Articles
<![CDATA[Analisa Denyut Jantung Menggunakan Aplikasi Mobile Self Integrated BioInformatics System ]]>
<![CDATA[Rani Purbaningtyas]]>
<![CDATA[ Jurnal Teknologi Informasi dan Terapan Vol 6 No 2 (2019) ]]>
Publisher : <![CDATA[Jurusan Teknologi Informasi Politeknik Negeri Jember ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.25047/jtit.v6i2.113
<![CDATA[Heart disease is still ranked first in the WHO most dangerous and deadly disease in the world. This is also influenced by the individual's reluctance to check his heart condition routinely. So we need an application that is able to help overcome this. SIBioS application is a mobile-based application that functions to analyze heart rate. SIBioS is useful to help with the initial diagnosis of the presence or absence of cardiovascular disorders in individuals. The method applied for data analysis in SIBioS applications is case-based reasoning. Each heart rate data obtained will be calculated the degree of closeness of the distance to the heart rate contained in the knowledge base owned. So that the individual's heart rate can be informed. The test results show SIBioS is able to provide information about the status of the heart condition tester in accordance with the real condition of the tester at the time of measurement. In addition to using the right data analysis method, the results of heart rate data analysis are also influenced by the smartwatch device which is used as a media for tapping heart rate data, gender, age, daily physical activity, individual professional status, and supporting factors when measuring the resting heart rate. Case-based reasoning analysis methods can be applied to heart rate analysis to determine the condition of a person's heart under normal conditions or the presence of cardiovascular disorders. The physical activity recommendations given by the system are determined based on the individual's heart condition.]]>
<![CDATA[Penerapan Metode Profile Matching Pada Proses Seleksi Rekrutmen Pegawai Berdasarkan Faktor Kompetensi Spencer ]]>
<![CDATA[Rani Purbaningtyas]]>
<![CDATA[ Jurnal Teknologi Informasi dan Terapan Vol 8 No 1 (2021) ]]>
Publisher : <![CDATA[Jurusan Teknologi Informasi Politeknik Negeri Jember ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.25047/jtit.v8i1.227
<![CDATA[One of the keys to the company's success is how to place the right people in the right positions. For this reason, the recruitment selection process plays a significant role. This study applies the Profile Matching method to the employee recruitment selection process for the marketing director position. The prerequisites for occupying the position of marketing director are based on 20 Spencer competency factors divided into 6 competency groups with varying weights. The Spencer competency groups used along with the weight variations are Achievement and Action (AA) – 30%, Helping and Human Service (HHS) – 5%, Impact and Influence (IMIN) – 10%, Managerial (MNG) – 30%, Cognitive (COG) – 15% and Personal Effectiveness (PE) – 10%. The results showed that the employee on behalf of Sigit Hernowo was the strongest candidate for the Marketing Director position with a score based on the Spencer competency factor of 4.46 points.]]>
<![CDATA[KLASIFIKASI TUMOR OTAK MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK DENGAN ARSITEKTUR EFFICIENTNET-B3 ]]>
<![CDATA[Rachmad Andre Ramadhani]]>;
<![CDATA[Baghas Wahyu Pangestu]]>;
<![CDATA[Rani Purbaningtyas]]>
<![CDATA[ JUST IT : Jurnal Sistem Informasi, Teknologi Informasi dan Komputer Volume 12 No 3 Tahun 2022 ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Jakarta ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.24853/justit.12.3.55-59
<![CDATA[Tumor otak merupakan penyakit yang ditandai dengan pertumbuhan sel yang tidak normal pada jaringan otak. Salah satu cara yang dapat dilakukan dokter dalam pendeteksian tumor otak yaitu pengamatan langsung dengan diagnosis secara manual yang memiliki resiko terjadinya kesalahan. Perkembangan kecerdasan buatan terhadap computer vision saat ini sudah diterapkan dalam klasifikasi citra pada bidang kesehatan. Penelitian ini melakukan klasifikasi citra tumor otak menggunakan deep learning, khususnya metode Convolutional Neural Network (CNN) dengan arsitektur EfficientNet-B3 serta melakukan hyper-parameter optimization untuk membangun model terbaik yang diterapkan dalam bentuk sistem. Dataset yang digunakan berjumlah 2875 gambar dengan kelas glioma dan meningioma yang diperoleh dari kaggle. Pengujian dilakukan dengan beberapa skenario dari learning rate serta kombinasi dari jumlah neuron pada dense layer. Hasil dari pengujian model dengan confusion matrix, mendapatkan akurasi tertinggi pada eksperimen dengan skenario learning rate 0.02 dan neuron pada dense layer berjumlah 256 yang menghasilkan akurasi mencapai 99.7% dan mendapatkan nilai F1-Score tertinggi mencapai 99.6%. Penerapan model terbaik yang dirancang dalam bentuk sistem berhasil melakukan prediksi terhadap jenis tumor glioma, meningioma, dan pitutary]]>
<![CDATA[Study Program Classification System Informatics Engineering of Ubhara Surabaya ]]>
<![CDATA[Wahyu Dyah Rizki Septiana]]>;
<![CDATA[Eko Prasetyo]]>;
<![CDATA[Rani Purbaningtyas]]>
<![CDATA[ JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 5 No. 1 (2020): JEECS (Journal of Electrical Engineering and Computer Sciences) ]]>
