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Jurnal Sains dan Teknologi Informasi
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 2809610X     DOI : https://doi.org/10.47065/jussi.v3i2.4883
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
Bidang kajian dari Jurnal Sains dan Teknologi Informasi, yaitu: Teknik Informatika, Manajemen Informatika, Sistem Informasi, Teknik Komputer, Kecerdasan Buatan, dan Computer Science.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 72 Documents
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Perancangan Aplikasi Kompresi File PDF Dengan Menerapkan Algoritma Stout Code Wardi, Indra
Jurnal Sains dan Teknologi Informasi Vol 4 No 1 (2024): Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v4i1.7706

Abstract

Human habits in collecting and exchanging data, one of which is in the form of PDF files, has an impact on limited storage space on computers. PDF files contain information in the form of PDF files and are widely used in the world of education, offices, companies and so on to create reports, assignments, papers, theses and others which will then be PDF files. Because the need for PDF files is very important, humans tend to collect data in the form of PDF files. In the process of exchanging data in the form of PDF files both online and offline, humans often unknowingly send and then store them in large and clear sizes, this causes the need for a large amount of storage media. The solution to solve this problem is to do compression. It is intended that the PDF file size becomes much smaller so that the PDF file transfer process is fast and can save storage space. There are several algorithms for compressing PDF files, but this study uses the Stout Code algorithm. After compressing the algorithm, then the results of the compression of the algorithm are based on several parameters such as Ratio Of Compression (RC), Compression Ratio (CR), Space Saving (SS). The results of the Stout Code compression algorithm will be compressed and a compressed PDF file will be obtained.
Review Produk Iphone dengan Analasis Sentimen menggunakan Algoritma Text Mining TF-IDF Tarigan, Devanta Abraham
Jurnal Sains dan Teknologi Informasi Vol 4 No 2 (2025): Maret 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v4i2.7799

Abstract

The iPhone is a product that has become a major concern in society and has become one of the main needs in everyday life. However, sometimes the iPhone often faces several problems that need attention. One problem that is often the main focus is the fairly high price. Therefore, we need a system that can determine the public's view of the iPhone product. This research uses text mining and TF-IDF to determine people's views on iPhone products. Text mining can be defined as the discovery of new, previously unknown information and the automatic extraction of valuable information from text from different sources. Meanwhile, TF-IDF is used to determine the frequency value of words in a document. In this research, sentiment refers to people's views on iPhone products, whether positive or negative. The final result of this sentiment analysis is that the positive sentiment value is 68.65% while the negative sentiment value is 31.35%. This is expected to provide information about the extent to which iPhone products are accepted by the public. By understanding people's sentiments, Apple company can take necessary actions to improve product quality and user satisfaction. Apart from that, this research also introduces the concept of Text Mining and the TF-IDF algorithm as a powerful tool for analyzing text data in the context of sentiment analysis.
Penerapan Metode ARAS Pada Pendukung Keputusan Penerimaan Karyawan dengan Pembobotan ROC Riadi, Rizka Salsabila
Jurnal Sains dan Teknologi Informasi Vol 4 No 2 (2025): Maret 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v4i2.7800

Abstract

A retail company adopts the concept of a hybrid convenience store, combining a minimarket and a cafe. The company's recruitment process for prospective employees is still manual and inefficient in making decisions to recruit employees who meet the company's criteria. Employees are the most important thing in a company for the company to thrive in the era of globalization. Based on the problems described above, a Decision Support System (DSS) is needed to help overcome these problems. By implementing the Rank Order Centroid (ROC) method, which can provide weighted values for each existing criterion based on its priority level. And to rank it using the Additive Ratio Assessment (ARAS) method, which can provide decision-making based on the highest ranking or value, it is hoped that this can help the company in making decisions regarding employee recruitment selection. So that the employee recruitment selection process can be more efficient. The results of this study indicate that a decision support system (DSS) built using the ARAS method and ROC weighting can assess prospective employees, with Alternative A4 achieving the highest final score of 0.9036.
Penerapan Teknik Data Mining dengan Algoritma Regresi Linier Berganda Untuk Estimasi Tingkat Penjualan Cafe Ritonga, Rama Prameswara
Jurnal Sains dan Teknologi Informasi Vol 4 No 2 (2025): Maret 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v4i2.7801

