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All Journal JIKSI (Jurnal Ilmu Komputer dan Sistem Informasi) Sistemasi: Jurnal Sistem Informasi Computatio : Journal of Computer Science and Information Systems Jurnal CoreIT Jurnal SOLMA SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan MIND (Multimedia Artificial Intelligent Networking Database) Journal Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Esensi Infokom: Jurnal Esensi Sistem Informasi dan Sistem Komputer Jurnal Indonesia Sosial Teknologi Jurnal Informatika: Jurnal Pengembangan IT KOMPUTASI Jurnal Serina Abdimas
Manatap Dolok Lauro, Manatap Dolok
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Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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PERANCANGAN DAN PEMBUATAN APLIKASI INVENTORY MANAGEMENT BERBASIS WEB PADA PT. X MENGGUNAKAN METODE EOQ(Economic Order Quantity) Reza Ghaudi Farhad; Ery Dewayani; Manatap Dolok Lauro
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 11 No. 1 (2023): 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.v11i1.24097

Abstract

Inventory is an activity that includes goods owned by a company with the intention of being sold within a certain business period, or inventories of goods that are still in construction or production processes, or inventories of raw materials awaiting use in a production process. PT. X is a company whose scope of business includes the distribution of communication equipment, accessories, electronic devices. PT. X itself sells several kinds of electronic products such as printers, cellphones, barcode scanners, computers, and others. Currently PT.X is carrying out data management of PT. X still enters data manually into Microsoft Excel, even reporting data for bookkeeping is still done manually. So it is very ineffective and data can be easily manipulated and if an error occurs in the storage on the device or the device is suddenly damaged, the data that has been collected can be lost. Web-based Inventory Management application at PT. X which will be made later aims to be a system that will assist in recording incoming and outgoing stock of goods. The process of making applications that are made using the waterfall method, with object-oriented design methods using the UML method, and the framework used uses the Laravel PHP framework.
PERANCANGAN APLIKASI PENGECEKAN DAN PEMESANAN LAPANGAN BASKET DI JAKARTA BERBASIS ANDROID Juan Elber Kristian; Zyad Rusdi; Manatap Dolok Lauro
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 11 No. 1 (2023): 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.v11i1.24125

Abstract

Basketball is one of the most popular sports today. The community loves playing basketball, especially among youths.That is one of the reasons why basketball offers chances to operate a basketball court leasing company. One of the requirements for beginning a basketball court leasing company is the high level of community involvement.If the desired basketball court has already been ordered, the prospective tenant will need to find another court, according to observations made with basketball court providers and field users. Another issue is that it is still difficult for prospective basketball court users to learn about the courts that are currently available. The field supplier also has challenges; for instance, they continue to manually record orders. As a result, the best way to address the issues at hand is to develop information technology, such as an Android-based basketball court checking and booking application, which would make it simpler for potential tenants to make field reservations and access data about schedules, locations, and court prices.It is believed that the application will help field service providers and renters make the field order procedure very effective. This application's development makes use of the Android Studio program and the MySQL database.
PEMBUATAN APLIKASI SALES FORCE AUTOMATION (SFA) BERBASIS MOBILE PADA PT NOVA TEKNOLOGI AWANI Ricky Soeputra; Zyad Rusdi; Manatap Dolok Lauro
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 11 No. 1 (2023): 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.v11i1.24126

Abstract

PT. Nova Technology is a company engaged in technology in several sections, such as Food and Beverage, Retail, and several others. So companies need an application that helps manage sales schedules. Therefore the purpose of making this application is to make it easier for the head of sales to arrange a schedule. And a feature to approve a quotation until there is a feature for tracking sales via GPS. In addition, there are several other supporting features, namely for registering brands and branches, viewing brand and branch data, making edits to brands and branches, and a feature to view a list of data lists owned by PT. Nova Technology Awani.
SISTEM PENDUKUNG KEPUTUSAN DALAM PEMILIHAN KARYAWAN TERBAIK DENGAN METODE SAW Axel Mikaya; Zyad Rusdi; Manatap Dolok Lauro
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 11 No. 1 (2023): 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.v11i1.24136

Abstract

This Finance company works in providing financial solutions for Indonesian people. This company requires a decision support system in assessing the performance of employees in the company. The method is Simple Addictive Weighting (SAW). The SAW method is the solution to support the decision making of the system. Create a decision support system using the Simple Addictive Weighting (SAW) method to make it easier for this company to select the best employees on a certain period. Managers can set qualifications in determining the best employees. It becomes a tool in the decision support system.
PEMBUATAN APLIKASI SISTEM INFORMASI PENGELOLAAN KOMUNITAS KARUTA BERBASIS WEBSITE Jessica Henry; Ery Dewayani; Manatap Dolok Lauro
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 11 No. 1 (2023): 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.v11i1.24140

