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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) JIK Jurnal Ilmu Komputer JIKSI (Jurnal Ilmu Komputer dan Sistem Informasi) Seminar Nasional Informatika (SEMNASIF) Computatio : Journal of Computer Science and Information Systems Jurnal Ilmiah Universitas Batanghari Jambi INTECOMS: Journal of Information Technology and Computer Science ComTech: Computer, Mathematics and Engineering Applications Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer Jurnal Muara Sains, Teknologi, Kedokteran dan Ilmu Kesehatan Jurnal Bakti Masyarakat Indonesia Prosiding Seri Seminar Nasional

Dedi Trisnawarman

Universitas Tarumanagara

Author-ID : 405924

Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Social Sciences Other

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SISTEM PENUNJANG KEPUTUSAN UNTUK MENENTUKAN UKURAN OUTWEAR OTOMOTIF TOKO RON'S STORE MENGGUNAKAN METODE NAIVE BAYES Bryan Riyanto; Jap Tji Beng; Dedi Trisnawarman
Jurnal Ilmu Komputer dan Sistem Informasi Vol 7, No 2 (2019): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

The purpose of this research is to develop a decision support system to help determine the size of the outwear motorcycles in Ron's Store. The methods used in the writing of this thesis is the Naïve Bayes. The result is an application can perform the calculation to find the greatest probability that it can figure out a more appropriate size, applications running with XAMPP as Localhost and PHPMyadmin as the database. Based on the test results it can be concluded that the system can assist the customer in determining the size of the product which is more appropriate.

APLIKASI PREDIKSI STATUS REGISTRASI MAHASISWA BARU MENGGUNAKAN METODE NAÏVE BAYES DAN ALGORITMA C4.5 Simon Simon; Dedi Trisnawarman
Jurnal Ilmu Komputer dan Sistem Informasi Vol 2, No 2 (2014): 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.v2i2.3226

Universitas Tarumanagara merupakan salah satu perguruan tinggi swasta yang setiap tahunnya mengadakan penerimaan mahasiswa baru. Dengan itu sulit mengetahui apakah jumlah mahasiswa yang masuk dan melakukan registrasi ulang. Aplikasi ini bertujuan untuk membuat status prediksi untuk menentukan suatu kelas. Aplikasi prediksi status registrasi mahasiswa baru dibuat dengan menggunakan metode Naive Bayes dan algoritma C4.5. Metode Naive Bayes dan algoritma C4.5 adalah metode klasifikasi. Metode klasifikasi dapat digunakan untuk memprediksi dimana dia akan menggunakan data sebelumnya untuk menjadikan aturan-aturan yang akan dipakai di data yang akan diprediksi. Aplikasi ini dibuat untuk membantu Universitas Tarumanagara memprediksi jumlah mahasiswa baru yang akan melakukan registrasi, karena banyak calon mahasiswa yang lulus dalam ujian masuk tetapi tidak melakukan registrasi ulang. Selain itu aplikasi ini dibuat untuk membandingkan mana yang lebih baik ketepatannya antara metode Naïve Bayes dan algoritma C4.5. Dari hasil metode Naive Bayes mendapatkan ketepatan hasil prediksi berkisar 66% - 67.44% dengan 5 kali percobaan, sedangkan algoritma C4.5 mendapatkan ketepatan hasil prediksi berkisar 67.618% - 72.16%. Berdasarkan rata-rata 5 kali percobaan algoritma C4.5 memiliki ketepatan yang lebih tinggi. Key words Algoritma C4.5, Klasifikasi, Naive Bayes, Prediksi, Status Registrasi Mahasiswa Baru

Aplikasi Perencanaan Studi Mahasiswa Menggunakan Bayesian Belief Networks (Studi Kasus FTI Untar) Ferryanto Ferryanto; Lely Hiryanto; Dedi Trisnawarman
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.v1i2.3128

The application of student’s itinerary consists of two main part. The first part is recommendation. The recommendation uses bayesian belief networks to classify whether a student might pass or not if they took a certain course. The recommendation will give an alternative itinerary about information regarding which courses, lecturers, and classes to take. This is possible by mining data from previous students with similiar academic achievements. The last but not least part is detection. The function of detection is to detect which students are likely to drop out. This is done by calculating the average total points accumulated for each passing courses, then comparing it with provision of minimum accumulated points from the Faculty of Information Technology. The detection also involves calculation of the average accumulated points terms and comparation whether the students might graduate within the time limit based on the provision. The recommendation using bayesian belief networks proves to be useful by getting 91,24 % accuracy. The high accuracy is likely supported by considerate preprocessing methods and the relationship of each attribute from bayesian belief networks. The detection part is able to detect which students are likely to drop out, for the marked students are students that had drop out before and had a bad academic achievements. Key wordsBayesian belief networks, detection, drop out, recommendation, student’s itinerary.

