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All Journal Semantik Jurnal Infra
Andreas Handojo
Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Kristen Petra Jl. Siwalankerto 121-131, Surabaya 60236, Indonesia
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Prediksi Kebutuhan Darah Menggunakan Metode ARIMA Dengan Mempertimbangkan Faktor Deterioration Gabriela Consuelo Heriyanto; Andreas Handojo; Tanti Octavia
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Blood has various uses that are very important for the human body. However, blood can only be donated in limited quantities because it can only be produced by humans. This blood donation activity is organized by the Blood Transfusion Unit (UTD), one of which is UTD PMI Surabaya. UTD PMI Surabaya also produces and stores blood products and distributes them to hospitals or directly to patients who need blood. Due to the uncertain amount of blood demand, UTD PMI Surabaya needs to make predictions in order to meet the blood needs. But blood has an expiry that also needs to be considered. Meanwhile, the blood demand prediction system still uses human estimates. Therefore, an information system is needed that can assist in predicting the need for blood by considering the expiration date of the blood. The application made in this research is a web application that can assist in making predictions using the ARIMA method. Then a calculation will be carried out by considering the deterioration of the blood to determine the need for blood in the next month. Based on the test results, the application is able to predict blood needs. The ARIMA model used to predict WB blood components is ARIMA (7,0,6) with a RMSE of 58,91. While the ARIMA model used to predict the TC blood component is ARIMA (5,0,6) with a RMSE of 272,46.
Sistem Optimalisasi Rute Model Capacitated Vehicle Routing Problem With Time Windows Menggunakan Algoritma Metaheuristic Particle Swarm Optimization pada Perusahaan Kantong Plastik HDPE PT XYZ Jason Jason; Silvia Rostianingsih; Andreas Handojo
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Technology has been one of the key factors behind industrial revolution. Companies are now required to use technological assistance and data processing to produce faster and more efficient business processes. This is also the case with Company XYZ. Company XYZ is an HDPE plastic manufacturer domiciled in Surabaya. Currently, the company is trying to handle the increasing frequency of shipments that exist in the company. Due to the increasing frequency of shipments, the company is often overwhelmed in handling its shipments because there is no system that can quickly determine the shipping route for the company. Moreover, there are other route determining factors such as shipment weight, truck capacity, and special delivery hour requests that add to the complexity of the route to be calculated manually. So a system is needed that is able to provide route recommendations quickly. This route optimization system is designed using the PHP programming language and the Bootstrap frontend framework to support the system UI Design. The database used is mySQL database. The system will be created in 2 modules, namely a module for the admin and a module for the driver. For this system to work, firstly the system will run the KMeans Cluster function from the database to cluster all customers in the company. This cluster is one of the factors determining the fitness value in the Particle Swarm Optimization algorithm. After the order data is obtained, the system will use the PSO algorithm to determine the delivery agenda for each truck. The determining factors of PSO include customer location, priority hours of customer requests, order weight, and loading capacity of different types trucks. After obtaining the delivery table of each truck, the system will use the help of Google Waypoints API to determine the routing order from each truck. The final result of this system is a delivery route optimization system that is able to provide route selection recommendations for each truck in the company. The system is also able to sort shipments with various shipping priority restrictions. From the test results, the PSO algorithm in the system is able to produce routes with less total distance traveled and less travel duration than the routes generated manually by the employees in the company.
Pembuatan Aplikasi Penyimpanan Password Menggunakan Metode Honey Encryption Pada Android Nouchka Indra Dewa; Agustinus Noertjahyana; Andreas Handojo
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Currently, this data storage certainly really needs security to avoid risks such as hacker attacks, data leaks, or loss that is always there. One measure for this security is to use a password to protect the information. However, this is quite risky where passwords that have difficult combinations will be difficult to remember. To help android smartphone users in storing and securing these passwords in their smartphones, a password storage application was made. This application is made on an android smartphone using a cryptographic method, namely the Honey Encryption method. Where is an application on an Android-based smartphone that aims to store and secure passwords. Users can manually set the key that will be used in the encryption process. This encryption process is done online so that the user can make a request from the server for the key data. This online step can make it easier for users to delete and manage online backup data in the form of keys and text data for their username and password. The results of this study indicate that this system is protected by the Honey Encryption Algorithm which is able to secure the stored passwords. It also shows that this system has successfully implemented the Honey Encryption Algorithm to trick users who do not have a password by displaying the wrong password.
