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Teguh Susyanto
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Jurnal Ilmiah Sinus
Published by STMIK Sinar Nusantara Surakarta
ISSN : 16931173     EISSN : 25484028     DOI : http://dx.doi.org/10.30646/sinus
Core Subject : Science,
Computer Science & IT
Jurnal Ilmiah SINUS is a magazine published twice a year, wherein one issue there are seven articles. Jurnal Ilmiah SINUS as a communication medium to report the results of field research, library research, observations or opinions on problems arising related to the development of information technology.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 263 Documents
 23   24   25   26   27 
Rancang Bangun Sistem Pakar Diagnosa Penyakit Tanaman Pisang Canvendish Dengan Metode Forward Chaining Kevin Kurniawansyah; Noneng Marthiawati. H; Reni Aryani
Jurnal Ilmiah SINUS Vol 21, No 1 (2023): Vol. 21 No. 1 Januari 2023
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v21i1.679

Abstract

Bananas are part of the horticultural commodity group of fruits which are widely consumed because of their delicious taste and high nutritional content. One of the problems that exist when cultivating canvendish banana plants is the existence of disease disorders that occur in these plants. To prevent this from happening, knowledge about the diseases experienced by these plants is based on the symptoms experienced. Sources of knowledge about the disease and its symptoms can be obtained from an expert. However, the difficulty of consulting with experts in the field of canvendish bananas can be overcome with the help of an expert system to diagnose diseases of canvendish bananas using the Forward Chaining method. The purpose of this research is to help banana farmers or ordinary people to be able to carry out prevention and treatment when bananas are attacked by diseases or pests and overcome existing problems regarding canvendish bananas.
SISTEM PENDUKUNG KEPUTUSAN PENERIMA BANTUAN PKH (PROGRAM KELUARGA HARAPAN) DENGAN METODE PERBANDINGAN EKSPONENSIAL Frandy Putra Gusti A.P; Elistya Rimawati; Sri Tomo
Jurnal Ilmiah SINUS Vol 21, No 1 (2023): Vol. 21 No. 1 Januari 2023
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v21i1.681

Abstract

The Pelem Village Head Office has several government aids that will be distributed to its citizens. One of the acceptances of “Program Keluarga Harapan” (PKH) in 2019 has several criteria such as the elderly, people with disabilities, pregnant women and dependent children. However, officers have difficulty in processing the data. The purpose of this thesis is to create a decision support system for the selection of beneficiaries of “Program Keluarga Harapan” (PKH) assistance in Pelem Village using the Exponential Comparison Method (MPE). The results of this study are in the form of a decision support system program that has been tested through functional testing of the system using the blackbox testing method. The results of the testing process with the User Acceptance Test (UAT) of the respondents agreed (70%) that the overall decision support system for the recipients of RTLH assistance could assist officers as needed.
Deteksi Wajah Bermasker Menggunakan Deep Neural Network dan Tensorflow Rian Dwi Yulian Prakoso; Sriyati Sriyati; Nabil Makarim; Farrel Witamajaya
Jurnal Ilmiah SINUS Vol 21, No 1 (2023): Vol. 21 No. 1 Januari 2023
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v21i1.629

Abstract

The use of face masks is an important part of life in the midst of the Covid-19 pandemic which has been designated as a global pandemic, people are urged to cover their faces when in public areas to avoid the spread of the virus. The use of these face masks has raised serious questions regarding face detection systems. This study used Deep Neural Network and Tensorflow methods to detect faces both using masks and without masks. This study used two datasets, a face collection dataset without a mask and a face group using a mask. The result of this study was the detection of faces with masks trained on the dataset achieved 98% accuracy in training, and for testing got 100% accuracy on faces without masks, and 99.99% accuracy for face with mask. 
Analisis Perbandingan Hasil Pengolahan Citra Asli Dan Cropping Untuk Mengidentifikasi Karakteristik Tanaman Selada Menggunakan Metode Morfologi Dan Ekstrasi Ciri akhmad fadjeri; Lisna Kurniatin; Dicki Kusuma Adri Ariyanto; Bayu Aji Saputra
Jurnal Ilmiah SINUS Vol 21, No 1 (2023): Vol. 21 No. 1 Januari 2023
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v21i1.664