Abstract

This study aims to apply data mining techniques using multiple linear regression methods to estimate sales levels. Efficient sales are a key factor in the success of a cafe business; therefore, this approach is expected to provide accurate predictions to assist management in strategic decision-making. The main problem faced is uncertainty in forecasting sales levels, which can lead to excess or shortages of raw material stocks, operational disruptions, and decreased profits. Therefore, this study focuses on developing a multiple linear regression model that can utilize historical sales data, environmental variables, and other related factors to produce more accurate estimates. This research method involves collecting sales data from previous periods, analyzing statistics, and applying multiple linear regression as the main tool for building a prediction model. In addition, the selection and adjustment of variables that most influence sales levels are also focused in this study. The results show that the multiple linear regression model can provide more accurate sales level predictions compared to conventional methods. This can assist in inventory planning, operational management, and marketing strategy development to improve business performance. The implementation of data mining techniques with this method makes a significant contribution to supporting the sustainability and growth of cafe businesses in an era of increasingly fierce business competition.
Analisa Sentimen Masyarakat Naiknya Bahan Pokok Menggunakan Algoritma Teks Mining Dan TF-IDF Syechu, Weno
Jurnal Sains dan Teknologi Informasi Vol 4 No 2 (2025): Maret 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v4i2.7802

Abstract

Twitter is one of the social media used by the public to express opinions on news that is often discussed. Various opinions were expressed by the public on Twitter social media, including expressing opinions and complaints regarding the increase in basic commodities. Staples are people's basic needs in everyday life. Rising prices of basic commodities are a problem that society often faces. Therefore, the government must take steps to reduce the increase in prices of basic commodities, such as strengthening market control and regulation, increasing agricultural production, and providing subsidies to people who cannot afford it. This research aims to measure public sentiment regarding the increase in basic commodities for the community and it is hoped that it can become a benchmark for government parties related to the increase in basic commodities, so that it does not affect inflation and the stability of the community's economy. This research was carried out by taking 100 data from Twitter using crawling techniques and processing 50 data using TF-IDF weighting. Then the data was processed using text mining and a word weighted search was carried out using the Term Frequency Inverse Document Frequency (TF-IDF) algorithm. The results of this research showed that the percentage of public sentiment towards the increase in basic commodities with positive sentiment was 24.2414% and negative was 75.7586%.
Pemilihan Staff Pengajar Terbaik dengan Menggunakan Metode Preference Selection Index Atsauri, Muhammad Riki
Jurnal Sains dan Teknologi Informasi Vol 4 No 2 (2025): Maret 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v4i2.7803

Abstract

Selecting the best teaching staff is crucial in the education sector, as it motivates teachers who have educated students and can be recognized for their contributions. However, the data collection process is currently poorly organized, resulting in less than optimal selection of the best teaching staff. Therefore, the author used a decision support system using the Preference Selection Index (PSI) method to calculate competency scores for each teaching staff member and to rank them accordingly. The PSI method does not require relative importance between attributes. This method is used when determining relative importance between attributes is problematic. A decision support system implementing the PSI method is expected to assist in selecting the best teaching staff. This research can assist in making decisions regarding the selection of the best teaching staff accurately, effectively, and in a structured manner. The results of the study in determining the best teaching staff resulted in the best alternative, A3, with a score of 1.0000, thus being the best teaching staff member.
Penerapan Algoritma FP-Growth Data Mining Untuk Pole Persediaan Stok Barang Aksesoris HP Mughnyanti, Mayang
Jurnal Sains dan Teknologi Informasi Vol 4 No 2 (2025): Maret 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v4i2.7804

Abstract

The need for inventory stock, especially HP accessories, is one of the main pillars of the business process that must be carried out by the store management. Where the opportunity for calculation errors is carried out conventionally without an in-depth analysis that causes inaccurate determination of the amount of inventory that must be fulfilled, the results of the study present a solution with a Data Mining approach using association rule techniques. in the study using 100 data from sales transaction history within a certain period of time identified by running the Frequent Pattern Growth (FP-Growth) algorithm to maximize computational performance in the process of extracting item patterns. From the results of testing the stock data of HP accessories, it is known that the calculation results by applying Association rules in searching for each itemset by applying the FP-Growth algorithm there are 9 rules with the condition of a support value limit of <10% and a confidence value of 70%. While 16 rules that do not meet the value requirements of a total of 25 rules.
Diagnosa Penyakit Rabbit Haemorrhagic Disease dengan Menggunakan Kombinasi Metode VCRIS dan CF Ningtyas, Alyiza Dwi
Jurnal Sains dan Teknologi Informasi Vol 4 No 2 (2025): Maret 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v4i2.7805

