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JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 2686228X     DOI : -
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Artikel yang dimuat melalui proses Blind Review oleh Jurnal JOSH, dengan mempertimbangkan antara lain: terpenuhinya persyaratan baku publikasi jurnal, metodologi riset yang digunakan, dan signifikansi kontribusi hasil riset terhadap pengembangan keilmuan bidang teknologi dan informasi. Fokus Journal of Information System Research (JOSH)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 774 Documents
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Implementasi Design Thinking dalam Perancangan UI/UX Rumah Sampah Digital Banjarejo Yusril Febriyanto; Pristi Sukmasetya; Maimunah Maimunah
Journal of Information System Research (JOSH) Vol 4 No 3 (2023): April 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i3.3135

Abstract

Garbage is a very serious problem, where the growth of waste is increasing day by day. Both the government and the public need to care about the waste itself, without any intervention from all of us, the waste problem will continue to grow and be difficult to overcome. For this reason, a waste bank was created which is expected to be able to reduce the rate of waste growth, as was done in the village of Banjarejo. But unfortunately the management of the waste bank in Banjarejo village had stopped. This is due to the lack of commitment from the waste bank management, and the decline in public trust and motivation to participate in the waste bank program. The purpose of this research is to revive the waste bank in Banjarejo village by digitizing the waste bank into the Banjarejo Digital Garbage House (RSDB). This research focuses on designing the web design of the Banjarejo Digital Garbage House (RSDB). The results of this study can later be tested on prospective users and waste bank admins in order to obtain test results. With the existence of the RSDB web system, it is hoped that it will be able to facilitate and foster the interest of the Banjarejo village community in efforts to clean the environment. This design uses the Design Thinking method. In the Design Thinking method there are 5 steps that must be carried out to get an idea and a solution, namely Empathize, Define, Ideate, Prototype, and Testing. Testing carried out on the prototype uses the Single Ease Question (SEQ). The results of the average SEQ score from the waste bank admin are 6.2 – 7. Meanwhile the average SEQ value results from the waste bank customers are 6 – 7. It can be concluded that the UI/UX on the RSDB prototype is easy to understand and according to user needs.
Analisis Kesiapan Pemerintahan Kota Prabumulih Dalam Implementasi E-Government Menggunakan Metode Technology Readiness Index (TRI) Nisa Aprina Maris; Eka Puji Agustini; Megawaty Megawaty; Tri Oktarina
Journal of Information System Research (JOSH) Vol 4 No 3 (2023): April 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i3.3263

Abstract

E-government s an nformation technology system developed by the government to mprove public services by providing choices to the public to get easy access to public nformation. For this reason, socialization of e-government needs to be carried out consistently, continuously and with ncentives to the community because the community does not yet understand what and how e-government applications are and the benefits they can get. The problem that occurs at this time s that t s not known how far the level of readiness of the Prabumulih City Government s n the use and application of nformation technology, especially E-Government. Because of this, t s necessary to carry out an analysis or assessment of the readiness to apply nformation technology, n this case the Government of Prabumulih City. The solution offered s to carry out a readiness analysis using the TR method or Technology Readiness (TR) which s a person's tendency to want to use a new technology that aims to achieve everyday life or n the workplace. Meanwhile, the Technology Readiness ndex s an ndex used to measure the readiness of new technology users to achieve goals n everyday life and work. n order to support the Government of Prabumulih City to carry out eGovernment mplementation with the help of nformation and communication technology, t opens new opportunities to further explore nformation so that t can be utilized optimally. E-Government users cover a wide population, both for government, citizens and business people, so that n the end a mutually beneficial relationship s created. The results obtained from this study are Optimism has a value of 1.51, nnovativeness has a value of 1.24, Discomfort has a value of 0.69 and nsecurity has a value of 0.64. The total results show that the relevant agencies are ready to mplement technology.
Pengujian Jaringan Saraf Tiruan Dalam Mendiagnosa Gangguan Jiwa Menggunakan Algoritma Backpropogation Levenberg-Marquardt Solikhun Solikhun; Sundari Putri Lestari
Journal of Information System Research (JOSH) Vol 4 No 3 (2023): April 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i3.3285