Abstract

Penelitian ini bertujuan untuk mengetahui hasil perbandingan  tanaman selada menggunakan metode morfologi dan ekstrasi ciri dari proses kroping pada citra dan citra asli. Teknik kroping merupakan teknik memperkecil ukuran citra. Sedangkan citra asli merupakan citra hasil dari tangkapan alat citra digital. Pada pengolahan citra digital terdapat teknik atau metode morfologi pada citra. Sebelum tahap morfologi, citra akan di proses menggunakan 2 metode yaitu metode kroping pada citra dan citra asi atau tanpa kroping. Setelah proses kroping atau tanpa kroping citra di olah menjadi citra abu-abu (grayscale), selanjutnya citra akan di proses menggunakan deteksi tepi untuk memperoleh hasil bagian tepi pada citra. Kemudian citra diubah menjadi bentuk biner (0 dan 1) atau sering disebut citra biner. Setelah pengolahan citra digital selesai kemudian tahap morfologi, dimana terdapat proses dilasi dan erosi. Proses ini bertujuan untuk mempertebal dan menipiskan hasil citra atau untuk meningkatkan hasil pendeteksian pada citra atau objek. Tahap selanjutnya yaitu proses ekstrasi ciri, dimana proses ini bertujuan untuk memperoleh nilai matematis pada sebuah citra.Proses ekstrasi ciri pada citra dilakukan sebanyak dua kali yaitu ekstrasi ciri citra asli dan ekstrasi ciri citra kroping. Dari hasil ekstrasi dapat diperoleh nilai matematis citra dengan ketentuan luas, keliling, kebundaran, kerampingan, panjang dan lebar. Proses ekstrasi ciri yang pertama atau citra asli didapatkan nilai matematis dengan rentang atau rata-rata luas 51.667.147.953.650.600, keliling 58.594.529.654.404.700, kebundaran 1.000.149.515.265.920, kerampingan 30.741.557.873.547.900, panjang 3.496.560.371.093.740 dan lebar 8.489.952.148.437.490. Sedangkan  proses  ekstrasi ciri kroping pada citra didapat nilai matematis citra dengan rentang atau rata-rata luas 83.364.228.960.567.300, keliling 26.081.033.779.659.700, kebundara 10.002.171.123.342.300, kerampingan 41.652.085.165.818.800, panjang 27.072.842.968.749.900 dan lebar 7.598.551.957.031.240.
Aplikasi Pengukuran Penggunaan Prebiotik untuk Tanaman Jagung di Kabupaten Aceh Utara Menggunakan Metode Fuzzy Tsukamoto Berbasis Web Angga Pratama; Maulida Hasbi; Ananda Faridhatul Ulva
Jurnal Ilmiah SINUS Vol 21, No 2 (2023): Volume 21 No. 2 Juli 2023
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v21i2.707

Abstract

Corn, along with rice and wheat, is one of the world's most significant food crops. Crop failures are a common concern for farmers, and one of the causes is the use of unsuitable fertilizers, which can limit the growth of organs and plant structure as a whole. Because good corn plant growth and high yields require the use of good and appropriate fertilizer for corn plants, this system is designed to recommend fertilization for plants based on the variables required by plants, namely soil pH, air temperature, humidity, rainfall, rainy days, altitude area, solar radiation, and land area, as determined by the agricultural service. Where each value is calculated using a specified set of each criterion, namely little, medium, and high. The outcomes of these computations are the final result of this decision system, namely suggestions for fertilizer usage in liters to assist farmers in analyzing fertilizer use for corn plants in North Aceh District. As in prior works, Tsukamoto's fuzzy technique is applied in this decision-making system to handle data values with a very high level of uncertainty or ambiguity.
Application of K-Mean in Clustering Mapping of Underprivileged Communities Iwan Ady Prabowo; Sri Siswanti; Lilis Wulandari
Jurnal Ilmiah SINUS Vol 21, No 2 (2023): Volume 21 No. 2 Juli 2023
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v21i2.734

Abstract

Jatiyoso is one of 17 sub-districts in Karanganyar Regency, Central Java Province. Through this sub-district office, residents can take care of various forms of permits. There are many other functions and duties of the subdistrict office. The distance from the county seat is 30.0 km to the south. Jatiyoso is divided into 9 village areas, namely, Jatisawit, Jatiyoso, Karangsari, Petung, Tlobo, Wonokeling, Wonorejo, and Wukirsawit. With the total population of Jatiyoso District is 40,709 people. With a large population, and also a large amount of poverty. To help reduce poverty in Jatiyoso District, Jatiyoso District, an information system is needed that can explain the mapping of poverty areas in Jatiyoso Village. This information system is expected to assist the government in distributing aid to the poor. K-Means method was applied in this study to overcome the problem of grouping poor families by category.  According to the findings of study, there were 23 groups of persons with low assets (C1) and four groups of people with substantial assets (C2). The findings of the feasibility testing process with the User Acceptance Test (UAT) respondents agreed (average 95%) that the application of mapping the clustering of poor people using the k-means method can help officers in mapping the poor and facilitate the distribution of aid to the poor in Jatiyoso village
Klasifikasi Biji Kopi Berdasarkan Bentuk Menggunakan Image Processing dan K-NN Akhmad Fadjeri
Jurnal Ilmiah SINUS Vol 21, No 2 (2023): Volume 21 No. 2 Juli 2023
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v21i2.726

