Jurnal Informatika: Jurnal Pengembangan IT
The scope encompasses the Informatics Engineering, Computer Engineering and information Systems., but not limited to, the following scope: 1. Information Systems Information management e-Government E-business and e-Commerce Spatial Information Systems Geographical Information Systems IT Governance and Audits IT Service Management IT Project Management Information System Development Research Methods of Information Systems Software Quality Assurance 2. Computer Engineering Intelligent Systems Network Protocol and Management Robotic Computer Security Information Security and Privacy Information Forensics Network Security Protection Systems 3. Informatics Engineering Software Engineering Soft Computing Data Mining Information Retrieval Multimedia Technology Mobile Computing Artificial Intelligence Games Programming Computer Vision Image Processing, Embedded System Augmented/ Virtual Reality Image Processing Speech Recognition
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<![CDATA[Klasifikasi Helpdesk Menggunakan Metode Support Vector Machine ]]>
<![CDATA[Stefanie Hilda Kusumahadi]]>;
<![CDATA[Hartarto Junaedi]]>;
<![CDATA[Joan Santoso]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 1 (2019): JPIT, Januari 2019 ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v4i1.1125
<![CDATA[The online helpdesk with ticketing system with the help of operators often experiences problems such as inappropriate delegation processes, the duration of the helpdesk waiting time to be delegated, even the helpdesk is missed to be handled. The ticket delegation checked manually by the operator has risks creating an error in delegating helpdesk tickets to inappropriate technicians. The helpdesk classification system is needed so that every incoming helpdesk ticket can be classified to the right technician according to the job description. The incoming Helpdesk is classified into 6 types of requests, namely multimedia, documentation, internet, server, hardware, software and miscellaneous. This helpdesk grouping is needed so that related technicians for each helpdesk can work and help the helpdesk according to their respective job descriptions. The Support Vector Machine method is used to classify text on the helpdesk. The use of Linear and Polynomial kernels produces an accuracy of 78%, the RBF or Gaussian kernel produces the highest accuracy of 81% while the Sigmoid kernel produces the smallest accuracy of 51%. The helpdesk classification results with the Support Vector Machine method can produce quite good accuracy.]]>
<![CDATA[Sistem Prediksi Kebutuhan Obat di Puskesmas Menggunakan Metode Least Square ]]>
<![CDATA[Devit Suwardiyanto]]>;
<![CDATA[Mohammad Nur Shodiq]]>;
<![CDATA[Dedy Hidayat Kusuma]]>;
<![CDATA[Tovia Oktalita Sari]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 1 (2019): JPIT, Januari 2019 ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v4i1.1085
<![CDATA[The Puskesmas is a health service center at the first level in the community. Medication is an important requirement in health agencies, including health centers. The Puskesmas must provide medicine for patients for a period of a month. As well, the puskesmas also has to plan drug requests for the period of the following month. The problem that often arises is about drug supplies. If the demand for drugs is too much, it will cause the drug to be removed for a long period of time, so that it will result in drug expiration. Likewise, if the demand for drugs is too little then it becomes less good, which results in less optimal service to the community. During this time, planning for drug demand for use in the next period, still using instinctive techniques by the head of the health center of the puskesmas. So, this will lead to excess or even reduced drug supply. In this study a system that is able to predict future drug needs was built. The results of this prediction can be used as a reference for drug requests to the health department. The method used to predict is the Least Square method, while the system to control the upper and lower limits uses the Minimum Maximum Stock Level (MMSL) method. The test system for prediction errors in this study uses Mean Absolute Percentage Error (MAPE). This systems was implemented using the PHP language and visualized on a web-based basis. The system test results showed an average prediction error rate of 12.70%. The existence of this system is expected to be able to assist the planning process of drug needs in the future at the puskesmas.]]>
<![CDATA[Optimasi Keamanan Watermarking pada Daubechies Transform Berbasis Arnold Cat Map ]]>
<![CDATA[Abdussalam Abdussalam]]>;
<![CDATA[Eko Hari Rachmawanto]]>;
<![CDATA[Noor Ageng Setiyanto]]>;
<![CDATA[De Rosal Ignatius Moses Setiadi]]>;
<![CDATA[Christy Atika Sari]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 1 (2019): JPIT, Januari 2019 ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v4i1.911
<![CDATA[Digital image security using Transform Domain algorithms such as Discrete Wavelet Transform (DWT) has been widely used. To improve the security of the DWT algorithm needs to randomize the pixel coefficient, namely Arnold Cat Map (ACM). Computing ACM as one of the chaos functions is known to be fast and fits with Transform Domain. DWT has been implemented in the Daubechies filter which is the development of the Haar filer. In this paper, we proposed the message insertion model using a combination of DWT and ACM on a 512x512 piskel grayscale image and a 64x64 pixel message on the LL subband. The experiments were performed on 2 different images to determine the ability produced by the combined algroithm. The ability test for message insertion process is done through Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and comparation between original image histogram and image insertion histogram. While in the process of message extraction, algorithmic capability test is done by calculating Normalized Cross Correlation (NCC) and its correlation. The highest MSE result is 2.9502 and the highest PSNR is 43.4323 dB, while the NCC value is 237.3584 with correlation 0.7181.]]>