Abstract

Mental disorders are mental health issues that make it hard to meet one's own or other people's needs. A person's life may be affected by changes in behavior brought on by this condition. To conquer this issue, a backpropagation calculation has been created to help with distinguishing mental problems. This calculation utilizes information got from mental tests to distinguish early indications of mental problems in an individual. With this calculation, psychological wellness experts can settle on additional quick and precise symptomatic choices. The Levenberg-Marquadt method and the backpropogation algorithm were used in this study to diagnose mental disorders. The aim of this study is to make it easier to diagnose mental disorders by analyzing a patient using the 24 attributes of the questions. After the diagnosis is made, the results will show up, and the Levenberg-Marquardt Backpropagation Algorithm will be used to test a person to see if they have bipolar disorder, OCD, or any other disorder. Researchers will have a difficult time determining the patient's mental illness if this diagnosis is not carried out. The aftereffects of this study are as demonstrative inquiries for mental issues that have been given. The Levenberg Marquadt method backpropagation algorithm is the bridge to accuracy, supporting this study's success. MSE is 24-10-1, with training performance equal to 0.000014246 and testing performance equal to 0.0000146. The diagnosis that comes out of it is more accurate the less error there is.
Implementasi Algoritma C.45 Dalam Memprediksi Kualitas Aset Kendaraan Kantor Chatarina Putri Salsabila; Aditya Wijayanto
Journal of Information System Research (JOSH) Vol 4 No 3 (2023): April 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i3.3316

Abstract

Badan Keuangan dan Aset Daerah (BKAD) of Banyumas Regency is an institution under a government position consisting of several sub-sectors, one of which is the Assets Sub-sector. The BKAD Regional Asset Sub-sector in Banyumas Regency has a type of Goods Inventory Card (KIB) that has not been managed properly, including KIB for office vehicles making it difficult to make a proposal for office vehicle maintenance. Maintenance of office vehicles is the initial stage of replacing vehicles according to employee needs so that employee performance can be maximized. Forecasts for office vehicle maintenance are presented to facilitate the implementation of duties in carrying out business trips. The methods used in data collection are survey methods, literature, and interviews. The data collection method used in this report uses a quantitative method with the C.45 algorithm. Predicting the quality of office vehicles can carry out several stages such as reviewing office vehicles, classifying the condition of office vehicles, after that a decision is made on which vehicles are suitable for use or not suitable for use. Analysis of predicting the quality of office vehicles using the C.45 algorithm with the rapidminer application can produce results in the form of a decision tree that is used by the asset sub-sector in order to make a decision. Based on the prediction results of office vehicle quality, it can be concluded that office vehicles will be suitable for use if the year of purchase or procurement is more than 2000 and office vehicles will not be suitable for use if the year of purchase or procurement is less than or equal to 2000. If you want to compare the results obtained it is advisable to use other tools or algorithms to make the next report.
Hoax Detection on Indonesian Tweets using Naïve Bayes Classifier with TF-IDF Ichwanul Muslim Karo Karo; Romia Romia; Sri Dewi; Putri Maulidina Fadilah
Journal of Information System Research (JOSH) Vol 4 No 3 (2023): April 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i3.3317

