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Scientific Journal of Informatics
Published by Universitas Negeri Semarang
ISSN : 24077658     EISSN : 24600040     DOI : -
Core Subject : Science,
Computer Science & IT
Scientific Journal of Informatics published by the Department of Computer Science, Semarang State University, a scientific journal of Information Systems and Information Technology which includes scholarly writings on pure research and applied research in the field of information systems and information technology as well as a review-general review of the development of the theory, methods, and related applied sciences.
Arjuna Subject : -
Articles 564 Documents
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Expert System Diagnosis of Urinary System Diseases using Forward Chaining and Dempster Shafer Fitriana, Jevita Dwi; Prasetiyo, Budi; Arifudin, Riza
Scientific Journal of Informatics Vol 7, No 1 (2020): May 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i1.22400

Abstract

Expert system is a computer system that can adopt human knowledge into a computer. Expert system can be used to solve problems commonly performed by experts, one of them is the diagnosis of urinary system diseases. Expert system for the diagnosis of the urinary system disease especially for the inflammation of the bladder and these pyelonephritis using the forward chaining and the dempster shafer method. Forward chaining is used to diagnose disease based on the rules and the dempster shafer is used to determine the value of confidence. The goal is to build an expert system using forward chaining and dempster shafer methods to diagnose early urinary system diseases and to determine the level of accuracy. The data used is the secondary data obtained from the UCI Machine Learning Repository as much as 120 data and 6 attributes. The result of the implementation of the forward chaining and the dempster shafer methods on this expert system of diagnosis of urinary system diseases generates an accuracy value of 87.5%.
Analisis Kinerja Pengenalan Telapak Tangan Menggunakan Ekstraksi Ciri Principal Component Analysis (PCA) dan Overlapping Block Isnanto, R. Rizal; Zahra, Ajub Ajulian; Widianto, Eko Didik
Scientific Journal of Informatics Vol 2, No 2 (2015): November 2015
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v2i2.5082

Abstract

Cara aman untuk mengenali seseorang adalah dengan teknologi biometrik. Telapak tangan merupakan biometrika yang masih relatif baru bila dibandingkan dengan sistem biometrika seperti wajah maupun sidik jari. Ciri yang digunakan adalah garis utama telapak tangan. Untuk mengekstraksi ciri, digunakan metode Principal Component Analysis (PCA) dan Overlapping Block, dengan metode pengenalannya menggunakan ukuran kemiripan jarak Euclidean. Pengujian dilakukan terhadap 30 individu. Berdasarkan hasil pengujian menggunakan metode PCA dengan variasi jumlah 50,75, dan 100 komponen utama dihasilkan tingkat pengenalan yang sama yaitu 90%. Sedangkan pengujian menggunakan citra dengan intensitas pencahayaan yang kurang, dihasilkan penurunan pengenalan menjadi 80%. Namun, untuk pengujian menggunakan 10 responden uji di luar 30 responden latih dan uji yang terdaftar dalam basisdata tidak ada yang dikenali. Sementara itu, dengan metode overlapping block, dari hasil pengujian dapat disimpulkan bahwa sistem identifikasi garis-garis telapak tangan memiliki tingkat keberhasilan pengenalan 100%, baik dengan menggunakan citra uji telapak tangan yang telah dilatih maupun dengan citra uji luar. Sistem hanya mampu memberikan tingkat keberhasilan 30% apabila intensitas cahaya ruangan dikurangi dan tingkat pengenalan 40% untuk perubahan jarak antara telapak tangan dengan kamera. 
Model for Identification and Prediction of Leaf Patterns: Preliminary Study for Improvement Muzakir, Ari; Ependi, Usman
Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i2.30024

Abstract

Purpose: Many studies have conducted studies related to automation for image-based plant species identification recently. Types of plants, in general, can be identified by looking at the shape of the leaves, colors, stems, flowers, and others. Not everyone can immediately recognize the types of plants scattered around the environment. In Indonesia, herbal plants thrive and are abundantly found and used as a concoction of traditional medicine known for its medicinal properties from generation to generation. In the current Z-generation era, children lack an understanding of the types of plants that benefit life. This study identifies and predicts the pattern of the leaf shape of herbal plants. Methods: The dataset used in this study used 15 types of herbal plants with 30 leaf data for each plant to obtain 450 data used. The extraction process uses the GLCM algorithm, and classification uses the K-NN algorithm. Result: The results carried out through the testing process in this study showed that the accuracy rate of the leaf pattern prediction process was 74% of the total 15 types of plants used. Value: Process of identifying and predicting leaf patterns of herbal plants can be applied using the K-NN classification algorithm combined with GLCM with the level of accuracy obtained.
Dataset Characteristics Identification for Federated SPARQL Query Rakhmawati, Nur Aini; Fadzilah, Lutfi Nur
Scientific Journal of Informatics Vol 6, No 1 (2019): May 2019
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v6i1.17258