Abstract

The OKAKURA karuta community is a gathering place for Indonesians who are interested in the game. The karuta community has carried out and participated in activities such as karuta training, workshops, and inter-community tournaments. The Website-Based Karuta Community Management Information System Application was created to help Karuta community administrators manage internal data and community members view training results. The lack of management data in the Karuta community creates uncertainty among community members, resulting in ineffective training procedures and data redundancy. Furthermore, because exercise recording is still done manually, community members who are not present cannot view training histories. As a result, a Website-Based Karuta Community Management Information System Application was developed to aid in the recording and management of data as well as the search for training history. The System Development Life Cycle development method was used in the creation of this application (SDLC). The programming languages used are HTML, CSS, and PHP, with MySQL as the database and XAMPP as a local server, resulting in a website application that can assist Karuta community administrators in data processing and makes it easier for community members to view training history.
Dashboard Monitoring Penjualan Luckymart Nippon Paint Kennedy Stefano; Tony; Manatap Dolok Lauro
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 11 No. 2 (2023): 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.v11i2.25862

Abstract

Pada artikel ini, penulis merancang dashboard monitoring pada Luckymart Nippon Paint. Sistem Dashboard Monitoring dibangun untuk digunakan sehingga memudahkan pemilik toko dalam melakukan pemantauan terhadap penjualan yang disesuaikan dengan kebutuhan Luckymart. Cat merupakan produk yang digunakan untuk melindungi dan memberikan warna pada sebuah objek dengan melapisinya dengan lapisan berpigmen. Tujuan perancangan dashboard ini adalah menciptakan aplikasi monitoring dengan menggunakan dashboard pada sistem penjualan produk untuk mengatasi permasalahan pada proses penjualan produk pada Luckymart Nippon Paint. Data penjualan yang digunakan dalam perancangan dashboard monitoring adalah detail penjualan Luckymart dari bulan Januari hingga Desember tahun 2021. Rancangan desain dashboard menggunakan metode prototyping. Kemudian data yang sudah divisualisasikan tersebut dapat digunakan untuk mempermudah pengguna atau user dalam mengetahui detail dan informasi penjualan Luckymart berdasarkan produk, waktu, Interpriser, kategori produk, sub kategori produk serta laporan penjualan. Perancangan dashboard monitoring akan menggunakan business intelligence tools yakni Microsoft Power BI.
PERBANDINGAN KNN DAN SVM UNTUK KLASIFIKASI KUALITAS UDARA DI JAKARTA Bryan Valentino Jayadi; Teny Handhayani; Manatap Dolok Lauro
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 11 No. 2 (2023): 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.v11i2.26006

Abstract

The growth and economic development of a city is one of the factors causing air pollution because air quality has been mixed with various components of chemical compounds such as motor vehicle exhaust gases and factory smoke waste. Data mining is a method to find out information about air pollution in the city of Jakarta. The data mining method used is classification because this method can process air pollution standard index (AQI) parameter data into information that can show the level of air quality per day using the K-Nearest Neighbor algorithm and Support Vector Machine. The result of the application of data mining for air quality classification in Jakarta is that the Support Vector Machine algorithm has better accuracy performance compared to the K-Nearest Neighbor algorithm. The Support Vector Machine algorithm uses the RBF kernel and 100 kernel parameter gets an accuracy value of 98%, precission of 97%, recall of 97%, and F1-Score of 97% while the K-Nearest Neighbor algorithm uses the number of K as much as 6 gets an accuracy value of 96%, precission of 96%, recall of 93%, and F1-Score of 94%.
PREDIKSI HARGA PANGAN DI PASAR TRADISIONAL KOTA SURABAYA DENGAN METODE LSTM Teddy Ericko; Manatap Dolok Lauro; Teny Handhayani
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 11 No. 2 (2023): 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.v11i2.26012

Abstract

Long Short-Term Memory is the development of an artificial neural network that has the ability to overcome the vanishing gradient problem, and makes it possible to remember long-term information, and understand temporal patterns in time series data, so that LSTM has good performance in predicting food prices [1]. In Indonesia, especially in Surabaya, food prices are often unstable. Fluctuations in food prices can be caused by many factors such as weather, growing season and production. Under these conditions, this research was conducted to predict future food prices. The purpose of this study is to apply the LSTM method in predicting food prices so that it can provide maximum results and can be used by the community in making good decisions. In this study the dataset used included 5 types of food, namely rice, beef, chicken eggs, granulated sugar, and cooking oil. The dataset was obtained from the website of the National Strategic Food Price Information Center (PIHPS Nasional, https://www.bi.go.id/hargapangan). Predictive results are evaluated with RMSE and MAE. RMSE and MAE values of 5 types of food, namely rice 32 and 27, beef 229 and 125, chicken eggs 319 and 213, cooking oil 424 and 215, granulated sugar 30 and 18.
PREDIKSI HARGA PANGAN KOTA BANDUNG MENGGUNAKAN METODE GATED RECURRENT UNIT Matthew Oni; Manatap Dolok Lauro; Teny Handhayani
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 11 No. 2 (2023): 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.v11i2.26014

