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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jusikom: Jurnal Sistem Informasi Ilmu Komputer Journal of Computer Networks, Architecture and High Performance Computing
Yonata Laia, Yonata
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Computer Science & IT Decision Sciences, Operations Research & Management Education

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Optimasi Rasio Kompresi Dan Kompleksitas Waktu Kompresi File Teks Menggunakan Algoritma Lempel-ZIV-Welch Dengan Fibonacci Search Laia, Yonata
Sinkron : jurnal dan penelitian teknik informatika Vol. 1 No. 1 (2016): SinkrOn Oktober Volume 1 Edisi 1 Tahun 2016
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (462.108 KB)

Abstract

Kompresi data berarti suatu teknik untuk memampatkan data agar diperoleh data dengan ukuran yang lebih kecil daripada ukuran aslinya sehingga lebih efisien dalam menyimpan serta mempersingkat waktu pertukaran data tersebut. Algoritma LZW ini dirancang cepat tetapi tidak bisa bekerja optimal karena hanya melakukan analisis terbatas pada data. Penelitian yang berkaitan dengan algoritma LZW menyatakan bahwa rasio kompresi dan waktu kompresi kurang optimal, serta algoritma LZW ini memerlukan waktu yang sangat besar dalam mengkompresi data. Pada penelitian ini, Algoritma Fibonacci Search (FS) diterapka untuk meningkatkan kinerja algoritma LZW dalam hal pencarian kamus kata (Dictionary) sehingga dengan pencarian yang optimal akan diperoleh kinerja LZW yang lebih baik. Data yang di gunakan dalam penelitian ini adalah data teks dengan alasan karena data teks lebih sederhana dalam pemrosesannya. Dari hasil penelitian dengan menguji lima jenis data teks menggukan algoritma LZW, dengan kapasitas yang berbeda yaitu 6,9,12,19 dan 24 Kb di peroleh rata – rata ukuran file kompresi sebesar 4, 148, rata-rata waktu kompresi sebesar 118,8, rata-rata rasio kompresi 64%. Dengan metodeLZWFS di peroleh rata-rata ukuran file kompresi 5,126, rata-rata waktu kompresi 86,2, rata – rata rasio kompresi 58%. Dari hasil penelitian diatas di peroleh kesimpulan bahwa Algoritma LZWFS berhasil menyingkat waktu pencarian data namun masih memiliki kelemahan pada saat pengurutan data
Analisis Implementasi Metode Fuzzy Tsukamoto Dalam Penentuan Calon Legislatif Salim, Stanley; -, Sutrisno; Laia, Yonata; Ompusunggu, Elvis sastra; Barus, Ertina Sabarita; Sihombing, Oloan
JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 7 No. 1 (2024): Jurnal Teknologi dan Ilmu Komputer Prima (JUTIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jutikomp.v7i1.4920

Abstract

Being elected as a legislative candidate is a challenging matter. Of course, you must know in the field of politics, both locally and globally, qualified leadership attitudes, moral values, and integrity, financially and financially established in order to carry out campaigns and have a base of followers so that all visions and programs can be conveyed to the public as a whole and clearly. Voters are also required to be wiser and more selective in choosing quality legislative candidates, given that the eligibility rate of candidates in Indonesia is still relatively low, and many participants still need to meet the criteria as ideal legislative candidates. Therefore, a technology and support system is needed that can sort and help the general public in determining quality candidates; in this case, the Tsukamoto Fuzzy method is used, which can be a solution in providing competent candidate recommendations because it has the characteristics of shortening time and simplifying the selection process objectively. This fuzzy method is a support system that is very
REDESIGN THE UI/UX OF THE PT MNO COMPANY PROFILE WEBSITE USING THE THINKING DESIGN METHOD Putera, Ihsan; Wati, Emma Nor Kholida; Natasia, Sri Rahayu; Laia, Yonata
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 7 No. 2 (2024): Jurnal Sistem Informasi dan Ilmu Komputer Prima (JUSIKOM PRIMA)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i2.4198

Abstract

In the current era of globalization, large and small companies must develop strategies for using websites to improve business branding to the general public. Based on the results of problem identification, there are several UI/UX problems on the PT MNO website, including an unattractive appearance, messy and overlapping fonts, and a messy layout. This research aims to redesign the PT MNO website to improve its UI/UX to make it more informative, clear, and easy to use. The solution can be implemented by redesigning the website design for PT MNO utilizing the design thinking methodology. This method has five phases: Empathize, define, imagine, prototype, and test. Based on observations and interviews, three categories of problems in the current website category were found: content, navigation, and features. Then, five pages were created for the design results or mockup solutions, namely the home page, services, portfolio, programs, and about us. Testing used a usability metric, SEQ (Single Ease Question). Based on SEQ theory, if the results given by respondents are more than 5.5, then the task or scenario is considered successful or easy to do. So, the five functions in terms of convenience were easy for the five respondents to complete. Keywords: Design Thinking, Redesign, UI/UX, Website.
APPLICATION OF DATA MINING USING THE RANDOM FOREST METHOD TO PREDICT HEART DISEASE Felix, Felix; Sitanggang, Delima; Laia, Yonata; -, Amalia; Radhi, Muhammad; Barus, Ertina Sabarita
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 7 No. 2 (2024): Jurnal Sistem Informasi dan Ilmu Komputer Prima (JUSIKOM PRIMA)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i2.4801

