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INDONESIA
Scientific Journal of Informatics
Published by Universitas Ibrahimy
ISSN : 25497480     EISSN : 25496301     DOI : https://doi.org/10.35316/jimi
Core Subject : Science,
Computer Science & IT
Topics cover the following areas (but are not limited to): 1. Information Technology (IT) a. Software engineering b. Game c. Information Retrieval d. Computer network e. Telecommunication f. Internet g. Wireless technology h. Network security i. Multimedia technology j. Mobile Computing k. Parallel/Distributed Computing 2. Information Systems Engineering a. Development, management and utilization of Information Systems b. Organizational Governance c. Enterprise Resource Planning d. Enterprise Architecture Planning e. e-Bbusinnes f. e-Commerce 3. Business Intelligence a. Data mining b. Text mining c. Data warehouse d. Online Analytical Processing e. Artificial Intelligence f. Decision Support System g. Machine Learning
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 115 Documents
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Perbandingan Metode Klasifikasi Data Mining Untuk Deteksi Keaslian Lowongan Pekerjaan di Medsos Mohammad Malik Fajar; Annisa Rizkiana Putri; Khadijah Fahmi Hayati Holle
Jurnal Ilmiah Informatika Vol. 7 No. 1 (2022): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v7i1.41-48

Abstract

The COVID-19 pandemic has resulted in more and more people losing their jobs. Due to layoffs or bankrupt companies. This has resulted in many people looking for job vacancies. Job vacancies are circulating on social media but there are real and fake ones. Irresponsible people create job vacancies on social media with fraudulent purposes or for personal gain. So, a comparison of data mining classification methods was made for the detection of authenticity of job vacancies on social media. The method used is naive bayes, KNN, and decision tree. In order to find out which method has the highest accuracy value and can be used to classify the authenticity of job vacancies, and fraud on social media can be prevented. Based on this research, the method that has the highest accuracy value is the KNN method. The accuracy value is 94.93%, while the Decision Tree model has an accuracy value of 91.57% and the Naive Bayes model has an accuracy of 84.35%. The KNN method is the best method for classifying the authenticity of job vacancies.
Sistem Pendukung Keputusan Pemberian Bonus Karyawan Menggunakan Metode MOORA Bella Putri Hapsari; Saifur Rohman Cholil
Jurnal Ilmiah Informatika Vol. 7 No. 1 (2022): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v7i1.21-28

Abstract

In the current era of technology, computers are used to help facilitate human work. Among them by making a Decision Support System, by using a computerized system, the decision-making process can be right on target and more efficient. This research was conducted against the background of the need to give bonuses to employees, this bonus is given so that employees feel valued by giving rewards or additions for their good performance. In addition, the provision of employee bonuses also aims to increase employee morale so that employees provide better performance results, which can have a good impact on customer satisfaction. This study uses the MOORA method with the results obtained in the form of ranking the calculation of the value of employees who meet the criteria will receive bonuses. By using this decision support system, it is hoped that it will facilitate the decision making of employee bonus recipients.
Analisis Cloud Computing Untuk Penyimpanan Dokumen Terhadap Proses Pembelajaran Menggunakan Algoritma Regresi Linear Berganda (Studi Kasus : SMA Chandra Kusuma Jakarta Utara) Sukirman Sukirman
Jurnal Ilmiah Informatika Vol. 7 No. 1 (2022): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v7i1.1-12

Abstract

Obstacles in the learning process carried out by subject teachers and students of SMA Chandra Kusuma School, North Jakarta, because document storage is still low and internet access is still slow. Multiple linear regression algorithm to determine the relationship between cloud computing variables and the learning process on document storage variables. Simultaneously the F test results are 15.387 and the coefficient of determination is 36.30% so that there is a significant relationship between cloud computing and the learning process for document storage. Partially, cloud computing for document storage has a significant relationship because it has a t-value of 3.211 which is greater than t-table. And partially the learning process for document storage there is a significant relationship because it has a t-count value of 3.824 which is greater than t-table.
Analisis Akurasi Prediksi Perubahan Aktivitas Pada Sistem Monitoring Aktivitas Jarak Jauh Pasien Isolasi Mandiri Berbasis IOT Annisaa Sri Indrawanti; Muchammad Husni; Khakim Ghozali
Jurnal Ilmiah Informatika Vol. 7 No. 1 (2022): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v7i1.13-20