Abstract

Food problems often occur among the community, this occurs due to a lack of predictions made to determine future food prices. Food prices can be achieved if the government can provide sufficient food supplies both in terms of quality and quantity. The availability of sufficient food is an important factor in maintaining the health and welfare of the community. However, the high price fluctuations of staple foods in traditional markets have a negative impact on the availability and quality of food for the community, especially those with low incomes. This was caused by various factors such as rising raw material prices, the influence of weather factors, and changes in people's consumption patterns. In addition, the process of distribution and marketing of staple foods in traditional markets in Bandung City, which still relies on manual processes and is less structured, can also cause high price fluctuations. Therefore we need an application to predict staple food needs for the future accurately and effectively. This study uses the Gated Recurrent Unit method. This method is used because the Gated Recurrent Unit method has good performance in making predictions and fits the data used for this study. In this study, there were 5 types of commodities used, namely rice, chicken meat, chicken eggs, shallots, and garlic. All datasets used were taken from the website of the National Strategic Food Price Information (PIHPSNasional, https://www.bi.go.id/hargapangan). Predictive results by evaluating MAE and MAPE for rice 12.8, and 0.10, for chicken meat 12.8 , and 0.10, for chicken egg 244.5, and 0.64, for onion 296.9, and 1.05, for garlic 602.8, and 1.32.
PERBANDINGAN LSTM DAN ELM DALAM MEMPREDIKSI HARGA PANGAN KOTA TASIKMALAYA Andry Winata; Manatap Dolok Lauro; Teny Handhayani
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 11 No. 2 (2023): 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.v11i2.26015

Abstract

Humans have needs that must be met, one of which is the need for food, but food prices often change. Factors that affect price changes occur because the amount of demand is high while the supply is small. Making predictions about price changes will be very helpful to get an idea of the pattern of price changes. Therefore making predictions from price patterns is useful for providing information to the public. Predictions regarding price changes can be made using many methods. Long Short-Term Memory (LSTM) and Extreme Learning Machine (ELM) are several methods that can be used to predict time series data, these two methods can provide an overview of the predictions made. The results of the study show that both algorithms have good results in terms of the the evaluation value. The evaluation results showed no significant difference between the two algorithms. The evaluation value of the rice commodity showed that ELM tended to be better with MAE values of 6,721, MAPE 0.061%, MSE 115,281, RMSE 10,737 and CV 3,699%, while LSTM with MAE 31,707, MAPE 0.286%, MSE 1927.633, RMSE 43.905 and CV 3.655%. However, for other commodities, LSTM can produce a better evaluation value.
Co-Authors Adrian Adrian Agus Toni Ahza Rafie Khalis Andrew Andrew Andrew Jhosua Andry Winata Angeline Alviona Meilyta Ariesta, Cindy Maharani Aryanatta Paramita Tiratana Aurelius Ondio Lamlo Axel Mikaya Bagus Mulyawan bagus Mulyawan Benhard, Benhard Billy Alexander Suherli Billy Marcelino Billy Wang Bryan Valentino Jayadi Chung, Cecillia David David David David Delya Delya Delya, Delya Desi Arisandi Destu Adiyanto Devi Ayu Permatasari Dyah Erni Herwindiati Dyah Erny Herwindiati Dyah Erny Herwindiati Edison, Hans Edric Aryanto Edwin Jayadi Edy Susanto Ericko, Teddy Ery Dewayani Febryan Valentino Tansen Ferdian Sugiarto Ferry Fernando Franky Wijaya Franky Yoga Gabriel Ivan Setyaputra Garneto Alvan Gozali, Carisha Puspa halim, philip bryan Handhayani@, Teny Hendrawan Cahyady Hugeng Hugeng Jacky jacky James Suryapranata Jayadi, Bryan Valentino Jeanny Pragantha Jeanny Pragantha Jessica Henry Jett Enrico Chandra Juan Elber Kristian Kelvin Kennedy Stefano Laksono Trisnantoro Lina Lioviani Gavrilla Lorico Salim Lucas Lucas Marvellino Matthew Oni Maulana Sandy Dermawan Mega Pertiwi Mulyono, Prisca Bebby Triola Angela Natalie, Cynthia Nicko Sebastian Noviandi Noviandi Oni, Matthew Puteri, Carissa Putri Oktariana Putri Shafira Reza Ghaudi Farhad Ricky Soeputra Shela Stephanie Wijaya Sugiarto Leo Surya Halim Susilo, Andri Teddy Ericko Tedja, Peter James Teny Handhayani Tony Tony Valentinus Vallian Viny Christanti M Wasino Wasino Wasino Winata, Andry Yanto Yanto Yosia Amadeus Ishak Zyad Rusdi Zyad Rusdi Zyad Rusdi