SISTEM PENUNJANG KEPUTUSAN UNTUK MENENTUKAN PRIORITAS POTENSI DESA MENGGUNAKAN METODE SAW Anthony Honggo; Dedi Trisnawarman; Zyad Rusdi
Jurnal Ilmu Komputer dan Sistem Informasi Vol 6, No 2 (2018): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Sumbersari Village is a village that located in Moyudan district, Sleman, Daerah Istimewa Yogyakarta, Indonesia. Which is a combination of 3 urban villages in the region of Yogyakarta. Only few information that can be found about Sumbersari village, so the potential of Sumbersari village can not be promoted well. Decision Support System To Determine the Development Priority for Sumbersari Village Potential has a goal to assist village in deciding the potential to be developed.The method used for data collection is literature study and observation. Calculation method that is used in decision support system that will be made is Simple Additive Weighting and programming language used is PHP and database used is MySQL. The design of the application program produces a decision support system that can be used for sorting priorities that displayed in the form of reports and graphs.

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

SISTEM PENDUKUNG KEPUTUSAN BIBIT SAPI UNGGUL DENGAN METODE SIMPLE ADDITIVE WEIGHTING BERBASIS WEB Ivan Filbert; Dedi Trisnawarman; Zyad Rusdi
Jurnal Ilmu Komputer dan Sistem Informasi Vol 8, No 1 (2020): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

The purpose of this study is to develop a Decision Support System for Selection of superior beef cattle based on criteria with existing parameters. There are five criteria used in this study, namely Weight, Height, Age, Price, and Feed Consumption. These criteria were obtained from the results of interviews with Mutiara Halim Trading Business and a literature study that had been conducted. The method used is the Simple Additive Weighting (SAW) method. The result obtained is a Decision Support System that can be accessed by the Admin and User to select the desired cow. The program is run by using XAMPP as Localhost and PHPMyAdmin as Database. Based on the trials that have been carried out, it can be concluded that the system created can be run and can assist the User in making decisions to determine superior cow breeds

DASHBOARD PENGUKURAN KINERJA PROGRAM STUDI PERGURUAN TINGGI Oktovianus Irvan; Jap Tji Beng; Dedi Trisnawarman
Jurnal Ilmu Komputer dan Sistem Informasi Vol 8, No 1 (2020): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Dashboard is a tool that used for serving information in diagram model, visual indicator or graphic that make simply summary of information. Purpose of the thesis is to make an application for development dashboard that could used for measuring the performance of study program. Method that used is Extract, Transform, Load (ETL) and Method Software Engineering. ETL Method is importing the data to SQL SERVER and then transform it into a data master which easier to process to be a fact table data and ready to be the database master, and the software engineering method is a method Business Intelligence development derived from the method of software engineering is justification, planning, Business Analysis, Design, Construction, Deployment. The Result of dashboard design that can show and monitoring data of lecturers, employees, college student, research faculty, and completed research.

DASHBOARD INVENTORI PT. PETRA SEJAHTERA ABADI Diana Christian; Dedi Trisnawarman; Zyad Rusdi
Jurnal Ilmu Komputer dan Sistem Informasi Vol 7, No 2 (2019): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

The goal in making the Dashboard System Inventory PT. Petra Eternal Peace is to help cultivate the company's inventory data in the form of excel into the Dashboard. Methods of analysis and design using Prototype Requirements to find out the business activities and the needs of the user as manager in pt. Petra Eternal Peace. In making this Dashboard using several tools that are used like 2017 SQL server, SQL Server, Visual Studio Data Tools and Tableau 18.3. The result of the creation of this Inventory is a Dashboard helps managers in doing analysis and monitoring inventory more quickly and easily.

SISTEM PENUNJANG KEPUTUSAN PEMILIHAN KARYAWAN DENGAN MENGGUNAKAN ANALYTICAL HIERARCHY PROCESS Stevan Stevan; Dedi Trisnawarman; Tri Sutrisno
Jurnal Ilmu Komputer dan Sistem Informasi Vol 8, No 1 (2020): Jurnal Ilmu Komputer dan Sistem Informasi
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Decision support systems are made to facilitate users in determining a decision that will be made with the help of a system. The purpose of this study is to facilitate Porence owner in selecting prospective teachers who want to apply as a teacher at Porence. Porence is a course institution engaged in English education. Data collection for this system is collected by using interviews with Porence owner. This system uses the Analytical Hierarchy Process method to determine the decisions made. This system is implemented in the form of a website so as to facilitate program accessibility by using a common browser such as Google Chrome and Mozilla Firefox. The results of the Analytical Hierarchy Process-based Decision Support system are displayed directly to the Porence owner after the data entered has met the standard method used. The results of the decision support system can be used to provide recommendations to applicants who can be accepted and who will be considered.