Abstract

Patients who contract the disease should avoid contact with other people. One way to do this is to self-isolate at home. The family of the patient who cares for the activities that are carried out in self-isolation to find out the condition of the patient's condition, his condition is improving or deteriorating. To avoid direct contact, the patient's activity, independently, can be monitored by remotely predicting changes in patient activity using an Internet of Things-based remote monitoring system for self-isolating patient activities. This cellular-based monitoring system uses an accelerometer sensor to retrieve data on changes in patient activity and analyzes the effect of several variations in the number of data samples and sliding-windows on the accuracy of the system in predicting changes in patient activity. Variations in the number of N samples tested were 4,6,8,10,20,30,40,50,60,70,80,90 and 100 samples, while the sliding-window N variation tested was 1 ,2,3,4,5,6,7,8,9 and 10 samples where there is a change in activity every 30 seconds for 330 seconds (10 changes in activity) for each number of N samples and N sliding windows. The results shown are N sample data = 6 providing the highest activity change prediction accuracy, amounting to 90.15%, while N sliding window data = 6 providing the highest activity change prediction accuracy, amounting to 92.72%.
Pemodelan Proses Bisnis Peternakan Ayam Petelur Lailatul Fadilah; Fadillah Siva; Muhammad Zaim Maulana; Muhammad Ainul Yaqin
Jurnal Ilmiah Informatika Vol. 7 No. 1 (2022): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v7i1.49-64

Abstract

Laying hens are all activities related to the production of laying hens from the chick stage to the adult stage. The business process of laying hens in general starts from the activities of the biosecurity system, breeding, rearing, housing, and the animal feed and health system. Based on three studies that have been carried out in the period 2017-2021, the business process of laying hens is still minimally modeled. The problem that arises when the laying hen's farm business process is not modeled is that many business activities are repeated and missed. Therefore, business process modeling needs to be done to improve coordination between process units. This research aims to model the business process of laying hens, which refers to Porter's value chain analysis. This study uses data taken from observations and interviews with local laying hens in Malang. The data used is related to details of business activities, the parties involved, and SOPs in the laying hens business. The method in this study uses the BPMN approach. This research begins with data collection, analysis of porter's value chains, analysis of the relationship between business processes, then denotes the process obtained with BPMN notation. This research produces a business process model for laying hens which BPMN denotes. This business process model can solve coordination problems in the laying hens business.
Implementasi Algoritma K-Nearest Neighbor (K-NN) dan Single Layer Perceptron (SLP) Dalam Prediksi Penyakit Sirosis Biliari Primer Annisa Nurba Iffah’da; Anita Desiani
Jurnal Ilmiah Informatika Vol. 7 No. 1 (2022): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v7i1.65-74

Abstract

Primary biliary cirrhosis is a chronic cholestatic liver disease that can lead to liver failure. The majority of individuals who suffer from this disease are women. Primary biliary cirrhosis is recorded as contributing to mortality worldwide with a percentage of 0.6% to 2.0%. However, so far, randomized trials have shown that some immunosuppressant or immunosuppressive drugs do not play a major role in patients with primary biliary cirrhosis. Therefore, early detection is important to start treatment and planning for appropriate medical needs. The results of the processing accuracy with the K-NN algorithm of 76.2% and the SLP algorithm of 63% using the Percentage Split method show that the K-NN algorithm is better for early detection of primary biliary cirrhosis. The K-Nearest Neighbor algorithm is able to perform early detection of primary biliary cirrhosis with a precision of 77% and recall of 75% with the hope that the percentage of mortality worldwide can decrease. However, the K-NN algorithm is not superior in retrieving information in patients with primary biliary cirrhosis. On the other hand, the SLP algorithm is superior in retrieving information in patients with primary biliary cirrhosis with a recall value of 65%.
Penerapan Algoritma K-Nearest Neighbor Untuk Klasifikasi Rumah Layak Atau Tidak Layak Huni (Studi Kasus: Desa Bulu Kecamatan Kraksaan Kabupaten Probolinggo) Deniyanto Muchlizin Wahidillah; Abu Tholib; Muafi Muafi
Jurnal Ilmiah Informatika Vol. 7 No. 2 (2022): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v7i2.75-84

