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Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen
Published by STMIK Palangka Raya
ISSN : 20881770     EISSN : 25033247     DOI : 10.33020
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Jurnal Saintekom adalah singkatan dari Sains, Teknologi, Komputer dan Manajemen, merupakan jurnal ilmiah yang berfungsi sebagai media mengkomunikasikan ide, gagasan dan pemikiran seputar kajian aktual tentang sains, teknologi, komputer dan manajemen antarkademisi dan peneliti.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 161 Documents
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Analisis Pengalaman Pengguna Game Visual Novel Asal Usul Kota Surabaya Menggunakan Metode Usability Testing Fauzan Dianta, Ashafidz; Kusuma Nurindiyani, Artiarini; Maisat Eka Darmawan, Zakha
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 13 No 1 (2023): Maret 2023
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/saintekom.v13i1.386

Abstract

A visual novel game is a visual communication design product that integrates graphic design through visual styles, visual character designs, and narrative designs accompanied by interactive communicative story construction. Games with the best storytelling and the ability to communicate historical chronology and cultural facts are synonymous with visual novel games. In the previous study, the Visual Novel Folklore Game of the Origins of the City of Surabaya featured puzzle and dialogue mechanics to build a more interactive narrative with the user. In addition, there is a branching narrative where users can make decisions by choosing which point of view the user wants to play. Several stages in this study include data collection, usability testing, data analysis, and conclusion. The results of this user experience analysis research overview several usability aspects that should be concerned in the subsequent game development. The usability aspects tested are Learnability, Memorability, Efficiency, Error, and Satisfaction. Of the 114 respondents involved in this study, the highest average score was obtained for the satisfaction aspect, which was 4.17, while the lowest average score was for the error aspect, which was 3.83, the games is easy to play and get satisfying results in every aspect of usability, the games is easy to play and achieves satisfactory results in each usability parameter.
Implementasi Data Mining Transaksi Penjualan Menggunakan Algoritma Clustering dengan Metode K-Means Afiasari, Nur; Suarna, Nana; Rahaningsi, Nining
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 13 No 1 (2023): Maret 2023
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/saintekom.v13i1.402

Abstract

The large number of products sold by the Bill Lights Store resulted in a stockpile of several product items due to the large supply of products that were less attractive to customers, resulting in many unsold and under-sold products. Bill Lights struggles with inventory levels of sold and unsold products, as well as shortages and overstocks. Bill Lights stores should rank each product so that they know which products are in the most demand. The purpose of this research is to solve the problem of using inventory information by grouping inventory products based on product characteristics using data mining techniques. The technique used is the K-Means algorithm method. K-Means algorithm clustering method and RapidMiner software processing. The data mining process starts with data processing (selection, cleaning, transformation, data mining and interpretation/evaluation). So if we start with a dataset of 160 products, we get cluster 0 with 88 products classified as sold, cluster 1 with 26 products classified as unsold, and cluster 2 with 46 fewer products classified as sold. The result of using the K-Means method is grouped into three clusters. To enable Bill Lights Store to implement sales and growth strategies based on products that are selling well.
Analisis Rekaman Suara pada Aplikasi Magic Call dengan Metode Forensik Audio untuk Mendapatkan Bukti Digital Subki, Ahmad; Karim, Muh Nasirudin; Imran, Bahtiar
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 13 No 2 (2023): September 2023
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/saintekom.v13i2.373

Abstract

Audio forensics is a method used to analyze sound or audio recordings. Voice or audio recording is one of the digital evidence that is easy to manipulate. One way to manipulate sound is to use magic call. Magic call has several levels of character voices that can be used such as cartoon, children, male and female voices. The analysis of the original voice recording with the magic voice recording is done by comparing the magic call sound and the voice with the original voice recording. The purpose of this study was to determine the voice recording produced by magic call from the magic call applications. As for the method used in this research is audio forensics, research on magic call sound using audio has never been done before. The results of this study indicate that the analysis of magic call sound recordings can be done using formant analysis and spectrograms, while pitch analysis on magic call voice recordings cannot be used. The formant and spectrogram values on magical voice recordings can still be searched because the original voice recordings have characteristics that are still attached to the magic recording calls.
Model Analisis Incident Management pada Layanan Teknologi Informasi Berdasarkan Framework Information Technology Infrastructure Library V3 Maulana, Yoppy Mirza
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 13 No 2 (2023): September 2023
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/saintekom.v13i2.398

