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INDONESIA
JURNAL SISTEM INFORMASI BISNIS
Published by Universitas Diponegoro
ISSN : 20883587     EISSN : 25022377     DOI : -
Core Subject : Economy, Science,
Computer Science & IT Economics, Econometrics & Finance
JSINBIS merupakan jurnal ilmiah dalam bidang Sistem Informasi bisnis fokus pada Business Intelligence. Sistem informasi bisnis didefinisikan sebagai suatu sistem yang mengintegrasikan teknologi informasi, orang dan bisnis. SINBIS membawa fungsi bisnis bersama informasi untuk membangun saluran komunikasi yang efektif dan berguna untuk membuat keputusan yang tepat waktu dan akurat. Business intelligence sebagai dasar pengembangan dan aplikasi SINBIS menjadi kerangka kerja teknologi informasi yang sangat penting untuk membuat agar organisasi dapat mengelola, mengembangkan dan mengkomunikasikan aset dalam bentuk informasi dan pengetahuan. Dengan demikian SINBIS merupakan kerangka dasar dalam pengembangan perekonomian berbasis pengetahuan.
Arjuna Subject : -
Articles 12 Documents
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Search results for , issue "Vol 13, No 2 (2023): Volume 13 Nomor 2 Tahun 2023" : 12 Documents clear
Perancangan Media Informasi Sentra Wisata Kuliner Wonorejo di Kota Surabaya Berbasis Website Menggunakan Metode Model View Controller Iqbal Ramadhani Mukhlis
Jurnal Sistem Informasi Bisnis Vol 13, No 2 (2023): Volume 13 Nomor 2 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss2pp143-153

Abstract

Surabaya possesses considerable potential for economic growth and the tourism industry. The Surabaya City Government is actively harnessing this potential, one of which involves establishing the Culinary Tourism Center to introduce a variety of traditional Surabaya cuisine. Specifically, the Surabaya City Government has initiated the creation of the Wonorejo Culinary Tourism Center (SWK) to showcase the iconic Surabaya dishes. In pursuit of this objective, an information platform, based on a website, has been developed using PHP programming technology and a MySQL database, employing the Model View Controller approach supported by the CodeIgniter framework. This website is intended to furnish information about the diverse Surabaya dishes accessible at the Wonorejo Culinary Tourism Center to the local community and visitors from beyond Surabaya. The research process encompasses various methodologies, including literature review, observation, interviews, and surveys. The research findings, which encompass both internal and external testing, indicate a success rate of 80.67%. These results signify that this information platform is a valuable tool for facilitating the acquisition of information about the legendary and other culinary offerings available at SWK Wonorejo, benefiting visitors from Surabaya and beyond.
Analisis Interaksi Guru dan Peserta Didik dengan Social Network Analysis yang Menumbuhkan Minat Belajar di SMK Negeri 1 Tengaran Joko Listiawan Sukowati; Ade Iriani; Irwan Sembiring
Jurnal Sistem Informasi Bisnis Vol 13, No 2 (2023): Volume 13 Nomor 2 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss2pp88-95

Abstract

School is a place where students gain knowledge and as a place where the process of interaction between teachers and students occurs.. The interaction between teachers and students greatly influences the learning interests of students. This study aims to find teachers and indicators that influence students' interest in learning in the school environment using Social Network Analysis (SNA). The research was conducted at Tengaran 1 Public Vocational School with the research object being teachers and class XI students. The results showed that the most dominant actor or teacher in degree centrality, which was chosen by the students, was the actor or teacher with the Cp code, with a value of 26. The next step after calculating the SNA and measure network is indicator validation and classification using Naïve Bayes. The results of the indicator validation show that the validation value for each indicator is more than 0.5, so the indicators can be said to be valid. The classification results using naïve Bayes, with a dataset divided by 80% training data and 20% test data showing an accuracy of 85%. It is hoped that the results of this research can be input to teachers so that in schools they are more active in participating in various kinds of activities held by schools, and are active in interacting with students in the teaching and learning process. So, it is hoped that students will be more active in learning.
Backmatter (Publication Ethics, Copyright Transfer Agreement for Publishing Form) Prof Mustafid
Jurnal Sistem Informasi Bisnis Vol 13, No 2 (2023): Volume 13 Nomor 2 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