Abstract

The house is a need that must be met, in addition to food and clothing needs, as well as an indicator of community welfare, to create a safe, comfortable and healthy living environment. The government provides social rehabilitation assistance to the community for uninhabitable houses by helping to buy building materials so they can rehabilitate homes that are not proper. In Bulu Village there are still many places to live that are categorized as uninhabitable houses. This is because of the community's income factor and limited knowledge about the function of the house, as well as facilities and infrastructure that make it increasingly difficult to realize livable dwellings. This research uses the K-Nearest Neighbor algorithm for the classification of decent or uninhabitable homes which aims to provide convenience in determining prospective recipients of social rehabilitation assistance for uninhabitable houses with accurate results and minimizing mistargeting. The results of this study are an average accuracy of 96.25% with a standard deviation of 5.73% in the 7th model test using 10-fold cross-validation with odd k and validation and evaluation of results with the confusion matrix getting an accuracy value of 100%, the precision value is 100%, the recall value is 100%, and the f-measure value is 100% with k = 13.
Sistem Pakar Untuk Mendeteksi Minat Dan Bakat : Sebuah Systematic Literature Review Hafiz Firdaus; Agung Susilo Yuda Irawan
Jurnal Ilmiah Informatika Vol. 7 No. 2 (2022): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v7i2.85-94

Abstract

We present a systematic literature review of an expert system to detect children's interests and talents. The purpose of this review is to plot all aspects of knowledge in the field of education, especially those using the expert system method, what children do in learning and how expert system methods can help in determining children's interests and talents. We conducted a systematic literature review of published studies that focused on the use of expert systems methods. The systematic review in this study is used to analyze how expert system methods can contribute massively to developments in the field of education. This research can also be used as a guideline for the most widely used expert system method to determine children's interests and talents. Research on determining children's talents and interests from 20 papers in a systematic literature review provides a broad understanding of the research conducted on what makes the system able to determine the best talents and interests for children through data obtained from experts
Analisis Sentimen Layanan Shopeefood Pada Twitter Dengan Metode K-Nearest Neighbor, Support Vector Machine, dan Decision Tree Muhammad Zaki Farhan
Jurnal Ilmiah Informatika Vol. 7 No. 2 (2022): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v7i2.95-106

Abstract

Sistem Informasi Jadwal Dan Pemesanan Tiket Keberangkatan Kapal Laut Di Pelabuhan Jangkar Berbasis Android M Syafiih; Nur Istifadah; Nur Hatima Inda Arifin
Jurnal Ilmiah Informatika Vol. 7 No. 2 (2022): Jurnal Ilmiah Informatika
Publisher : Department of Science and Technology Ibrahimy University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35316/jimi.v7i2.107-116

Abstract

The port is a place consisting of land and waters around it with certain as a place of economic activity and activities, the surrounding area becomes a place to lean, up and down passengers or unloading goods equipped with shipping safety facilities. Anchors Port which was built in 1986 to serve loading and unloading of passenger goods for alternative crossings connected between the island of Java and many islands and regencies in Madura, especially Kalianget and Sumenep districts (Sapudi, Raas and Kangean Islands), Anchors Harbor is located in Asembagus District, 35 km east of Situbondo, East Java Province. Ship transportation crossings at Anchors Situbondo port, sometimes not fixed with an uncertain departure schedule, departure schedules and ticket reservations are still made manually, namely from the bookkeeping and have not been equipped with information system devices to manage ship schedules. So from these problems, an android-based application was created that can be used as an android-based schedule information system and ticket booking for ship departures with the aim of making it easier for prospective passengers to find out departure schedules and ticket reservations. The method used is the waterfall method with flowchart, DFD and ERD tools so that the management of information systems is more systematic. The results of this test are to produce an android-based schedule information system application and ship departure ticket booking which shows a percentage of 90.6% with the category strongly agreeing to be used.

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