Publisher : <![CDATA[Fakultas Teknik Universitas Bhayangkara ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (255.907 KB)
|
DOI: 10.54732/jeecs.v5i1.98
<![CDATA[One indicator to improve the quality of a university is the number of students who graduate on time. But the problem that often occurs at Bhayangkara University in Surabaya is the number of students entering and the number of students graduating unbalanced. Therefore this research was made to classify the period of study of students by using variables in the form of social studies semester 1-4, school origin, work status, morning / evening class status, and sex. This study aims to classify the length of time a student studies on time or late using the naïve bayes method. The results of this study indicate that the system is able to classify training data and test data on experiments conducted in each batch, the highest accuracy results are 59% and the lowest accuracy results are 56%.]]>
<![CDATA[Decision Support System for Evaluation of Java Learning in Elementary School (SD) Using Cummulative Voting Method ]]>
<![CDATA[Fajrul Islam]]>;
<![CDATA[Rani Purbaningtyas]]>;
<![CDATA[Syariful Alim]]>;
<![CDATA[Rifki Fahrial Zainal]]>
<![CDATA[ JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 5 No. 1 (2020): JEECS (Journal of Electrical Engineering and Computer Sciences) ]]>
Publisher : <![CDATA[Fakultas Teknik Universitas Bhayangkara ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (213.553 KB)
|
DOI: 10.54732/jeecs.v5i1.101
<![CDATA[Javanese is a language used by Javanese ethnic groups in Central Java and East Java, learning Javanese should be done by Javanese people to carry on the language of ancestral heritage so that Javanese language will not disappear in the future. To support effective and flexible learning tools, learning evaluations are needed so that teachers know the extent of students' understanding of Javanese language, the purpose of this research is to make it easier for students to learn Javanese in the learning process and in order to make teachers evaluate. From these problems led to the idea to create a web-based application in which it can carry out an accurate assessment process using the Cumulative Votting method with a Likert Scale. The programming language uses PHP and the database uses MySQL. From the test results using a Likert Scale manual values tested at 3 places found the results, namely, Gresikan Village Elementary School students get an interval value of 67.5% with a "Good" Scale, Rautlatul Jannah Islamic Elementary School students get an interval value of 61.5% with a "Good" Scale, SDIT Nurul Fikri Students get an interval value of 61.5% with a "Good" Scale.]]>
<![CDATA[Determination of The Best Location Garden of Public Reading (TBM) in Surabaya Using the Method Analysis Overlay and AHP ]]>
<![CDATA[Dzulfikar Revelation Rosyidi]]>;
<![CDATA[Rani Purbaningtyas]]>;
<![CDATA[Fardanto Setyatama]]>
<![CDATA[ JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 5 No. 1 (2020): JEECS (Journal of Electrical Engineering and Computer Sciences) ]]>
Publisher : <![CDATA[Fakultas Teknik Universitas Bhayangkara ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (582.386 KB)
|
DOI: 10.54732/jeecs.v5i1.103
<![CDATA[The growth of organizations in the field of literacy is very good for the development of children's interest in reading and insight at an early age, especially in the city of Surabaya. Taman Bacaan Masyarakat (TBM) is an organization that has an important role to support and facilitate the community in seeking knowledge in the field of literacy in particular. The addition of TBM in Balai RW, Kelurahan, Kecamatan, and in the corners of community crowds is a tangible manifestation of the role of the Surabaya City Library and Archives Service as the authority that intersects directly in the field of literacy to facilitate the reach of the public in finding quality sources of information. However, several technical factors influence the selection of TBM addition locations that are still very objective. And the limited budget for the establishment of TBM also affects the number of TBM founding locations]]>
<![CDATA[Evaluation of Understanding of Safety, Health and Safety (K3) Using the Method Cumulative Voting (case Study of PT. Kencar Sukses Investama) ]]>
<![CDATA[Wildansyah Rokhmana Putra]]>;
<![CDATA[Rani Purbaningtyas]]>;
<![CDATA[Eko Prasetyo]]>
<![CDATA[ JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 5 No. 1 (2020): JEECS (Journal of Electrical Engineering and Computer Sciences) ]]>
Publisher : <![CDATA[Fakultas Teknik Universitas Bhayangkara ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (718.858 KB)
|
DOI: 10.54732/jeecs.v5i1.107
<![CDATA[Every employee who works must understand safety in order to create a conducive work environment and Zero Accident. This study aims to create an Evaluation System for Understanding Safety, Health and Safety (K3) by using the Cumulative Voting Method so that it can optimize the quality of K3 in the company to be more effective and efficient. From the application trial results obtained the results of the validity test between manual data and application data have a difference in the results because the manual workmanship is calculated with a manual averagewithout any cumulativevalue of each item being tested. Application of K3 Comprehension Evaluation with Cumulative Voting Method can also prevent or minimize user input errors.]]>