Abstract

Nowadays, the amount of data published in the RDF format is increasing. Federated SPARQL query engines that can query from multiple distributed SPARQL endpoints have been developed recently. A federated query engine usually has different performance compared to the others. One of the factors that affect the performance of the query engine is the characteristic of the accessed RDF dataset, such as the number of triples, the number of classes, the number of properties, the number of subjects, the number of entities, the number of objects, and the spreading factor of a dataset. The aim of this work is to identify the characteristic of RDF dataset and create a query set for evaluating a federated engine.  The study was conducted by identifying 16 datasets that used by ten research papers in Linked Data area.
Expert System for Determination of Type Lenses Glasses Using Forward Chaining Method Pramesti, Atikah Ari; Arifudin, Riza; Sugiharti, Endang
Scientific Journal of Informatics Vol 3, No 2 (2016): November 2016
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v3i2.7914

Abstract

One of the branches of computer science that is widely used by humans to help her work is the establishment of an expert system. In this study we will design an expert system for determining the type of spectacle lenses using a forward chaining method. In forward chaining method, starting with the initial information (early symptoms) and moved forward to fit more information to find the information in accordance with the rules of the knowledge base and production, and will be concluded in the form of the type of disorder diagnosis of eye disorders and provide solutions in the form of lenses of eyeglasses. Result from this study is that the match calculation of algorithm of forward chaining method between system and manual calculations produce the same output.
Reminder and Online Booking Features at Android-Based Motorcycle Repair Shop Marketplace Wayan Dony Mahendra; I Made Sukarsa; AA.Kt. Agung Cahyawan
Scientific Journal of Informatics Vol 7, No 1 (2020): May 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i1.22212

Abstract

Generally, vehicle service is a must for the vehicle owner. However, due to tight work routines, people often forget to service their vehicles. In addition, the service process is still using a manual system, such as taking a queue number which leads to the long queue of the service time. An Android-based Motorcycle Repair Shop Information System provides a solution to remind people to do a regular service on their vehicles with a reminder feature and make online bookings.  The system development uses the SDLC (System Development Life Cycle) method. The implementation process requires an Android smartphone and a computer device by using MySQL as data storage, Firebase as a notification sender, React native and Visual Studio Code are used for developing the system. The results of the UAT test (user acceptance testing) from 20 users show 55,8% answered agree to the display, features and flow of the system, 39,5% answered strongly agree to the three question parameters, and 4,7% answered disagree with the flow and display of the system.
Wireless Sensor Networks For Volcano Activity Monitoring: A Survey Hulu, Elisati; Riyanto, Bambang; Widyantoro, Sri
Scientific Journal of Informatics Vol 2, No 1 (2015): May 2015
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v2i1.4528

Abstract

Pemantauan gunung api merupakan salah satu bidang penerapan Wireless Sensor Network (WSN). WSN digunakan pertama kali untuk pemantauan gunung api di gunung Tungurahua, Ekuador Tengah pada tahun 2004. Selanjutnya diterapkan pada riset di gunung Reventador, Ekuador Utara dengan 16 sensor digunakan untuk menangkap sinyal seismik dan akustik. Pada kedua riset ini, desain jaringan dan algoritma dibangun untuk menangkap raw-data sinyal seismik dan akustik, dan mengirimnya ke base station. Seperti dua riset sebelumnya, proyek OASIS membangun WSN yang robust untuk memperoleh raw-data sebanyak-banyaknya dengan real time, kontinu dan kualitas sinyal yang high-fidelity. Berbeda dengan riset WSN untuk pemantauan gunung api sebelumnya, riset Rui Tan, dkk. dan Guojin Liu, dkk. mengembangkan WSN untuk pemantauan gunung api secara real time, in-situ dan long-lived tanpa transmisi raw-data ke base station. WSN dan algoritma didesain dengan membangun algoritma pemrosesan in-network untuk mendeteksi gempa vulkanik, menentukan onset time dari gelombang yang biasa muncul pada saat terjadi gempa.
Increasing Message Capacity in Images Using Advanced Least Significant Bit and Image Scaling Fadlil, Affan; Prasetiyo, Budi; Alamsyah, Alamsyah
Scientific Journal of Informatics Vol 8, No 2 (2021): November 2021
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v8i2.28138