Abstract

Temanggung Regency is the largest coffee producing area in Central Java. Robusta and Arabica are two types of coffee grown in this area. The manual method of sorting coffee beans is still used so the results are more subjective. Therefore, we require a system for categorizing coffee beans so that the results are more objective and reliable. This study uses K-NN classification and morphological features to recognize coffee beans based on the type and shape of the coffee bean defects. This aim of this study discovers which characteristics are better at classifying coffee beans into four categories (whole Robusta, whole Arabica, Robusta broken, and broken Arabica). A total of 110 coffee bean photos were used, with 80 images as training data, 40 images as test data, and a total of five morphological features.Our findings reveal that morphological traits may classify coffee beans into four categories with an accuracy of 62.5%, which is very good for detecting 100% whole Robusta and 90% Arabica but remains weak for recognizing broken coffee beans by type. Lean performs better in distinguishing coffee beans based on four classes, with a 70% accuracy. Morphological features outperform color features in distinguishing coffee beans based on shape defects, with an accuracy score of 83%. 
Comparison of Response Time Database RDBMS with NoSQL on Electronic Medical Records (EMR) Erwin Apriliyanto
Jurnal Ilmiah SINUS Vol 21, No 2 (2023): Volume 21 No. 2 Juli 2023
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v21i2.746

Abstract

The electronic medical record is a system for storing and managing patient medical data in electronic form. EMR replaces traditional medical record systems that still use paper, allowing doctors and other medical personnel to access patient medical records more quickly and easily from anywhere, as long as they are connected to the same network. In the EMR, patient medical data is stored in electronic format, such as text, images, and test results. EMR allows doctors to create patient medical records, make drug prescriptions, place laboratory orders and radiology orders, and access other patient medical data in one centralized system. EMR can also enable doctors to perform data analysis to gain insight into a patient's health condition and improve the treatment provided. In this study, the ERM database is used, with one database using PostgreSQL and the other using NoSQL. The purpose of this research is to test the speed performance of PostgreSQL and NoSQL with insert, select, and delete commands. Testing Method Using 1,000 records, 5,000 records, and 10,000 records, with each record being tested three times, and then taking the average, The results of this study are that the NoSQL database insert command has a speed of 3,900 times faster than the PostgreSQL database with 1,000 data records, whereas with 5,000 data records the NoSQL database is 471 times faster, while with 10,000 data records the NoSQL database is 355 times faster, and the select command for 1 NoSQL database table is 8 times faster than the PostgreSQL database, while for the above 1 PostgreSQL database table is faster.
Sistem Pengambilan Keputusan Penentuan Kualitas Biji Kopi Ekspor Menggunakan Metode TOPSIS dan VIKOR (Studi Kasus : Biji Kopi Ekspor Pada Tiap Koperasi) Angga Pratama; Rizki Mela Kurnia; Veri Ilhadi
Jurnal Ilmiah SINUS Vol 21, No 2 (2023): Volume 21 No. 2 Juli 2023
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v21i2.689

Abstract

Coffee, which has grown to be one of the most popular traditional plantation crops, contributes significantly to the economics of a coffee-producing region. Central Aceh, Bener Meriah, and Gayo Highlands are three of Indonesia's largest coffee-producing districts. A number of standards must be met in order for coffee beans to be regarded high grade and fall into the category of quality beans. TOPSIS and VIKOR methods were utilized in this research to develop a decision support system for assessing the quality of exporting beans. This system generates a rating as an output based on input values and weights, with weight values that can be adjusted by the chosen criteria. The purpose of this research is to develop software for grading coffee beans based on user input such as bean flaws, water volume, bean size, bean color, and aroma. Moreover, after two methods had been evaluated, TOPSIS method with the results of Gayo Permata cooperative with Grade 1 Arabica Gayo Coffee was recognized as the most effective method. Based on the results of KBQ Baburrayan cooperative using Arabica Gayo Coffee, TOPSIS is closer to the ideal solution than the VIKOR approach.
Ekstraksi Fitur Rantai Markov untuk Klasifikasi Famili Protein Toto Haryanto; Rizky Kurniawan; Sony Muhammad; Aziz Kustiyo; Endang Purnama Giri
Jurnal Ilmiah SINUS Vol 21, No 2 (2023): Volume 21 No. 2 Juli 2023
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v21i2.748

Abstract

As complex molecules, proteins have various roles for living things. Proteins are organic molecules formed from twenty amino acid combinations with various functions for living things, such as transportation systems, a catalyst of chemical reactions for metabolism, and food reserves. This research aims to classify proteins family based on sequences of amino acids as the primary structure. There are 300 amino acid fragments obtained from the Pfam database. The proteins family database subset with three sub-sample classes was obtained, including 1-cysPrx_C, 4HBT, and ABC_Tran. In this research, the first and second order of the Markov chain for extracting features were applied. Moreover, we use a Probabilistic Neural Network (PNN) as a classifier compared to the joint probability technique with Markov assumptions. We evaluate the results by comparing the sensitivity and specificity of both classification techniques. The evaluation results show that overall, PNN has slightly better performance than the joint probability technique for classifying protein families.

Page 26 of 27 | Total Record : 263

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