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Handoko, Koko
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IMPLEMENTASI DATA MINING PADA PENGATURAN DATA INVOICE DISTRIBUTOR MENGGUNAKAN ALGORITMA FP GROWTH Sudarto, Piter Prasetyo; Handoko, Koko
Computer Science and Industrial Engineering Vol 9 No 2 (2023): Comasie
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v9i2.7603

Abstract

A research was conducted at PT. Wyssa Artha Sejahtera a distribution company, to explore the processing of sales transaction data using the FP Growth algorithm to support better decision-making. The company deals with a large volume of daily sales transaction data involving various types of products, both wet and dry. The study aimed to extract useful information from the sales data, such as sales trends and the most popular products among customers. Data was collected through observations and direct interviews with the company owner from January 2022 to December 2022, using the proactive method for more comprehensive and accurate information. Upon collecting the sales transaction data, the research identified certain products with higher sales than others. RapidMiner software was utilized for processing the sales data, which proved to be suitable for implementing the FP Growth algorithm, especially for wet and dry product types with increasing sales transaction data. In the testing phase, RapidMiner successfully discovered item sets 1, 2, 3, and 4, along with their corresponding support and confidence values.The results of this research carry significant implications for PT. Wyssa Artha Sejahtera in making more informed decisions. By analyzing the sales transaction data, the company can devise more effective strategies to boost sales and meet customer demands. Furthermore, the findings can serve as a valuable reference for other companies in similar industries, helping to enhance their decision-making processes. The FP Growth algorithm analysis revealed that item sets 2, 3, and 4 had a minimum support of 20% and a minimum confidence of 70%.
IMPLEMENTASI DATA MINING DENGAN ALGORITMA NAIVE BAYES UNTUK KLASIFIKASI KELAYAKAN PENERIMA BANTUAN SEMBAKO Entini, Ayu; Handoko, Koko
Computer Science and Industrial Engineering Vol 9 No 3 (2023): Comasie
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v9i3.7659

Abstract

The percentage of the population receiving assistance was 5.19%, this figure increased compared to March 2022, while the line of aid recipients was recorded in 2022 of 783,730 people per capita per month. The number of poor households in Batu Aji District is Bukit Tempayang Village with 15,857 inhabitants, 300 poor households, 37,531 inhabitants in Buliang Village, 289 poor households, 28,693 The beneficiary of assistance is an inability to meet basic needs including food, clothing, education and housing. Thus it is necessary to carry out a strategy in dealing with the level of beneficiaries, namely by providing accurate and targeted data on beneficiaries. Naive Bayes is an algorithm that exists in data mining and is part of the data mining classification technique by using probability and statistical techniques to estimate or predict opportunities that will occur based on previous opportunities, namely there are two feasible and inappropriate classes. The results of the classification that will be carried out later will help in the processing of assistance to help make decisions regarding the classification of determining basic food recipients. And by testing calculations manually and using rapid minner software, you get an accuracy value of 80%.
IMPLEMENTASI PENGINPUTAN DATA COMPONENT ELECTRONICA BERBASIS WEB MENGGUNAKAN METODE AGILE Sihombing, Nita Anggrina; Handoko, Koko
Computer Science and Industrial Engineering Vol 9 No 6 (2023): Comasie
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v9i6.7822

Abstract

ABSTRACT Along with the rapid development of the times, human needs that are always increasing, especially increasingly advanced technology encourages every change that is much more modern. A need that is indispensable for an organization, company, agency, and so on is like a website. Where the website becomes a necessity both in business activities but also needed in every sales promotion and helps in work within an organization or company. PT. PCI is one of the companies that develops in the field of technology, where the company still inputs work component data manually so that the data input is less accurate. With the help of artificial intelligence can provide solutions in inputting data Entering component data and providing innovation using website-based technology can provide learning for every employee to be able to increase knowledge about technology, changes in a website-based method with manual input are very different, data that was originally input manually but can be made manually automatic. AGILE is known as a form of data development, the development works collaboratively, structured and organized so that the development is able to provide ease of work. With this research carried out in order to introduce how to input data properly and correctly. Artificial intelligence used on this website that produces input component data properly and correctly for use by employees in the work process, the use of artificial intelligence is expected to be an alternative media, so that it becomes more interesting in inputting data. Keywords: PT.PCI; Artificial Intelligence; Website; Agilel; Data component
IMPLEMENTASI DATA MINING MENGGUNAKAN ALGORITMA APRIORI UNTUK MENINGKATKAN POLA PENJUALAN Adam, Chairil; Handoko, Koko
Computer Science and Industrial Engineering Vol 9 No 6 (2023): Comasie
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v9i6.7823