Abstract

One of the rabbit diseases in the respiratory system is caused by a virus called rabbit hemorrhagic disease. Rabbit hemorrhagic disease is a disease caused by a virus that attacks the respiratory system of rabbits. For this reason, a system is needed that is designed to be able to imitate the expertise of an expert in answering questions and solving a problem according to the expert's knowledge which is entered into a computer system. The development of artificial intelligence technology that has occurred has enabled expert systems to be applied in detecting disease using programming languages. One of them is providing information about various problems, especially rabbit hemorrhagic disease. The expert system method used is a combination of the Variable Centered Intelligent Rule System (VCIRS) and Certainty Factor (CF) methods, which is one solution that can display the final results of several rabbit haemorrhagic disease diagnoses. With the facilities provided to users, it is possible to use this system according to their individual needs. Users are given the convenience of finding out information about the symptoms of rabbit hemorrhagic disease and its prevention.
Analisis Fungsi Implikasi Max-Min dalam Pengambilan Keputusan Penentuan Penduduk Kurang Mampu Menggunakan Metode Fuzzy Tsukamoto Ginting, Clusilla Via Mia Dalmatia Br; Agnesia, Mella; Rahayu, Cici; Ginting, Raheliya Br; Surbakti, Asprina Br
Jurnal Sains dan Teknologi Informasi Vol 4 No 4 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v4i4.8390

Abstract

Determining the underprivileged population is a crucial aspect in the distribution of social assistance to ensure it is targeted. Fuzzy logic methods, specifically the Tsukamoto Fuzzy Inference System (FIS), are capable of addressing uncertainty and subjectivity in the decision-making process. This study aims to analyze the application of the Max-Min implication function in the Tsukamoto fuzzy system to determine the category of underprivileged population based on income, number of dependents, and housing conditions. The results show that the use of the Max-Min implication function produces consistent, transparent, and reliable decisions to support government policy in distributing social assistance. Based on the test results, where Income = 1.5 million, Number of dependents = 5, and housing condition score = 4, the ability level of Mrs. Clu is included in the underprivileged category.
Implementasi Metode TOPSIS untuk Meningkatkan Objektivitas Sistem Pendukung Keputusan dalam Pemilihan Pegawai Teladan Sembiring, Elisabet Br; Tambunan, Esaday Gavinella Br; Siagian, Indah Enjelyna; Sembiring, Rafael Dekanta Yosafat; Ginting, Dewi Yohana br; Ginting, Lastri Marsely Br
Jurnal Sains dan Teknologi Informasi Vol 4 No 4 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v4i4.8448

Abstract

The selection of exemplary employees is an essential effort for organizations to improve performance, motivation, and work discipline. However, determining exemplary employees often encounters challenges due to subjectivity in the assessment process, which may result in decisions that do not fully reflect actual performance. To address this issue, a decision support system (DSS) is required to assist management in conducting evaluations objectively, systematically, and transparently. This study applies the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, which measures the relative closeness of each alternative to the positive ideal solution and the negative ideal solution. The evaluation criteria include discipline, responsibility, communication, initiative, and job mastery. The calculation stages consist of decision matrix normalization, weighted matrix formation, determination of ideal solutions, and preference value calculation to obtain employee rankings. The results indicate that the TOPSIS method produces consistent and fair outcomes in determining exemplary employees. From the ranking table, it is shown that the highest preference value of 0.6511 was obtained by alternative V8, namely Dermansyah, who is therefore concluded to be the most suitable candidate for the exemplary employee award. Thus, this research provides a practical contribution to organizations by offering an efficient and accurate decision-making tool that minimizes subjectivity. In the future, this system can be further developed by integrating additional methods or web-based technology to enhance accessibility and applicability in various organizational contexts.

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