Abstract

Information Technology (IT) services are services developed by service provider organizations for customers. Service provider organizations in implementing IT services have a goal to ensure IT systems remain in good condition to avoid incidents. Incidents are unexpected interruptions and reductions in the quality of IT services. Therefore, when an incident occurs in IT services, it is necessary to recover as quickly as possible or it is called incident management. Incident management is very important for service provider organizations, because if incidents are not managed and analyzed carefully then these incidents will recur. On this basis, a study was conducted to develop an IT service incident management analysis model based on the Information Technology Infrastructure Library (ITIL) V3 which aims to serve as a guide in analyzing and making recommendations for incident management. This model uses case studies in the PPTI section at Dinamika University. This model produces three stages including the incident data collection stage which produces IT service incident data. The incident management analysis stage produces a gap analysis, while the recommendation stage produces recommendations for improvement.
Evaluasi Usability Aplikasi Zenly Menggunakan Metode Usability Testing Hibban, Naseh; Albaihaqi, Rafi; Rifai, Dito Bakhtiar; Aiman, Hasby
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 13 No 2 (2023): September 2023
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/saintekom.v13i2.399

Abstract

The rapid development of applications has resulted in mobile application developers competing to create applications that are useful for the wider community, as is the case with the Zenly application. Through this application, every user can easily meet in real life, track the current whereabouts of someone with their consent, find the whereabouts of friends or relatives who are lost in the crowd, and follow the progress of the closest people. This research aims to determine the level of usability of the Zenly application and provide suggestions for improvement. The research stages followed a sequence of methods, including usability testing, preparation, execution, and analysis, time efficiency, and SEQ (Single Ease Question). Data was obtained on the average task time, success level, completion rate, and the lowest time efficiency, with task 1 taking 14,357 seconds, 38% success rate, two partial completions, and 87.5% completion rate. Based on the testing of these aspects and the results of the SUS (System Usability Testing) value of 71 Grade C (Good), the level of usability of the Zenly application is quite good but improvements need to be made, especially for task 1.
Data Mining Menggunakan Multiple Regression untuk Prediksi Harga Saham Netflix Dona Ariyatma, Rama; Fahmi, Syahrul
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 13 No 2 (2023): September 2023
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/saintekom.v13i2.419

Abstract

Investing in the stock market is an important and fascinating endeavor, especially when we observe significant increases in certain stocks. Currently, Netflix stock is one of the rising stars and sought after by investors. However, along with the potential for high profits, there are certainly risks of losses that need to be anticipated. To mitigate these risks, an investor must make predictions about future stock prices. One method that can be used is data mining, a data processing technique used to discover patterns in data. In this study, data mining was conducted using the multiple regression algorithm to predict the future price of Netflix stock. Python and Jupyter Notebook were used as tools to process the data, which was collected from January 4, 2010, to March 30, 2023, totaling 3334 data points. After data processing, the model yielded a score of 0.99%, indicating a highly reliable model. Additionally, evaluation using RMSE resulted in a value of 3.73, and MAE had a value of 2.80, both derived from 1334 testing data points. With accurate prediction results and the evaluation conducted, an investor can use these findings as a reference when deciding whether to buy or sell Netflix stock.
Klasifikasi Buah Jeruk Segar dan Busuk Berdasarkan RGB dan HSV Menggunakan Metode KNN Napitu, Stifani; Paramita Panjaitan, Rini; Nulhakim, Putri Aisyah; Khalik Lubis, Muaz
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 13 No 2 (2023): September 2023
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/saintekom.v13i2.420