Abstract

Purpose: Steganography is the science of writing hidden or hiding messages so that apart from the sender and the recipient, no one can know or realize that a message is hidden. This paper aims to analyze the method of advanced LSB to increase message capacity. Methods/Study design/approach: The steganography technique advanced LSB algorithm develops pre-existing steganographic algorithms such as LSB by utilizing a range of media pixel values cover (images that are used as media to hide messages) with different insertion rules from LSB. Image scaling in digital image processing is known as resampling. Resampling is a mathematical technique used to produce a new image from the previous image with different pixel size, often called interpolation. Increasing the pixel size of the previous image is called upsampling and in this study we will only use twice the image magnification. Result/Findings: The results of each test method using advanced LSB without image scaling and advanced LSB using image scaling were compared to obtain detailed comparison results of each method. Novelty/Originality/Value: Advanced LSB and image scaling in this study can increase the message capacity three times compared to only using the advanced LSB method without image scaling. It depends on the image pixels used.
Decision Support System for "Buleleng Cerdas" Program Social Fund Recipient Candidates with Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) Method Fitri, Aini Aidilah; Pradnyana, I Made Ardwi; Darmawiguna, I Gede Mahendra
Scientific Journal of Informatics Vol 5, No 2 (2018): November 2018
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v5i2.16457

Abstract

BAZNAS in Buleleng Regency has a problem program "Buleleng Cerdas". The problems are to make a decision to choose prospective scholarship recipients. The program activities include Student Assistance, One Family One Scholar, and Student Assistance with Achievement. The problems that arise because the selection of the prospective recipients are still manual and the assessment of the final results obtained is relatively long, still difficult to identify prospective recipients who are eligible in accordance with the existing quota, because the candidates Scholarship recipients are spread in the Buleleng region for private and public schools. The purpose of this research is to develop a Decision Support System for "Buleleng Cerdas" Program Social fund Recipient Candidates with AHP and SAW Method and to know the responsiveness of users. This system is supported by a method of decision making, namely the AHP method which is used to find the weights in each criterion, and the ranking calculation with the SAW method. For the testing process, four test process stages are performed: (1) black box test, (2) white box test  (3) test UEQ percentage is positive impression SUS percentage is 93%, (4) suitability testing of manual calculations on the system is appropriate.
Implementasi Adaptive Neuro-Fuzzy Inference System (Anfis) untuk Peramalan Pemakaian Air di Perusahaan Daerah Air Minum Tirta Moedal Semarang Hani'ah, Ulfatun; Arifudin, Riza; Sugiharti, Endang
Scientific Journal of Informatics Vol 3, No 1 (2016): May 2016
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v3i1.6516

Abstract

Peramalan pemakaian air pada bulan januari 2015 sampai April 2015 dapat dilakukan menggunakan perhitungan matematika dengan bantuan ilmu komputer. Metode yang digunakan adalah Adaptive Neuro Fuzzy Inference System (ANFIS) dengan bantuan software MATLAB. Untuk pengujian program, dilakukan percobaan dengan memasukkan variabel klas = 2, maksimum epoh = 100, error = 10-6, rentang nilai learning rate = 0.6 sampai 0.9, dan rentang nilai momentum = 0.6 sampai 0.9. Simpulan yang diperoleh adalah bahwa implementasi metode Adaptive Neuro-Fuzzy Inference System dalam peramalan pemakaian air yang pertama adalah membuat rancangan flowchart, melakukan clustering data menggunakan fuzzy C-Mean, menentukan neuron tiap-tiap lapisan, mencari nilai parameter dengan menggunakan LSE rekursif, lalu penentuan perhitungan error menggunakan sum square error (SSE) dan membuat sistem peramalan pemakaian air dengan software MATLAB. Setelah dilakukan percobaan hasil yang menunjukkan SSE paling kecil adalah nilai learning rate 0.9 dan momentum 0.6 dengan SSE 0.0080107. Hasil peramalan pemakaian air pada bulan Januari adalah 3.836.138m3, bulan Februari adalah 3.595.188m3, bulan Maret adalah 3.596.416 m3, dan bulan April adalah 3.776.833 m3. 

Page 28 of 57 | Total Record : 564

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