount. Data evaluation using Weighted Moving Average method acquires sales forecast with Accuracy rate of 92.456%.

PEMILIHAN PEMASOK BAHAN MENTAH PADA RESTORAN CHANG THIEN HAKKA KITCHEN MENGGUNAKAN METODE AHP DAN TOPSIS Victor Victor; Dedi Trisnawarman; Bagus Mulyawan
Jurnal Ilmu Komputer dan Sistem Informasi Vol 3, No 2 (2015): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v3i2.3329

In this globalization era, technology plays a significant role in human’s life. Many systems have been developed to help people work efficiently and to reduce human error. Nowadays, decision making is one of the most important things in companies. Making the right decision may affect company’s profit and success.In this thesis, a research is made to help Chang Thien Hakka Kitchen Restaurant in choosing the best supplier effectively and efficiently. In many restaurants, production process is a very important process in the continuous growth and profitability of the restaurants. The effectiveness and efficiency of production process is determined by many factors such as availability of raw materials, quality of raw materials, price of raw materials, and so on. In this thesis, Chang Thien Hakka Kitchen Restaurant is using 6 criteria in determining the best supplier such as price of raw material, quality of raw material, suppliers’ location, supply management, suppliers’ flexibility, suppliers’ service.Therefore, it is very crucial to choose the best supplier of raw materials for the restaurant.Through this research, it is known that currently Chang Thien Hakka Kitchen Restaurant still chooses its supplier manually. In this thesis, a decision support system for Chang Thien Hakka Kitchen Restaurant is developed using a combination of Analytical Hierarchy Process (AHP) and Technique for Others Performance by Similarity to Ideal Solution (TOPSIS) where the criteria used in evaluating the best supplier is determined by the restaurant management. Then, the qualitative criteria are converted into quantitative data so that it can be measured objectively.At last, the program was tested by user and had the same result with the manual calculation (program error 0,002). Key word supplier, selection, method, AHP, TOPSIS, DSS

PERANCANGAN SISTEM PENGELOMPOKAN DAN REKOMENDASI SAHAM LQ45 DENGAN K-MEDOIDS, EXPONENTIAL MOVING AVERAGE DAN WEIGHTED PRODUCT Alvin Chandra; Bagus Mulyawan; Novario Jaya Perdana
Jurnal Ilmu Komputer dan Sistem Informasi Vol 9, No 1 (2021): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Stock is an instrumentation that has the fundamentalsof a company. Owning a share means owning theshares of the company. Shares can be traded on theIndonesian Stock Exchange by the entire public. TheLQ45 stock grouping and recommendation applicationis a desktop-based application that aims to assist inmaking investment decisions in the Indonesian CapitalMarket. The application is designed using the Pythonprogramming language. The application applies the KMedoidsClustering method to group stocks andExponential Moving Average along with WeightedProducts to make recommendations or sort shares.Users can enter the desired share criteria and theapplication will recommend according to the inputcriteria from the user. Testing on this application iscarried out by the BlackBox testing method,questionnaire, K-Medoids Algorithm Testing and theoutput results of the program. From the results of theblack box testing, the application results can runaccording to plan. In testing the K-Medoids Algorithm,the results obtained that the number of clustersdetermined are in accordance with the number of 2clusters using the elbow method. And in testing theoutput results of the program, the results obtained arethe recommendation accuracy of 80.8%.

PERBANDINGAN METODE TOPSIS DAN SIMPLE ADDITIVE WEIGHTING UNTUK REKOMENDASI PENENTU PENERIMA BEASISWA SMA DY Julio Yan Augusto; Bagus Mulyawan; Tri Sutrisno
Jurnal Ilmu Komputer dan Sistem Informasi Vol 7, No 1 (2019): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Aplikasi Perbandingan Metode TOPSIS dan Simple Additive Weighting untuk Rekomendasi Penentuan Penerima Beasiswa SMA DY merupakan aplikasi yang di buat bertujuan untuk memudahkan proses penentuan penerima beasiswa pada SMA DY melalui aplikasi web, yang dapat melakukan proses pengambilan keputusan berdasarkan kriteria-kriteria yang sudah ditentukan oleh pihak sekolah dengan memberikan masing-masing bobot presentase kriterianya. Aplikasi ini dirancang dengan menggunakan Bahasa pemrograman PHP. Metode perancangan aplikasi menggunakan System Development Life Cycle. Hasil pengujian dilakukan dengan metode User Acceptance Test. Dengan adanya aplikasi ini, diharapkan sekolah SMA DY dapat menentukan penerima beasiswa dengan tepat.