Abstract

Medicine is a necessity for someone who is sold to people with disease. Therefore, every pharmacy or hospital must have a data processing system so that each transaction data can be used to make reports. From this report a useful result will be created to determine which drugs are most frequently purchased and sold so as to be able to determine the amount of stock at the pharmacy. But at the present time drug sales transaction data continues to increase every day so that it has accumulated because the system used is a system for storing or archiving bookkeeping without utilizing the transaction data, besides that the problem that often arises is the lack of maximum customer service at pharmacies because the drugs or needs that consumers are looking for are still not available. The a priori algorithm functions as a candidate for possible item combinations, then tests whether the combination meets the minimum support and minimum confidence parameters which are the threshold values ​​given by the user, so that it finds patterns in the form of products that will often be purchased together or products that tend to appear together in a transaction.
SISTEM PAKAR UNTUK DIAGNOSA KERUSAKAN KOMPUTER MENGGUNAKAN METODE FORWARD CHAINING DAN CERTAINTY FACTOR BERBASIS WEB Marpaung, Andy Jhonatan; Handoko, Koko
Computer Science and Industrial Engineering Vol 9 No 6 (2023): Comasie
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v9i6.7829

Abstract

Damage to the computer is caused by several problematic components such as problematic RAM, hard disk or VGA. This condition is a condition of minor damage which sometimes users consider this to be fatal damage due to a lack of knowledge about computer components, which is why an expert system is needed to help users understand. damage to the computer. In this research, the Forward chaining method will be used in the system that will be used in the program. This research will focus on a system that produces and adopts knowledge from an expert in the field and to be able to diagnose computer damage using a web-based method. An expert system is an application that uses the expertise or knowledge of an expert in a particular field and this expertise is implemented in a system.
RANCANGAN SISTEM PAKAR DIAGNOSA PENYAKIT PADA UDANG MENGGUNAKAN METODE FORWARD CHAINING BERBASIS WEB Cawa, Yohanes Valendry; Handoko, Koko
Computer Science and Industrial Engineering Vol 9 No 6 (2023): Comasie
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v9i6.7868

Abstract

The cultivation of vannamei shrimp has become the primary choice for shrimp farmers and breeders today. The superiority of this shrimp species lies in its resilience to stress and extreme weather conditions. However, the occurrence of diseases in cultivated shrimps remains a significant concern as it can lead to substantial losses if not properly addressed. This research aims to develop a web-based expert system to assist shrimp farmers and breeders in identifying the types of diseases affecting vannamei shrimp. The expert system employs the Forward Chaining method, allowing the system to infer and reach accurate disease diagnoses based on observed symptoms in the shrimp. The web-based nature of the system enables easy access for farmers and breeders through internet-connected devices. Utilizing PHP as the programming language and appserver as the database, the system gathers data provided by users about observed symptoms in the shrimp, subsequently performing inference to deliver precise diagnoses of potential diseases in vannamei shrimp. Leveraging the knowledge and expertise of fisheries experts, the system aims to provide more effective guidance in disease prevention and identification in vannamei shrimp. The expected outcome of this research is to contribute significantly to improving the management of vannamei shrimp cultivation, particularly in preventing and addressing diseases that may affect the shrimp. The expert system aims to empower farmers and breeders to swiftly recognize various diseases and take appropriate measures to maintain the health and productivity of vannamei shrimp cultivation.
IMPLEMENTASI APLIKASI PENGENALAN SOP PENGOLAHAN LIMBAH INDUSTRI PT X BERBASIS ANDROID Derosari, Rosalinda Mentigasa; Handoko, Koko
Computer Science and Industrial Engineering Vol 9 No 7 (2023): Comasie
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v9i7.7977

Abstract

The management and proper handling of industrial waste are crucial for environmental sustainability and regulatory compliance. This project presents the development and implementation of an Android-based application designed to recognize and facilitate the adherence to Standard Operating Procedures (SOPs) in the industrial waste processing operations of PT X. The application employs advanced image recognition and processing techniques to identify and validate SOPs associated with different waste processing tasks, ensuring that employees follow the prescribed guidelines accurately. By providing real-time guidance and verification, the application aims to enhance operational efficiency, reduce errors, and promote responsible waste management practices. This paper outlines the key features, technical aspects, and benefits of the application, underscoring its potential to contribute to a more sustainable and compliant industrial waste processing environment at PT X.
IMPLEMENTASI APLIKASI PENGENALAN SOP PENGOLAHAN LIMBAH INDUSTRI PT X BERBASIS ANDROID DEROSARI, ROSALINDA MENTIGASA DEROSARI; Handoko, Koko
Computer Science and Industrial Engineering Vol 10 No 1 (2024): Comasie
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v10i1.8140