Abstract

Fruits are a group of agricultural commodities in Indonesia. The demand for domestic fruit commodities is quite high, this is indicated by the large number of fruits available in modern markets and traditional markets. In this research, a classification process will be carried out between fresh oranges and rotten oranges based on RGB (Red, Green, Blue) and HSV (Hue, Saturation, Value) color extraction. This study uses the K-Nearest Neighbor classification algorithm with a value of k = 1; 2; 3; 4; 5; 6; and 7. The dataset used consists of 146 training data and 88 testing data. The purpose and benefits of this research are to save time and facilitate classification according to the wishes of fruit growers. The final result of the test accuracy is 88.95%. Based on the test, this system can be said to be quite good at classifying fresh and rotten citrus fruits.
Rancang Bangun Sistem Informasi Pencarian Data Objek Pemajuan Kebudayaan Kota Bengkulu dengan Algoritma Sequential Searching Dyah Pujiastuti, Nur Rochmah; Ramadhandi, Wahyu Dwi
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 13 No 2 (2023): September 2023
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/saintekom.v13i2.424

Abstract

Information media supports knowledge about cultural objects, especially Bengkulu. The search for cultural objects in Bengkulu City. with the desired keywords using the Sequential Searching Algorithm is a solution to the search problem. This study uses a system development that applies the Waterfall method. Methods that are serial namely Analysis, Design, Implementation, and Testing. System testing uses the System Usability Scale (SUS) to test user convenience and Blackbox Testing to test functionality. A web-based search information system for cultural promotion objects of Bengkulu City has been built by applying the Sequential Searching Algorithm. The SUS test with 30 respondents got a score of 83.75, according to the Acceptable Range scale, which is Acceptable, the Grade Scale scale, which is B, and the Adjective Rating scale, which is good. Black Box testing is carried out for 22 activities to get 100% results meaning the system is running well. Based on the results of keyword testing and search time, it has a real time average of 0.055 ms for the 10 data tested. It was concluded that the information system for the promotion of culture in the city of Bengkulu is feasible to use.
Sistem Klasifikasi Monitoring dan Evaluasi Kelayakan Penerima Beasiswa UAD Menggunakan Algoritma Naïve Bayes Siswanto, Dyllan Bagus; Normawati, Dwi
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 13 No 2 (2023): September 2023
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/saintekom.v13i2.428

Abstract

Kartu Indonesia Pintar (KIP) scholarship program at Ahmad Dahlan University includes a monitoring and evaluation internal process conducted at the end of each semester to monitor scholarship recipients. This allows for an assessment of their eligibility to receive the scholarship in the upcoming semester. The current manual MONEVIN process results in a time-consuming and less objective eligibility analysis. This eligibility determination system is needed, utilizing data mining techniques based on previous KIP scholarship recipient data to make predictions. Naïve Bayes algorithm, a data mining technique employing mathematical probability calculations, is utilized. The process begins with preprocessing, followed by data mining, evaluation, system implementation, and testing using System Usability Scale. The research uses a dataset of 270 student records, employing a 9-fold cross-validation process to split the data. Implemented model is integrated into a website-based system accessible to Biro Kemahasiswaan dan Alumni (BIMAWA). Model testing employs the Confusion Matrix technique, resulting in an accuracy score of 0.985, precision of 0.987, recall of 0.985, and an F-score of 0.985, indicating a favorable classification outcome. The system's eligibility assessment is further tested using the SUS, yielding a score of 90. Therefore, it can be concluded that the developed system is suitable for use.
Implementasi Algoritma Convolutional Neural Network untuk Pendeteksi Objek dalam Rumah pada Mata Rabun Egamo, Pramadika; Hermawan, Arief
Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Vol 13 No 2 (2023): September 2023
Publisher : STMIK Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33020/saintekom.v13i2.456

Abstract

The increased use of laptops and smartphones during the COVID-19 pandemic has led to an increase in the number of people suffering from nearsightedness. Convolutional Neural Network (CNN) is a class of deep learning that is capable of recognizing images and classifying images. Convolutional Neural Network is a technique inspired by the way mammals (humans) generate vision. CNN can be used to help nearsighted people detect or see objects in the house. With the CNN algorithm, this algorithm will be implemented to detect objects in the house to help people with myopic eyes. The number of epochs is varied in the dataset training process using Yolov5 which is included in the Convolutional Neural Network algorithm. The training dataset results show that the highest accuracy is 95%, which is obtained through mAp (mean Average Precision) calculation. The training process was carried out using a batch size of 16 and running training for 100 epochs. Different from previous research, this research implements the CNN algorithm to detect objects in the house to help people with nearsighted eyes.

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