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Analisis Sentimen Terhadap Pengaruh Minat Belanja Berdasarkan Komentar di Marketplace Menggunakan Metode Recurrent Neural Network (RNN) Gerry Santos Lasatira; Kristoko Dwi Hartomo; Irwan Sembiring
Jurnal Sistem Informasi Bisnis Vol 13, No 2 (2023): Volume 13 Nomor 2 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss2pp112-119

Abstract

Product reviews on the marketplace can provide useful information if they are properly processed. Product review analysis can be performed by merchants to obtain information that can be used to evaluate products and services. It is not enough to look at the number of stars in product review analysis activities; it is also necessary to look at the entire contents of the review comments to determine the intent of the review. This can be done manually in small quantities, but in large quantities, the system is more efficient. In order to understand the intent of the reviews, a system that can effectively analyze many reviews is required. Using the Recurrent Neural Network (RNN) method, this study aims to analyze sentiment on the influence of shopping interest based on comments in the marketplace. The RNN model is trained to recognize positive and negative sentiments using data from the marketplace. The sentiment analysis results will be used to assess the impact on user shopping interest in the marketplace. Sentiment analysis was performed in this study using the RNN method in the GRU/LSTM training model with epochs. The researcher determined the epoch to achieve high accuracy. The data used for model training and testing is separated into training and testing data before it is used. A comparison of 80% of training data and 20% of test data is used to split data. This study uses a training model with 77 epochs and a batch size of 128 to create a system that automatically calculates comment sentiment in the marketplace with a 100% accuracy value and determines positive and negative sentiments.
Komparasi Algoritme Random Forest dan XGBoosting dalam Klasifikasi Performa UMKM Moh Erkamim; Suswadi Suswadi; Muhammad Zidni Subarkah; Erni Widarti
Jurnal Sistem Informasi Bisnis Vol 13, No 2 (2023): Volume 13 Nomor 2 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss2pp127-134

Abstract

The Covid-19 pandemic has greatly impacted the whole world, especially Indonesia. Various policies have been implemented starting from the implementation of lockdowns, restrictions on large-scale economic activities, and bans from leaving the region. The economic sector is a sector that has been affected quite a lot, one of which is Micro, Small, and Medium Enterprises (MSMEs). As a result of the Covid-19 pandemic, many MSMEs have suffered losses, so many investors have started to consider investing in MSMEs. Therefore, MSMEs need to know their business performance through potential analysis and financial reports to deal with the economic crisis during a pandemic. This study compares two algorithms namely Random Forest and XGBoosting in classifying the good or bad performance of MSME financial conditions. The performance of the developed algorithm will be improved using hyperparameter tuning to obtain the best parameter combination for each algorithm. In this study, the Random Forest algorithm has an accuracy value of 0.944 and an f1-score of 0.944, while the XGBoosting algorithm has an accuracy value of 0.944 and an f1-score of 0.950. Based on the model with the best evaluation metric, six important features are obtained: the 2021 profit and loss variable, 2020 cash, 2020 liabilities, 2020 capital, 2021 sales, and 2021 liabilities.
Prediksi Penjualan Bisnis Rumah Properti Dengan Menggunakan Metode Autoregressive Integrated Moving Average (ARIMA) Jefri Junifer Pangaribuan; Fanny Fanny; Okky Putra Barus; Romindo Romindo
Jurnal Sistem Informasi Bisnis Vol 13, No 2 (2023): Volume 13 Nomor 2 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss2pp154-161