Aplikasi Channel Management dan Point of Sales pada perusahaan retail PT. XYZ dengan menggunakan metode Cross-channel dan Market Basket Analysis Kenny Nugraha; Andreas Handojo; Alexander Setiawan
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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PT XYZ is a company engaged in the retail and distribution of baby equipment located in Surabaya. Generally, the company has many stores ranging from physical stores and online stores. The problem faced at this time is that there is no system that can connect the company's internal systems including the cashier system, warehouse system, sales calculation system with the existing system in online stores such as in this case the Shopee system. To answer these problems, PT XYZ requires a website-based channel management system so that it can be integrated both on mobile and desktop. It is hoped that by using this technology, it can help companies improve the performance and sales performance of stores both physical stores and online stores. An integrated Multichannel Management System and Point of Sales Application can record every sale, stock management practically and efficiently so that when a stock transaction occurs it will always be synchronized along with transaction data from between online stores and offline stores.
Penerapan Artificial Neural Network dan Rule Based Classifier untuk Mengklasifikasikan Pendonor Darah Potensial pada Sistem Broadcast Pendonor Widya Arditanti; Andreas Handojo; Tanti Octavia
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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One of UTD PMI Surabaya’s task is to provide safe and quality blood when blood is needed in an emergency. The availability of blood at UTD PMI Surabaya can be erratic, because it depends on the number of donors that fluctuates and the storage time of blood is not long. Therefore, UTD PMI Surabaya needs a system to invite potential donors to meet blood needs when needed in an emergency, by minimizing blood wasted. The classification model and the creation of a recommendation system will produce a list containing donors who have been sorted by priority. Testing was carried out by dividing the data according to the conditions of the data collection environment (before the pandemic, during the pandemic and a combination of before and during the COVID-19 pandemic). The highest MRR value was obtained from the ANN model made from a combined data of 90% classification results using RBC and fake data. The accuracy value obtained from the model is 91.13% for training and 91.83% for testing. The resulting MRR value is 8.07 x 10-4 .
Aplikasi Sistem Pendukung Keputusan Metode TOPSIS dan AHP-TOPSIS Untuk Pemilihan Proyek Pada Perusahaan Kontraktor CV.X Aldo Kurnia Christianto; Alexander Setiawan; Andreas Handojo
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

A contractor company is an example of a company engaged in the construction sector. CV.X contractor companies need to consider project bids by considering all aspects of the company and appropriately. Inefficient project selection can be fatal. Project selection errors can occur because decision makers only rely on feelings and experiences. Therefore, a decision support system can help the decision-making process at the CV.X contractor company. The TOPSIS and AHP-TOPSIS methods are used to find out which method is better to be applied to a decision support system and make weight improvements after knowing the best method for each project category that CV.X is working on. In the construction/rehabilitation project category, AHP-TOPSIS is better than TOPSIS with a correlation coefficient of 0.8 for Kendall and 0.9 for Spearman. In the TOPSIS and AHP-TOPSIS road improvement project categories, the Kendall 1 and Spearman correlation coefficient values are 1. For the licensing project category, the TOPSIS method excels with the Kendall correlation coefficient value of 0.33 and Spearman 0.464286. TOPSIS weight improvement is done by brute force to find the combination of weights with the best correlation value. Improvements to the weight of the criteria were not carried out in the category of development/rehabilitation projects because the resulting ranking results were slightly different and were used as a reference for decision making. Improvements to the weighting criteria for the road improvement project category were not carried out. Improvements to the weighting criteria for the TOPSIS method permit project category were carried out and increased the resulting Kendall and Spearman correlation values to 0.714286 and 0.821429.
Order Fulfillment pada Taksi Online dengan Mempertimbangkan Prioritas Penumpang Menggunakan Metode Recency, Frequency dan Monetary Viona Angelica; Andreas Handojo; Tanti Octavia
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Along with the development of technology in Indonesia, online taxi companies are one of the fields that are starting to be developed. Just like other companies, online taxi companies are looking for profits, to achieve it, they need to maintain good relations with their passengers. That can be achieved by improving service to loyal passengers. In this study, factors will be applied to improve service to loyal passengers and drivers such as rating, number of trips, driver’s RFM score and passenger’s RFM score. The method used to segment drivers and passengers is RFM prioritization and Filtered RFM prioritization. The method used to pair the driver and passengers is the Hungarian method. This study shows that by adding additional factors such as driver and passenger RFM scores, driver ratings, and the number of trip drivers accompanied by a passenger pick-up time limit, don’t change the assign time, waiting time, and pickup time of passenger but can prioritize passengers and drivers according to those factors. In addition, internet speed also has a huge influence on website-based order fulfillment simulations.