Abstract

A heart attack is when fatty deposits block the arteries. This causes symptoms such as shortness of breath and chest pain. In addition, obstructed blood flow to the heart can cause damage to the heart muscle. Heart attacks are still the highest cause of death in Indonesia to date. The problem today is that it is tough to predict and identify heart disease. The appropriate method needed to predict heart disease is the Random Forest method. This research aims to calculate the level of accuracy in predicting heart attacks. Based on research and data processing carried out by previous study by comparing two K-Neighbor algorithms, which produced an accuracy value of 83% and the Logistic Regression algorithm produced an accuracy value of 88% and it was found that the Random Forest algorithm had an accuracy of 86.88%. Thus, other algorithms are better at predicting heart attacks than the Random Forest algorithm. Keywords: Heart Attack, Random Forest, Prediction.
Utilization Of Website-Based Technology For Analysis And Prevention Of Stunting Using The Fuzzy Tsukamoto Methods Wijaya, Chandra; Asido, Elpri; Laia, Yonata
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 8 No. 1 (2024): Jurnal Sistem Informasi dan Ilmu Komputer Prima (JUSIKOM PRIMA)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v8i1.5319

Abstract

Stunting is a chronic malnutrition condition that has significant impact on inhibiting the growth of a child both physically and intellectually. The study aims toto analyze stunts using a web-based technology system using Tsukamoto’s Fuzzy method. This method was chosen for its ability to deal with the uncertainty and variability medical data. The system integrates various variables that affect stunts, such as nutritional intake and physical growth, to produce a more accurate diagnosis. The research was carried out by collecting data from various health sources and applying the fuzzy Tsukamoto method to process the data. The trial subjects in this developmental study were 30 children aged 1–60 months, or 0–5 years. Subjects were selected by random sampling, consisting of 6 children from 1–5 years of age each. Based on the results of the analysis, it appears that the fuzzy Tsukamoto-based system development trial can provide a better prediction of the risk of stunting in children compared to conventional methods. Using this approach, it is expected to help health workers take more accurate steps in the treatment and prevention of stunts. Keywords: Stunting, Fuzzy Tsukamoto Method, Nutritional Analyisis, Technology Systems, Child Heal
Implementation of comparison of K-means algorithm with C4.5 algorithm to predict the feasibility of being a Catholic Hulu, Ricky Kristian Arifin; Ginting, Alwi; Laia, Yonata
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 8 No. 1 (2024): Jurnal Sistem Informasi dan Ilmu Komputer Prima (JUSIKOM PRIMA)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v8i1.5345

Abstract

This research conducted a comparison between two methods, namely C4.5 and K-Means, with the aim of improving the work efficiency of the Catholic Church Secretariat in selecting data of prospective Catholic congregants. These methods were developed to assist secretariat employees in determining the eligibility of valid files and data of prospective Catholic congregants through a web-based application. The data used comes from the selection results of several files and data of prospective congregants that have been collected by the Catholic Church Secretariat. Data analysis was carried out using the K-Means and C4.5 algorithms to predict the feasibility of the prospective congregants' files. It is hoped that the results of this research can help the Catholic Church Secretariat to improve work efficiency, both in terms of time and effort, in the selection process of prospective Catholic congregants and increase accuracy in determining the eligibility of the data of each applicant at the Catholic Church Secretariat improve the efficiency of the selection process and enhance the accuracy in determining the suitability of potential members.
Investigation of The Increase in Drug Use in Medan City Using The Support Vector Machine (SVM) Method Sagala, Yessy Phalentina br; Samosir, Roman; Laia, Yonata
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4137

Abstract

Medan city is currently experiencing a troubling rise in the prevalence of drug abuse, necessitating effective strategies for detection and intervention. This research aims to improve the accuracy of identifying drug users in Medan using the Support Vector Machine (SVM) method. Data for the study were sourced from reputable institutions including the National Narcotics Agency (BNN), North Sumatra Regional Police (Polda Sumut), and the Health Office of Medan City. SVM was employed to analyze these datasets and distinguish between drug users and non-users. The study revealed that SVM achieved an impressive detection accuracy of 98.0%, a notable improvement compared to earlier approaches like Convolutional Neural Networks (CNN), which attained 83.33% accuracy.These findings highlight SVM's effectiveness as a robust tool for accurately identifying drug users. The outcomes of this study are anticipated to aid government entities in crafting targeted policies and strategies to combat drug abuse in Medan. By harnessing SVM technology, law enforcement and healthcare authorities can bolster their capabilities in swiftly and precisely detecting and responding to drug-related issues. This research contributes significantly to advancing methodologies in drug abuse detection, emphasizing SVM's pivotal role in achieving superior detection rates. In conclusion, the application of SVM in this study not only enhances detection accuracy but also underscores its potential as a reliable technology for addressing the growing challenge of drug abuse in urban settings like Medan. Future research could further refine SVM models and explore additional datasets to validate its efficacy in real-world scenarios, thereby strengthening efforts to mitigate the societal impact of drug misuse.
Co-Authors -, Amalia Asido, Elpri Barus, Ertina Sabarita Chandra Wijaya Delima Sitanggang, Delima Felix Felix Ginting, Alwi Hulu, Ricky Kristian Arifin Natasia, Sri Rahayu Oloan Sihombing, Oloan Ompusunggu, Elvis Sastra Putera, Ihsan Radhi, Muhammad Sagala, Yessy Phalentina br Salim, Stanley Samosir, Roman Sutrisno - Wati, Emma Nor Kholida