Abstract

Abstract - Sales forecasting plays an important role in determining the company's strategy in the future because it allows control of planning and availability of home production according to consumer needs. Forecasting accuracy provides significant advantages for companies, including production cost savings and avoidance of unnecessary costs. Without accurate forecasting, a company will face difficulties in determining the quantity of house production, which can have a negative impact on the company's financial balance if the houses do not sell. This research implements the Autoregressive Integrated Moving Average (ARIMA) model to forecast property business house sales with a high level of accuracy to support future business decisions. The results of the research on the application of the Autoregressive Integrated Moving Average algorithm show that the ARIMA model (9,1,10) provides good forecasting results measured by the lowest AIC and BIC values compared to the other 4 models, namely ARIMA (10,1,9); ARIMA(8,1,9); ARIMA(10,1,10); and ARIMA (12,1,12) accompanied by an evaluation of measuring the accuracy of the model using RMSE, MSE, and MAPE with each value of 0.281409; 0.079191 and MAPE of 3.4% so that it can be said that sales forecasting provides a good level of accuracy.Abstrak - Prediksi penjualan memegang peran penting dalam menentukan strategi perusahaan di masa depan karena memungkinkan pengendalian perencanaan dan ketersediaan produksi rumah sesuai dengan kebutuhan konsumen. Keakuratan prediksi memberikan keuntungan signifikan bagi perusahaan, termasuk penghematan biaya produksi dan menghindari biaya yang tidak perlu. Kesulitan dalam menentukan jumlah produksi rumah tanpa prediksi yang tepat dapat berdampak negatif pada keseimbangan keuangan perusahaan jika rumah tidak terjual. Penelitian ini mengimplementasikan model Autoregressive Integrated Moving Average untuk melakukan prediksi penjualan bisnis rumah properti dengan tingkat akurasi yang baik untuk dapat mendukung keputusan bisnis kedepannya. Hasil penelitian pada pengaplikasian algoritma Autoregressive Integrated Moving Average menunjukkan bahwa model ARIMA (9,1,10) memberikan hasil nilai prediksi yang baik diukur dari nilai AIC dan BIC yang paling rendah dibandingkan 4 model lainnya yaitu ARIMA (10,1,9); ARIMA (8,1,9); ARIMA (10,1,10); dan ARIMA (12,1,12) disertai evaluasi pengukuran keakuratan model dengan menggunakan RMSE, MSE, dan MAPE dengan masing-masing nilai yaitu 0.281409; 0.079191 dan MAPE sebesar 3.4% sehingga dapat dikatakan prediksi penjualan memberikan tingkat akurasi yang baik.
Pengukuran Prestasi Belajar Mahasiswa Berdasarkan Prediksi Nilai Menggunakan General Linear Model Dina Fitria Murad; Bambang Dwi Wijanarko; Silvia Ayunda Murad; Vina Septiana Windyasari
Jurnal Sistem Informasi Bisnis Vol 13, No 2 (2023): Volume 13 Nomor 2 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss2pp135-142

Abstract

The Covid-19 pandemic is an international disaster experienced by almost all countries in the world. Several research results reveal the special impact of the pandemic on the education sector. Not only lecturers and students, but higher education providers also experience the same thing. Various adjustments were made so that all parties involved were able to adapt properly. It's been two years since the pandemic among us and during that time the learning process has continued. Based on this, several institutions began to take steps that raised questions about whether the learning achievement targets in each subject could still be achieved. This study aims to predict student grades using several machine-learning algorithms. The prediction results are a measure to find out whether learning outcomes have been achieved or not, if not achieved then additional steps need to be taken to help students. The results of this research are expected to help UNIS to prepare appropriate learning models for its students and ensure that all learning achievement targets are achieved. The research method used is a technique of machine learning. The results of this study indicate that the General Linear Model is a classification model with the best accuracy, which can be used to predict student achievement in certain classes based on the evaluation scores of the first structured activity (EKT1), midterm exams, grades (UTS), and second structured activity evaluation scores (EKT2). And it turns out that the UTS score has the greatest influence between EKT1 and EKT.
Peran Digital Entrepreneurship Mindset: Keputusan Adopsi Platform Digital Bagi Pelaku Bisnis Dewi Widyaningsih; Edwin Zusrony; Hardi Utomo
Jurnal Sistem Informasi Bisnis Vol 13, No 2 (2023): Volume 13 Nomor 2 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss2pp162-171