Abstract

Twitter is one of the most popular social media platforms in the world nowadays. Twitter users in Indonesia are the fifth largest in the world and are always active in expressing themselves and getting information through tweets. A hoax is a lie created as if it were true. Hoaxes are also often spread via tweets. The spread of hoaxes is extremely dangerous because it can cause social discord and even misunderstanding. Therefore, hoaxes must be resisted. This study aims to build a system to detect hoaxes on Indonesian tweets. The objective of this research is to identify hoax Indonesian tweets by using the Naïve Bayes classifier with Term Frequency Inverse Document Frequency (TF-IDF). This study collects and annotates tweets from hoax tweets post which sent by a user account. This study also applied several text preprocessing techniques to provide datasets. To provide the best hoax prediction model, this work splits datasets into training and testing datasets. There are four experimental scenarios that refer to splitting the dataset. The experimental results showed that the hoax prediction model using Naïve Bayes with TF-IDF had 64% accuracy and recall, 69% and 67% precision, and a F1-score respectively. This result is also superior to the hoax prediction model when using the Naïve Bayes classifier without the TF-IDF. It means that TF-IDF has made a positive contribution to improving model performance. Finally, this research contributes by detecting news with a proclivity for hoaxes and filtering what is classified as hoaxes or not.
Sistem Pakar Dalam Mendiagnosa Penyakit Parkinson Menerapkan Metode Dempster-Shafer Agus Iskandar
Journal of Information System Research (JOSH) Vol 4 No 3 (2023): April 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i3.3320

Abstract

After Alzheimer's disease, Parkinson's disease is the most common neurodegenerative condition affecting people. Millions of people, or about 1% of the world's population, are affected by Parkinson's disease. Parkinson's disease is a neurodegenerative condition of the central nervous system that affects the motor system and develops over time. Even though Parkinson's disease is an uncommon condition, a tool is created by utilizing an expert system to identify this condition from the symptoms experienced by the patient. Based on the user's perceived trust value, the expert system generates disease opportunities. The Dempster-Shafer approach technique is used to calculate the trust value. The Dempster-Shafer approach reduces uncertainty and results in a correct diagnosis. the result of the inclusion or deletion of new data, such as details about symptoms and disease. Under this approach, specialists are valued for the knowledge they possess. This method rewards professionals for the knowledge they possess. Dempster-Shafer This investigation will use a diagnostic approach to Parkinson's disease. Based on the results of the procedure for applying the Dempster-Shafer method, it was determined that the patient showed some symptoms of Parkinson's disease, and it was determined that the patient had stage 2 Parkinson's disease with an accuracy value of 0.944 or a percentage of 94%. An expert system with the Dempster-Shafer technique can be used to diagnose Parkinson's disease in patients or users by calculating the symptoms experienced by the patient, according to the results of calculations performed manually by the system.
Analisis Sentimen Ulasan Aplikasi WeTV Untuk Peningkatan Layanan Menggunakan Metode K-Nearst Neighbor Nurkholimah Faridhotun; Elin Haerani; Reski Mai Candra
Journal of Information System Research (JOSH) Vol 4 No 3 (2023): April 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i3.3349

Abstract

Online streaming applications are activities for watching movies that are very popular with the public, one of which is WeTV. WeTV is an online streaming that is used by the public as a medium of entertainment. The WeTV application has a rating of 4 out of 256 thousand reviews written by its users. The collection of reviews in the form of text can be collected and classified into negative responses, neutral responses, and negative responses. Positive responses are comments that are optimistic or supportive. Negative responses are comments on phrases or cases that do not support statements about related cases. Neutral responses are comments that are difficult to understand between negative or positive in nature to provide suggestions, sentences that have reviews from application users can be positive, negative and neutral, the data will go through a classification process using the K-Nearst Neighbor method. In this study, 12,000 reviews were used from the playstore. The research used the preprocessing stage, namely cleaning, case folding, tokenizing, normalization, stopword removal and steaming then to the TF-IDF stage and the final results will be tested with a confusion matrix using the Python programming language. The highest accuracy results from the testing process with a value of K = 3 in the dataset model 90% training data and 10% test data obtain an accuracy of 0.70%, precision 0.76%, recall 0.69%, f1-score 0.72% . Based on the results of the research that the K-Nearest Neighbor method is good in the process of identifying negative responses on WeTV.
Analisis Sentimen Ulasan Aplikasi Wetv Untuk Peningkatan Layanan Menggunakan Metode Support Vector Machine Rezky Abdillah; Elin Haerani; Reski Mai Candra
Journal of Information System Research (JOSH) Vol 4 No 3 (2023): April 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i3.3353