Sistem Otomasi Rute Order Picking Pada Gudang dengan Metode Simulated Annealing Stienley Nagata Cahyady; Andreas Handojo; Tanti Octavia
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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Abstract

Order Picking is a process to make a selection from products and picking them up from the place that products are stored and then sort the products out to fulfill the customer orders. Order picking process is the most expensive activity in the warehouse. The reason is order picking needs a lot of workforce and if order picking done manually it will cost as much as 55 % of the total cost of the warehouse. That’s why order picking is the correct part to be optimize to make warehouse become more effective and efficient. In this thesis, a web based application designed to solve all the problems above, which includes showing the shortest route to be pick for orders picking with simulated annealing method. Other than that, the application will be included with a hardware named RFID reader which can detect product placement and pickup from the shelf. The result of this thesis showed that simulated annealing algorithm able to reduce the range that are needed to order picking as much as 51.57058354 % for 100 data, 35.56569879 % for 500 data and 28.18222784% for 1000 data with fixed parameters. For the RFID reader it have the accuracy of 40% for reading products on the shelf. This is because the signals from tags clashing with each other which make the reader unable to read all of them.
Aspect-Based Sentiment Analysis pada Ulasan ECommerce dengan Metode Support Vector Machine untuk Mendapatkan Informasi Sentimen dari Beberapa Aspek Hansen Gunawan Sulistio; Andreas Handojo
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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In this era of globalization, all people's activities are starting to use technology to facilitate their daily activities. One of the most impactful forms of digitization activities is online buying and selling activities such as the use of the Tokopedia and Shopee platforms. The existence of a review feature on online buying and selling places (e-commerce) is one of the factors supporting the increase in people's online transactions. The number of people who have started to implement online buying and selling activities in their daily lives has resulted in an increase in the number of reviews on e-commerce.The large number of reviews makes it difficult for potential buyers to review a product to be purchased. The factors that determine the shopping experience of each individual are different so that the reviews and ratings given by each individual on a product or store vary. This affects the average rating of a product or store so that the average rating on a product does not necessarily represent the quality of the product. To overcome this problem, the author makes a system where prospective buyers and sellers will be facilitated to assess an aspect of a product. The system created by the author shows several aspects that are crucial for buyers and sellers in reading a review, such as general aspects, accuracy, quality, service, delivery, packaging, and price using the Support Vector Machine method. In these aspects, the system created will show sentiments on reviews that have been written by buyers such as positive, negative, or neutral sentiments. In addition to showing the sentiments of aspects of a product, this system also shows which aspects affect the product rating the most, the aspects that are most frequently discussed, what aspects are most rated positively and negatively.The results of the thesis show that the aspect that is often discussed is the quality aspect. General aspects, accuracy, quality, service, delivery, and packaging affect the rating value on a product rating while the price aspect does not affect a product rating. Compared to the Shopee platform, there are more positive reviews written on Tokopedia than reviews on Shopee.
Sistem Rekomendasi Content Based Filtering Pekerjaan dan Tenaga Kerja Potensial menggunakan Cosine Similarity Philips Nogo Raharjo; Andreas Handojo; Hans Juwiantho
Jurnal Infra Vol 10, No 2 (2022)
Publisher : Universitas Kristen Petra

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During the pandemic, there was an economic problem that forced companies to do something to avoid any loss. One of the action is to terminate the employment with their workforces. In the conventional way, the workforce and the company will waste a lot of time looking for the right fit for them. So, the recommendation system for jobs and workforce plays an important role in these conditions. Because with the existence of recommendation system that can help from both sides, it will speed up the meeting between companies that need workers and workers who need jobs. Based on the test have been carried out, the recommendation system using the TF-IDF model can provide good recommendations based on the calculation of the Mean Reciprocal Rank getting 0.857 and Mean Average Precision of 0.833, where these results are quite good.
Co-Authors Adi - Wibowo Agus Santoso Agustinus Noertjahyana Agustinus Noertjahyana Aldo Kurnia Christianto Alexander Setiawan Alvin Assianto Leiman Anton Wahyudi Christian Purnama Djoni Haryadi Setiabudi Djuvan Pranoto Dwiki Noviandra Kristanto Edward Budiman Sutanto Gabriela Consuelo Heriyanto Gregorius Satia Budhi Gregorius Satia Budhi Hans Juwiantho Hansen Gunawan Sulistio Harry Timothy Tumalewa Iwan Setiawan Jaceline Wongsonegoro Jason Jason Jessica Florencia Johan Sutanto Julius Wonodihardjo Justinus Andjarwirawan Kenny Nugraha Lienny Ferlinda Magdalena Magdalena Michael Christian Wibisono Nouchka Indra Dewa Osbert Tjitro Sampurna Philips Nogo Raharjo Sandy Sunaryo Silvia Rostianingsih Silvia Rostianingsih Stienley Nagata Cahyady Tanti Octavia Viona Angelica Vitalona Crysantini Paays Wahyu Christianto Widya Arditanti William Surya Wijaya William Tupan Yulia -