<![CDATA[Sistem Pendukung Keputusan Penilaian Kesehatan Tanah Dengan Metode Simple Additive Weighting ]]>
<![CDATA[Arief Kelik Nugroho]]>;
<![CDATA[Ipung Permadi]]>;
<![CDATA[Nofiyati Nofiyati]]>;
<![CDATA[Sri Hayyu Naufal Ulfa]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 1 (2019): JPIT, Januari 2019 ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v4i1.1034
<![CDATA[Soil is the most crucial factor in the management of agriculture. To measure and monitor soil health status, soil health assessments can be undertaken in the management of agricultural land that aims to determine whether the land is being or will be used in an area in a healthy condition and can perform its functions properly. The results of soil health assessments can also be used as a reference for agricultural land managers to set planning targets and implementing systems to practice soil health management by reducing identified constraints, and assisting land managers in searching agricultural land. Comprehensive soil health assessments can be undertaken based on soil health indicators which consist physical, chemical, and biological properties of the soil. But there is no definite standard for assessing soil health comprehensively, and people who know and understand soil health indicators are still minimal. The number of indicators in soil health assessments can also make it difficult for experts to assess the health of the soil. Therefore, it is needed a Decision Support System of Soil Health Assessment Using Simple Additive Weighting Method so that with this application, it is expected to assist the community especially those involved in agriculture in assessing soil health easily, and quickly, and obtain land health status of an area based on predetermined soil health indicators.]]>
<![CDATA[Analisis Value chain Dalam Desain Alert System Pengajuan Jabatan Fungsional Dosen ]]>
<![CDATA[Citra Wiguna]]>;
<![CDATA[Afandi Nur Aziz Thohari]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 1 (2019): JPIT, Januari 2019 ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v4i1.1249
<![CDATA[Information and communication technology (ICT) currently become one of the important things to increasing excellence in various fields, where one of field is education. Institut Teknologi Telkom Purwokerto (ITTP) is an educational institution that has a focus on ICT technology development.One of the ICT development conducted by ITTP is the existence of an alert system for submitting functional lecturer position. This alert system can produce competent lecturer and can pass the qualifications according to the rules set. In the construction of alert system, absolutely must be through desain, and corresponding with requirement and business process that exist in ITTP. Therefore in this study was conducted alert system design analysis for the submission of functional lecturer position. The analytical method that used is a Value chain which has been proven to increase the strategic step of the product. The result of this research is strength weakness analysis in the alert system design that useful for institution and also lecturer in order to improve the quality and level that is controlled and directed.]]>
<![CDATA[Implementasi Metode Promethee Dalam Sistem Pendukung Keputusan Penilaian Raport Dosen ]]>
<![CDATA[Dyah Apriliani]]>;
<![CDATA[Oman Somantri]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 1 (2019): JPIT, Januari 2019 ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v4i1.1251
<![CDATA[Assessment of lecturer report cards is a decision-making process using information obtained through measuring the results of lecturer performance by students and administrative completeness of each lecturer. The object used in this study is the Informatics Engineering IV Study Program using the promethee method. The Promethee method is used to obtain a ranking of grades from lecturers. Promethee's method of calculating requires several alternatives and criteria. The alternative used for assessment is the lecturer who teaches in the D IV Informatics Engineering Study Program. The criteria used to assess each alternative are lecturer assessment data by students which includes student assessment input taken from the final score or the average resulting from the questionnaire assessment filled in by students. Administrative appraisal data which includes: syllabus collection, collection of college contracts, modules, number of attendance, timeliness of UTS and UAS collection questions as well as the timeliness of collecting UTS and UAS scores. From this study, the assessment of lecturer report cards was obtained, which also included lecturer rankings based on the scores produced. System testing is done by comparing the results of manual assessment with the results of the assessment produced by the system. Based on the testing that has been done it can be concluded that the results of testing both manually and using the system are the same.]]>
<![CDATA[Penerapan Algoritma Pencarian Binary Search dan QuickSort pada Aplikasi Kamus Bahasa Palembang Berbasis Web ]]>