PENERAPAN BAYESIAN BELIEF NETWORK UNTUK ANALISIS DATA KRIMINAL Rio Rio; Dedi Trisnawarman; Bagus Mulyawan
Jurnal Ilmu Komputer dan Sistem Informasi Vol 2, No 2 (2014): 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.v2i2.3222

Fokus utama dalam penelitian ini untuk membangun model bayesian terbaik dalam mencari profil kejahatan di Indonesia dengan mengunakan metode Bayesian Belief Network. Bayesian Belief Network atau biasa disbut Bayesian Network adalah model distribusi probabilitas gabungan yang digunakan untuk membantu dalam pengambilan keputusan pada keadaan yang tidak pasti. Bayesian Network ditampilkan dalam bentuh grafik yang merepresentasi suatu kumpulan variabel yang acak dan ketergantungan secara kondisional yang disebut directed acyclic graph(DAG). Dikarenakan Weka merupakan aplikasi pembelajaran mesin yang menyediakan berbagai algoritma untuk membantu dalam tugas penggalian data, seperti klasifikasi, regresi dan clusetering untuk tujuan penelitian, kami menggunakan Weka untuk membangun model DAG dengan menggunakan modul bayesnet classifier pada Weka yang berisi berbagai algoritma pencarian model seperti K2, Hillclimber, Tabu Search, Tree Augmented Naive Bayes dan lainya. Pencarian yang dilakukan dengan melakukan perbandingan algoritma pencarian untuk mencari model DAG dengan akurasi terbaik yang akan digunakan untuk pencarian profil kriminalitas di Indonesia. Setelah model DAG terbaik didapatkan, tahap selanjutnya adalah membuat rumus klasifikasi dari model DAG yang telah terbentuk sebelumnya. Algoritma pencarian terbaik yang dihasilkan Weka juga dibuat versi sendiri dengan tujuan sebagai pembanding dengan model yang telah dibentuk oleh Weka. Key words Bayesian Belief Networks, Data Mining, Neural Network, Weka, directed acyclic graph .

Co-Authors Aditya Tanuwijaya Afina Putri Dayanti Alexander Assisi Amalia Nurain Anthony Honggo Arfianto Panitra Arleine Arleine Bagus Mulyawan bagus Mulyawan Bryan Jordan Goh Bryan Riyanto Chairisni Lubis Cosmas Damianus Wijaya Cynthia Marcelina Cynthia Marcelina, Cynthia Cyrillus Damar Setyo Wardhana Dali Santun Naga Desi Arisandi Diana Christian Eddy Sutedjo Eddy Sutedjo, Eddy Edward Edward Elvandio Frinandy Ernestito Jovian Ery Dewayani Ferdinand Hartanto Ferdinand Hartanto Ferryanto Ferryanto Ferryanto Ferryanto Feryan Hadipurwanto Godeliva Vania Ekawardhani Helga Eva Julia Helga Eva Julia, Helga Eva Herison Halim Hizkia Aristyo Christianto Imam, Muhammad Choirul Ivan Filbert Jaceline Chan Janson Hendryli Jap Tji Beng Joseline Joseline Josh Louis Josua Marojahan Joycelin Joycelin Kelvin Julian Tannius Kenny Yan Lely Hiryanto Margaret Livereja Martin Johnsons Muhammad Choirul Imam Ni Putu Diah Ayu Vita Widia Murti Ni Putu Diah Ayu Vita Widia Murti, Ni Putu Diah Ayu Vita Widia Nizham Kamil Hia Novario Jaya Perdana Oktovianus Irvan Radot Regen, Radot Ricki Gozal Ricky Giovanni Putra Tanjaya Rio Rio Rio Sucitra, Rio Riva Audrey Robin Saputra Simon Simon Stefanus Simon, Stefanus Stephen Prihandana, Stephen Stevan Stevan Steven Federico Giovano Thomas Frederick Tony Tony Tony Tony Tri Sutrisno TRI SUTRISNO TRI SUTRISNO Utari Apriani Veronika Verrent Prischila Victor Femona Laoli Victor Victor Victor Victor Viny Christanti Wasino Wasino Zyad Rusdi Zyad Rusdi Zyad Rusdi

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