Abstract

The research was conducted to analyze the influence of developing a digital entrepreneurship mindset as an impact of facing digital transformation for MSME actors by considering digital aptitude factors, digital literacy. Non-random sampling techniques were taken by 120 MSME actors and questionnaire distribution techniques by convenience sampling. Data analysis method to determine the relationship between variables with multiple linear regression and path analysis test (sobel test), data was processed using the IMB SPSS 25 application. Finding the results of digital aptitude t count 5,531 and digital literacy tcount 4,419 > ttable1,980 (level sig. 5%) have a significant effect on DEM and all simultaneous variables 47% influence the development of digital entrepreneurship mindset. Digital aptitude tcount 5,531 and digital literacy tcount 3,215> 1,980 have a significant effect on digital platform adoption decisions and variables simultaneously by 55% have an influence on adopting digital platforms. Meanwhile, the results of the DEM pathway test were significantly able to mediate the influence of digital aptitude Zhitung = 2 and digital literacy Zhitung = 2.854> 1.96 on digital platform adoption decisions.
Implementasi Metode Fuzzy AHP untuk Sistem Pendukung Keputusan Peminjaman pada Koperasi Kredit Sejahtera Muhammad Galih Wonoseto; Muhammad Yolan Alfiandy
Jurnal Sistem Informasi Bisnis Vol 13, No 2 (2023): Volume 13 Nomor 2 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss2pp104-111

Abstract

Koperasi Kredit Sejahtera is a cooperative engaged in savings and loan services in the Bogor area. One form of KKS service to employees is by providing loan funds to help solve financial problems for employees. The problem faced by KKS so far is that decision-making activities in lending are still inadequate which results in non-performing loans or bad debts because the cooperative does not have a special system for decision making. Based on the problems that occur, researchers will build a decision support system that can handle credit problems using the Fuzzy AHP method using 9 criteria, namely salary, term, other loans, membership status, expenses, accuracy of previous payments, work, loan purpose and loan amount so that it can help the cooperative in determining the provision of loans to prospective creditors quickly, precise and accurate according to the ranking of the fuzzy AHP calculation results. Blackbox testing is carried out to test the achievement of the functional requirements of the system which shows that the functional requirements are met 100% of the total 8 functional consisting of 5 functional on admin actor and 3 functional on officer actor can be done/valid. UAT testing is used to test the achievement of non-functional requirements. By conducting a questionnaire to 16 respondents, the result is 100% valid and reliable. So that 100% of non-functional needs are successfully met.
Pengembangan Sistem Informasi Inspeksi Kesehatan Lingkungan Rumah Sehat Berbasis Website Ranindyta Elda Cintya
Jurnal Sistem Informasi Bisnis Vol 13, No 2 (2023): Volume 13 Nomor 2 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss2pp172-178

Abstract

Pengawasan terhadap kondisi kesehatan rumah dilaksanakan melalui kegiatan inspeksi kesehatan lingkungan rumah yang dilakukan oleh sanitarian puskesmas. Namun, Dinas Kesehatan selaku koordinator pelaporan data masih kesulitan mendapatkan informasi yang berkualitas dari pelaksanaan kegiatan inspeksi kesehatan lingkungan rumah tersebut. Adanya keterlambatan pelaporan, kesulitan akses dan update data, risiko ketidakuratan data, dan pelaporan yang kurang lengkap menjadi beberapa permasalahan di sistem pencatatan dan pelaporan data yang saat ini digunakan. Tujun penelitian ini adalah untuk mengembangkan sistem informasi inspeksi rumah sehat untuk memantau pencatatan dan pelaporan data serta evaluasi kinerja sanitarian puskesmas. Metode yang digunakan dalam penelitian ini menggunakan metodologi FAST (Framework for the Application of System Thinking) yang terdiri dari tahapan studi pendahuluan, analisis masalah, analisis kebutuhan, analisis keputusan, perancangan, konstruksi, dan implementasi. Sistem informasi inspeksi rumah sehat menghasilkan output laporan berupa tabel yang meliputi laporan rekapitulasi hasil penilaian rumah sehat, laporan progres penilaian rumah sehat per kelurahan, dan laporan rumah yang tidak memenuhi syarat sehat untuk berbagai level manajemen.  

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