Abstract

B3 medical waste management raises specific considerations and can provide a major problem if not handled effectively. As a result, PT. Desa Air Cargo Batam is on hand to undertake the processing, and the company already holds a B3 industrial waste processing authorization. To meet the company's vision and objective, the correct Standard Operating Procedure (SOP) must be used to reduce negative affects on the environment and society. However, in these companies, awareness and comprehension of the Standard Operating Procedure (SOP) for the handling of B3 medical waste remains a concern that must be addressed. The Software Development Life Cycle (SDLC) research technique was utilized for software development, and application development in this study was done with Adobe Illustrator, Visual Studio Code, and Flutter. The resulting application is compatible with Android smartphones running at least version 8.0 (Oreo). The waterfall method is applied in this scenario. The findings of black-box testing and functional testing reveal that the application performed as predicted, and the results of this application questionnaire are in the very good category, with no problems when operating
IMPLEMENTASI FINITE STATE MACHINE DALAM GAME EDUKASI BAHASA JEPANG Saputra, Juan; Handoko, Koko
Computer Science and Industrial Engineering Vol 11 No 2 (2024): Comasie Vol 11 No 2
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v11i2.9084

Abstract

The development of technology enables people to immerse themselves in Japanese culture, encompassing aspects such as fashion, culinary, arts, and language. This influence has sparked a rapid increase in Indonesian interest to learn Japanese. However, it is undeniable that few schools include Japanese language courses in their curriculums, this circumstances forces students to seek alternative learning sources such as private tutoring or courses. Moreover, traditional learning methods often leave students feeling bored dan exhausted, particularly through textbooks, thus demanding more engaging and relaxed learning approaches. Solas School of Languages, located in Batam, offers various language courses including Japanese. This study aims to implement the finite state machine method into an educational Japanese language visual novel game for Android, designed using Ren’Py game engine. This method will be applied to alter NPC character expressions within the game. The research output includes an educational Japanese language game featuring implemented finite state machines, the appearance of its interface, and data collected directly from students learning Japanese at Solas School of Languages. Thus, it is hoped that this research will demonstrate the effectiveness of game-based learning methods in making studying more engaging and assisting teachers in educating their students outside classroom.
ANALISIS PERBANDINGAN KINERJA ALGORITMA MACHINE LEARNING BERBASIS FEATURE SELECTION DALAM DETEKSI SERANGAN BOTNET Khoo, Rio; Handoko, Koko
Computer Science and Industrial Engineering Vol 12 No 2 (2025): Comasie Vol 12 No 2
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v12i2.9778

Abstract

Internet has experienced significant development. Increasing devices connected to internet makes security against cyber attacks a critical issue, thus creates opportunities for cyber attackers, one form of those attack is botnets. In Indonesia, Botnets is the highest traffic anomalies in 2022 by BSSN. High number of attacks because detecting botnet can be challenging, difficulty of detecting attacks and low level of detection accuracy means that normal data sometimes considered an attack, so choosing method that can handle this is very important. Machine learning algorithms are able to study network data traffic and identify suspicious activity, this makes machine learning an effective method. Machine learning based on feature selection has an accuracy of above 90% in detecting DDoS attacks on datasets and machine learning algorithms are also able to detect attack data and normal data. Thus, in this research machine learning algorithms such as K-Nearest Neighbors, Support Vector Machine and Naive Bayes will be applied to dataset containing botnet and normal data to explore how machine learning algorithms can effectively detect botnet attack patterns and normal data. This research compares the performance of commonly used machine learning algorithms to find which one effective for detecting botnet attacks in existing datasets.
Co-Authors Adam, Chairil Adriana, Lia ANDRIA, KIKI Andy Ari, jaya Ari Suhut Siregar Arisandy, Rizal Cawa, Yohanes Valendry Darmansah, Darmansah Deni, Irwansyah Derosari, Rosalinda Mentigasa DEROSARI, ROSALINDA MENTIGASA DEROSARI Eko Suharyanto, Cosmas Elan, Muhammad Elisa, Erlin Entini, Ayu Harman, Rika Hutahaean, Mangaratua Kesuma, Hendra Khoo, Rio Kusnanto, Romario lumban gaol, frenky lambas Marpaung, Andy Jhonatan Muhammad Iqbal Nainggolan, Brian Natanael NAPITUPULU, RIKKI LEONARDO Novri Adhiatma, Novri Rendi, Alvin Saputra, Juan Seldi, Yestiani Setyaji, Alvia Setyaji Sianipar, Agustinus Sihombing, Nita Anggrina Simanjuntak, Pastima Simanjutak, Pastima Sinaga, Karolina Steven Steven Sudarto, Piter Prasetyo Suharyanto, Cosmas Eko tampubolon, abdul chafid Tampubolon, Susi Susanti Tukino, Tukino Utami, Winda Putri Zebua, Alisa Zetli, Sri Zetly, Sri