PERANCANGAN APLIKASI PREDIKSI MASA STUDI MAHASISWA DENGAN METODE NAÏVE BAYES DAN C4.5 Charles Yuliansen; Bagus Mulyawan; Novario Jaya Perdana
Jurnal Ilmu Komputer dan Sistem Informasi Vol 7, No 2 (2019): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

In college studies each study period uses a semester system where each semester of study period will obtain a Grade Point Average (GPA) in which the GPA shows the value obtained during the study period in that semester. With the right calculation the GPA can be used as a long time determinant of a student's study period. This prediction application is made using the classification method. The data used is obtained legally from the faculty and is used to carry out the training process and test applications that have been made. For the development method use the test structure method with several tools and workmanship techniques such as flowcharts, context diagrams, and relationships between tables. The programming language used in making applications is PHP, Python, the database used is MySQL. The training and testing methods used in making the application are Naïve Bayes and C4.5. The results of system testing show that using 237 student data obtained that the C4.5 method is always superior compared to the Naïve Bayes method. Addition of sex variables did not change the accuracy significantly.

Co-Authors Adrian Adrian Agus Toni Ahza Rafie Khalis Albert Jeremy Alvin Alvin Alvin Chandra Andy Wijaya Angga Saputra Arthian Terry Sammatha Sudarthio Aryanatta Paramita Tiratana Aurelius Ondio Lamlo Bryan Aprian Bryan Daniel Pinenda Pasaribu Caesha Rachma Dhani Calvin Alexander Chairisni Lubis Charles Yuliansen Chintia Yusnita Violetta Christian Yacobus Christopher Louis Fabian Daffa Salsabila Daniel Daniel Darius Andana Haris Dedi Trisnawarman Dedofin Dedofin Delya Delya Desi Arisandi Deza Farras Tsany Dhela Tria Afiyanti Diri Anindyah Qonita Dwi Putri Diri Anindyah Qonitah Dwi Putri Dodi Putra Edgar Lawrence Edwin Jayadi Edwin Suryaputra Eriana Retno Putri Eric Ang Eric Winata Jonathan Erica Yewinda Ery Dewayani Ery Dewayani Farenco Farenco Febryan Valentino Tansen Felix Kabonero Tanlimhuijaya Filbert Firdah Sholihah Frangky Selamat Franky Yoga Gabriel Ivan Setyaputra Garneto Alvan Gavrilla, Lioviani George Timotius Harefa Gian Ramanda Gladys Nathashya Tansen Hansenn Dustin Keane Hartanto Hartanto Helga Eva Julia Hendrawan Cahyady Hetty Karunia Tunjungsari Ita Nilasari Jane Syahwalina Kaprica Sandra Janson Hendryli Jeffrey Triguna Jonathan Putra Sugito Joshua Octavianus Joshua Saputra Julio Yan Augusto Kelvin Fernando Pinem Kelvin Kelvin Kevin kevin Kevin Marcello Jonathan Kevin Susanto Lely Hiryanto Lioviani Gavrilla Manatap Dolok Lauro Sitorus Manatap Dolok Lauro, Manatap Dolok Maulana Sandy Dermawan Meirista Wulandari Novario Jaya Perdana Peter Putra Nizar Aditya Putri Dewi Zabita Putri Oktariana Putri Shafira Rachmat Rachmat Raymond Raymond Rayvaldi Harvian Renaldy Cahya Reynold Adiputra Richard Rio Rio Sari Lalita Stefanus Alvin Hartono Stephanie Wijaya Sudono Widjaja Surono Surono Surya Halim Theresia Cynthia Lay TRI SUTRISNO Victor Victor Viny Christanti M Wimvy Nanda Tanius Wiratama Hadi Prananto Yenita Candra Sari Yongky Saputra

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