Abstract

Wetv is an online streaming media that has been running since 2019. Wetv has many user reviews from various applications. The rating consists of positive, neutral and negative. The response is used to determine sentiment by using the support vector machine classification method. This study took 12,000 comments from the Google Play Store, this study used preprocessing namely, cleaning, case folding, tokenizing, normalization, stopword removal, and steaming, then to the TF-IDF stage and the final results were tested with a fusion matrix with the Python program, the score results highest from the acquisition test process with accuracy of 0.76%, precision of 0.77%, recall of 0.79%, and f1 score of 0.78, in a dataset of 90% training data and 10% test data. Based on the research results of the Support Vector Machine method which is known to be good in the process of requesting negative responses on WeTV.
Analisa Sentimen Ulasan Aplikasi Wetv Untuk Peningkatan Layanan Menggunakan Metode Naïve Bayes Novi Lestari; Elin Haerani; Reski Mai Candra
Journal of Information System Research (JOSH) Vol 4 No 3 (2023): April 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i3.3355

Abstract

The most popular online streaming application is WeTV. WeTV is an internet-based streaming service that is used by the public as an entertainment medium. The WeTV application has been downloaded by up to 50,000 users. Application user ratings may affect the image of the application depending on the services provided by the application developer. Many positive, neutral and negative reactions have had a big impact on WeTV. Categorizing user ratings cannot be done manually because it is not easy with very large amounts of data. Therefore, the purpose of this research is to analyze the user rating of the WeTV application on the Goggle Playstore. In this study the processing steps consisted of cleaning, case convolution, tokenization, normalization, stopword and vape removal, after which it was continued with the TF-IDF step and the final result was a confused matrix using the Python programming language with Naive Bayes classifier. method in this research. Using 12,000 reviews found on Google Playstore. to generate positive, negative and neutral sentiments from Wetv application user comments in the play store. The test with the highest precision value of 0.64% with a -1 precision value of 0.58% in Class Recall gives a value of 0.89% in the 90%:10 balance model.
Implementasi Triple Exponential Smoothing dan Double Moving Average Untuk Peramalan Produksi Kernel Kelapa Sawit Risfi Ayu Sandika; Siska Kurnia Gusti; Lestari Handayani; Siti Ramadhani
Journal of Information System Research (JOSH) Vol 4 No 3 (2023): April 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v4i3.3359

Abstract

The production of palm kernel is a significant product for the company and plays a crucial role. Nevertheless, the stability of kernel production is not always consistent, and the quality of the kernel can be detrimental to the company. As consumer demands change over time, companies must anticipate every fluctuation in palm kernel production. Hence it is vital to figure the long run with a settlement prepare utilizing information mining utilizing information within the past. The Triple Exponential Smoothing and Double Moving Average methods, which are data mining methods for future forecasting, were used in this study. The aim of this research is to predict the yield of future oil palm kernel production using the Triple Exponential Smoothing and Double Moving Average methods and to determine the level of forecasting errors using the Mean Absolute Percentage Error (MAPE) method. The data for the last ten years, from January 2013 to December 2022, were used in this study. After testing the Triple Exponential Smoothing method with parameters α=0.2,β=0.γ=0.2, the error rate using MAPE was 9.48%, and the Double Moving Average method had an error rate of 11.2%. The MAPE results of the Triple Exponential Smoothing method are considered very good, while the MAPE results of the Double Moving Average method are categorized as good based on the range of MAPE values. This research is expected to provide information to related companies as a supporting reference in anticipating palm oil kernel production. The conclusion of the research is that the Triple Exponential Smoothing method with the test parameters is the best method for forecasting.

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