<![CDATA[Andri Andri]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 1 (2019): JPIT, Januari 2019 ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v4i1.1104
<![CDATA[Dictionaries can be used as a means to find meaning and meaning in a word. Palembang language is one of the regional languages in the province of South Sumatra. In their daily lives besides using Indonesian, the Palembang people also use the Palembang language as a means of communication with each other. This study aims to create a web-based Palembang language dictionary application so that it can be accessed using internet media. This dictionary application was created to help people who are not native to the city who live in the city of Palembang. This dictionary application provides a simple user interface that makes it easy for users to use it. In the development of this dictionary application is made using the RAD method. The search algorithm used in word search in a database is using the binary search method. The binary search method has the advantage of linear search. In practice binary search searches by first dividing into two data in a database that has been sorted first. This application can do an effective word search and the information displayed in this application in addition to the meaning and meaning of the word also provides an example of how to use the searched word in Palembang sentences.]]>
<![CDATA[Association rules of Prognostic Variables for Survival in a Randomized Comparison of Treatments for Prostatic Cancer ]]>
<![CDATA[Iing Lukman]]>;
<![CDATA[Emy Khikmawati]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 1 (2019): JPIT, Januari 2019 ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v4i1.1252
<![CDATA[In this paper, the data was analyzed by data mining techniques of association rules. The data for 506 patients consist of an identification number, stage of tumour, a code for the treatment to which the patient was assigned, the date of randomization, the total months of follow-up since randomization, an indicator for the survival status or cause of death, and the values of twelve pretreatment covariates. The goal of an analysis should be to compare the treatments with respect to survival of the patients. Since this was a randomized study it would ordinarily not be necessary to adjust for the values of the pretreatment covariates. However, in such studies it is advisable to examine the prognostic significance of the covariates and to confirm that they are balanced across treatment groups. In addition, the analyst should look for important treatment-covariates interactions which might lead to the definition of subsets of patients in which treatment differences were significantly more marked or even reversed.]]>
<![CDATA[Sistem Pendukung Keputusan Kelompok Untuk Menentukan Penerima AGC Award Menggunakan Metode Simple Additive Weighting dan Borda ]]>
<![CDATA[Arif Tirtana]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 1 (2019): JPIT, Januari 2019 ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v4i1.1062
<![CDATA[ PT. Astra International continues to develop into one of the leading group of companies in Indonesia. Currenty its manages six core business namely, automotive, financial, services, heavy equipment, mining, agro-business, infrastructure, logistics, and information techonology. In its operations can bring various impact on enviroment quality, such as the avalaibility of natural resources (water, energy and materials), waste generated in the form of solid, fluid, and air. Therefore ESR Division carry out an assessment of the subsidiary programs to minimize the impact. In this research using SAW method to support the decision making of individual decision, and Borda method to support the group decision making and to determine AGC Award recipient. The decision support system model proposed in this study has proven to solve problems that require individual or group decision-making processes.]]>
<![CDATA[Klasifikasi Jeruk Nipis Terhadap Tingkat Kematangan Buah Berdasarkan Fitur Warna Menggunakan K-Nearest Neighbor ]]>
<![CDATA[Cinantya Paramita]]>;
<![CDATA[Eko Hari Rachmawanto]]>;
<![CDATA[Christy Atika Sari]]>;
<![CDATA[De Rosal Ignatius Moses Setiadi]]>
<![CDATA[ Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 1 (2019): JPIT, Januari 2019 ]]>
Publisher : <![CDATA[Politeknik Harapan Bersama ]]>
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DOI: 10.30591/jpit.v4i1.1267
<![CDATA[In the process of classification of lime fruit previously done manually using the human eye is a very difficult thing to do. This is proven by being inconsistent and subjective, causing a low level of accuracy. Sometimes there are also differences of opinion from the human eye to one another. Therefore, to increase the level of accuracy and reduce the subjectivity of the human eye, this study proposes the K-Nearest Neighbor algorithm to classify the maturity level of lime based on the skin color of the lime. In this study, the K values used were 1, 3, 5, 7 and 9 to test the search for Euclidean distance and cityblock distance distances on images with pixel sizes of 512x512, 256x256 and 128x128. In the prerosesing stage, the extraction feature process uses mean RGB. The research that has been done proves that with Euclidean distance distance k = 3 and k = 7 has a percentage value of 92% and the cityblock distance distance k = 1 and k = 3 has a percentage value of 88%. Based on the level of accuracy possessed, the color feature k = 3 shows the best k value in the classification of the maturity level of the lime fruit.]]>