<![CDATA[Disease Diagnosis System in Appel Plant Using Backward Chaining Method ]]>
<![CDATA[Rifki Fahrial Zainal]]>;
<![CDATA[Rani Purbaningtyas]]>;
<![CDATA[Dina Zahrotul Fadhilah]]>
<![CDATA[ JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 4 No. 2 (2019): JEECS (Journal of Electrical Engineering and Computer Sciences) ]]>
Publisher : <![CDATA[Fakultas Teknik Universitas Bhayangkara ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (1927.369 KB)
|
DOI: 10.54732/jeecs.v4i2.108
<![CDATA[Apples are one type of food that contains nutrients, vitamins and minerals that are very good for consumption because it has antioxidants that are good for the body. However, in cultivating these apple plants there are many obstacles, especially when the plant is attacked by disease. Diseases that attack apple plants greatly affect fruit production, because it can produce bad fruit and can result in the death of apple trees. The disease attack can be resolved quickly if it is able to identify the type of disease that attacks it quickly and precisely based on the symptoms that appear. So that the impact can be minimized as early as possible. The purpose of this research is to build an expert system of diagnosing diseases in apple plants by using the backward chaining method that can facilitate in providing information about the causes of the emergence of diseases and how to deal with apple plants quickly and accurately. From the application trial results with the Expert Diagnosis System in Apple Plant Diseases Using the Backward Chaining Method, users can find out the symptoms of diseases experienced by apple plants and test results by making comparisons using the forward chaining method the results are the same as backward chaining accuracy level of 100 % input from backward chaining is the same as output from forward chaining.]]>
<![CDATA[Forecasting of Total Stock Raw Materials of Double Exponential Smoothing Method (study: PT. Charoen Pokphand Indonesia) ]]>
<![CDATA[Rani Purbaningtyas]]>;
<![CDATA[Rahmawati Febrifyaning Tias]]>;
<![CDATA[M. ZAINAL ABIDIN]]>
<![CDATA[ JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 4 No. 2 (2019): JEECS (Journal of Electrical Engineering and Computer Sciences) ]]>
Publisher : <![CDATA[Fakultas Teknik Universitas Bhayangkara ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (484.179 KB)
|
DOI: 10.54732/jeecs.v4i2.109
<![CDATA[Inventory control at a company is very important in determining the efficiency of warehouse functions. Uncertain information about the availability of goods in the warehouse affects the decision to be taken in determining the amount of ordering goods. So that it has difficulty in predicting stock in the next month. The negative effect in the future if one predicts the stock will experience excessive stock build up. This study aims to create an application that can help facilitate and maximize the performance of warehouse administration employees in predicting the number of goods that must be ordered for the next period. Forecasting method used is the double exponential smoothing method. This method requires data information in previous years so that in this study took data 4 years earlier. With this forecasting method the forecasting results are obtained close to the actual data. From the results of testing the system imposed on 3 data obtained a system accuracy of 60%.]]>
<![CDATA[Online Based Academic Information System (case Study: SD. Hidayatur Rohman Asemrowo Surabaya) ]]>
<![CDATA[Rifki Fahrial Zainal]]>;
<![CDATA[Rani Purbaningtyas]]>;
<![CDATA[Mustofa]]>
<![CDATA[ JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 4 No. 2 (2019): JEECS (Journal of Electrical Engineering and Computer Sciences) ]]>
Publisher : <![CDATA[Fakultas Teknik Universitas Bhayangkara ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
Full PDF (1353.976 KB)
|
DOI: 10.54732/jeecs.v4i2.110
<![CDATA[The influence of technology is very large, especially in the development of information. Accurate, fast, and precise information is very important for life today because information becomes a necessity in conveying something. The use of computers is one of the developments in information that is very useful because it can perform data processing, making reports and sending information remotely and in determining the potential of students. Determination of the potential is absolutely necessary by the school agency, namely the school, the guidance teacher has an important role in granting status to students. Determination of student potential requires special professional handling, because it involves the success of students in facing the examinations that will be given. Mistakes in determining students' readiness to face national exams can negatively affect the process and results of student exams themselves. So we need a method that can help minimize the impact of mistakes when determining the potential of these students, namely by grouping data techniques from the results of data mining. The need for data mining becauseof the large amount of data that can be used to produce useful information and knowledge. Naïve Bayes is a machine learning method that uses probability calculations. The use of this algorithm is considered appropriate because Naive Bayesian Classifier is one classification algorithm that is simple but has high capability and accuracy.]]>
