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INDONESIA
Jurnal Informasi dan Teknologi
Published by Universitas Putra Indonesia YPTK Padang
ISSN : 27149730     EISSN : 27149730     DOI : https://doi.org/10.37034/jidt
Core Subject : Science,
Computer Science & IT
Jurnal Informasi & Teknologi media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian Rekayasa Sistem, Teknik Informatika/Teknologi Informasi, Manajemen Informatika dan Sistem Informasi. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada Masyarakat luas dan sebagai sumber referensi akademisi di bidang Teknologi dan Informasi.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
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Search results for , issue "2020, Vol. 2, No. 3" : 5 Documents clear
Penentuan Tingkat Kompetensi Soft Skill Mahasiswa Menggunakan Metode Analytical Hierarchy Process dan Promethee Hardiansyah Putra; Sumijan
Jurnal Informasi dan Teknologi 2020, Vol. 2, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v2i3.62

Abstract

Bureau of Student Advisory Center (BSAC) Universitas Pembangunan Panca Budi is a center for career development and character building for students. In this case, a soft skill seminar is conducted to find the best candidate employees in the field of recruitment offered based on the criteria of student soft skill training. Determining the level of soft skill competences of students using the Analytical Hierarchy Process (AHP) method and the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE). For decision support systems using the AHP and PROMETHEE methods in determining the level of soft skill competencies, in order to obtain prospective employees who have the required soft skill competency level. Data collection was carried out by conducting research. The data is taken from the seminar results with 100 participants. The data that has been collected, processed and analyzed before being used as input and output as a basis for learning or training using the AHP and Promethee methods. Based on the calculations of the two methods, namely the AHP and Promethee methods, there are differences in calculations. In other words, because Promethee does not support the determination of weights and the hierarchy of criteria and does not have the assurance of consistency when determining weights like AHP. So that the program execution has a different time in the results, in the AHP method, program execution until the final result is obtained is better than the Promethee method. AHP has advantages in determining weights and criteria hierarchy, while Promethee has advantages in the alternative ranking process using different preference and weight functions.
Clustering Students' Interest Determination in School Selection Using the K-Means Clustering Algorithm Method Suhefi Oktarian; Sarjon Defit; Sumijan
Jurnal Informasi dan Teknologi 2020, Vol. 2, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v2i3.65

Abstract

Education is one of the main focuses of the Indragiri Hilir Regency Government work program. Based on data from the Regional Central Statistics Agency of Indragiri district in 2019, the high level of student interest in attending school is at the elementary and junior high school levels. K-means clustering is a data grouping technique by dividing existing data into one or more clusters. School grouping based on student interest is important because at the high school level students' interest in education has decreased so that information is needed which schools are in great demand, sufficient interest and less interest by students at the junior high school level when after finishing elementary school education. This study aims to assist the Education Office in the decision-making process to determine which school students are most interested in as a reference in development both in terms of quality and quantity. The data used in this study is the Dapodikdasmen data in 2019.Data processing in this study uses the K-means clustering method with a total of 3 clusters, namely cluster 0 (C0) is less attractive, Cluster 1 (C1) is quite attractive, cluster 2 (c2) is very interested in students in choosing a school. The results of the clustering process with 2 iterations state that for cluster 0 there are 6 school data, for cluster 1 there are 3 school data, cluster 2 is 1 school data.
Data Mining dalam Akurasi Tingkat Kelayakan Pakai terhadap Peralatan Perangkat Keras Nurhidayat; Sarjon Defit; Sumijan
Jurnal Informasi dan Teknologi 2020, Vol. 2, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v2i3.67

Abstract

Hardware is a computer that can be seen and touched in person. Hardware is used to support student work and learning processes. The hardware should always be in good shape. If any damage should be done quickly. The benefits of this study provide a viable level of data against hardware tools. The purpose of this study determines that hardware that is worth using quickly and precisely so easily can be repaired and replaced. Hard-processed action consists of 12 projectors, 2 units of access point, 6 units of monitors, and 20 CPU units. To see the level of appropriateness regarding hard drives requires a rough set algorithm with that stage: information system; Decision system; Equivalency class; Discernibility matrix; Discernibility Matrix module D; Reduction; Generate Rules. The results of the 40 devices of study STMIK Indonesia Padang subtract college have 10 rules of policy on whether the hardware is still viable, repaired or replaced. So using a rough set algorithm is particularly appropriate to apply in a verifiable level of accuracy to fast and precise hardware. Keywords: Hardware, Decision System, Data Mining, Rules , Rough Set
Sistem Pakar Menggunakan Metode Certainty Factor untuk Mengidentifikasi Penyakit pada Hewan Peliharaan Fortia Magfira; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2020, Vol. 2, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v2i3.68

Abstract

Large domesticated types of ruminants such as goats, buffalo and cows are animals that are commonly kept and used as food sources and as assistants to human work in rural areas. Knowledge about pets, especially animal health, is something owners really need to keep their pets healthy. The owner's lack of knowledge about diseases and early handling of diseases in pets and the difficulty of seeing a veterinarian in urgent situations prevent pets from getting proper first aid. This study aims to identify the types of diseases suffered by pets based on the symptoms experienced by pets precisely. The method used is themethod Certainty Factor to accommodate the uncertainty of an expert's thinking on 12 diseases and 47 disease symptoms in pets. The results of this study can identify diseases in pets and produce certainty values ​​for the types of diseases in the form of diseases suffered by pets. So that this research can be a reference in identifying diseases in pets and providing knowledge to owners about first aid and disease management in pets.
Sistem Pakar Menggunakan Metode Certainty Factor dalam Akurasi Mengidentifikasi Penyakit Gingivitis pada Manusia Cyntia Lasmi Andesti; Sumijan Sumijan; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2020, Vol. 2, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v2i3.69

Abstract

Gingivitis is a common inflammatory disease of the gums, which is a condition where bacteria develop in the mouth that causes damage to the connective tissue cells that are attached to the teeth. Lack of awareness in caring for teeth will have a negative impact not only on dental health but also on the health of the body. At present many people do not know how to accurately identify gingivitis in humans so that the condition is worsened and can even cause the paralysis of the existing connective tissue. This study aims to determine the level of accuracy in identifying gingivitis by using the Certainty Factor method precisely and accurately. The data processed in this study are fifty data sourced from expert interviews at Rahmatan Lil Alamin Clinic, Padang Indonesia. There are several types Symptoms refer to gingivitis in humans. The data is obtained from the results of medical records of patients who carry out examinations in the clinic. The data will be processed to identify the type of gingivitis based on the direction of the expert. The processing steps are solving rules, determining the weight value of each symptom and calculating the Certainty Factor value. The results of the processing were continued by calculating the level of accuracy. The results of the testing of this method were that 96% of them had gingivitis, the type most often suffered by marginal gingivitis patients. Based on the signs entered by the user. The results of this test have been able to specifically identify gingivitis, using the Certainty Factor method, the results of the accuracy level obtained are quite accurate and can be recommended to help dentists improve their accuracy in identifying gingivitis in humans.

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