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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 26 Documents
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Search results for , issue "Vol 6 No 3 (2025): April 2025" : 26 Documents clear
Pemodelan Attack Tree Pada Spear Phishing Attack di Instansi Publik dengan Metrik Granularitas Data Pratiwi, Anisa Wahyu; Widjajarto, A.; Budiyono, Avon
Journal of Information System Research (JOSH) Vol 6 No 3 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i3.5876

Abstract

Data security is important to protect personal and sensitive information. Data leakage cases that have occurred in Indonesia have recorded that 80% of Indonesian citizens' data is sold on dark forums (dark web), this will certainly cause losses to individuals and organizations. Factors that cause data leaks can be the lack of security protocols, direct attacks, or phishing attacks. One type of phishing attack that targets more specific individuals is called a spear phishing attack. This research aims to identify potential data leakage from public data in public institutions by formulating an attack tree based on the Data Flow Diagram (DFD) of a spear phishing attack using data granularity metrics with a combination of attacks from Open Source Intelligence (OSINT) tools, social engineering tools, and email spoofing. This research generates and compares four attack tree models with no attack launching or exploitation. First OSINT TheHarvester, social engineering SEToolkit, and email spoofing. Second OSINT Metagoofil, social engineering ZPhisher, and email spoofing. Third OSINT Recon-ng, social engineering SEToolkit, and email spoofing. The fourth OSINT Snov.io, social engineering ZPhisher, and email spoofing. Spear phishing attack using OSINT Snov.io is the best attack combination because it has varied data details, namely getting five types of data and a high level of data granularity with a total of 367 data so that there are more opportunities to carry out attack planning and security analysis.
Aplikasi Identifikasi Gaya Bahasa Sarkasme Dalam Lirik Lagu Berbasis Mobile Menggunakan Support Vector Machine Algoritma Masengi, Julio Joseph Victor; Frans, Rycko Giovann Leon; Taju, Semmy Wellem
Journal of Information System Research (JOSH) Vol 6 No 3 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i3.6103

Abstract

In the digital era, with the widespread use of social media, the use of sarcasm in song lyrics often presents a unique challenge in the interpretation process. One issue is the difficulty in detecting sarcastic language due to its implicit nature and dependence on context. Conventional methods often fail to capture this complex language pattern, which may lead to misunderstandings. This research aims to develop a mobile-based application capable of identifying sarcasm in song lyrics using the Support Vector Machine (SVM) algorithm. The application is designed to detect sarcasm in song lyrics, which is often hard to identify accurately through traditional methods. The development process includes several stages, such as data collection, pre-processing song lyrics data, applying the Term Frequency-Inverse Document Frequency (TF-IDF) method, and feature extraction. A sarcasm keyword dataset containing 600 data points with sarcasm elements and a general song lyrics dataset without sarcasm elements were collected and used for machine learning model training. The processed data is then classified using Support Vector Machine (SVM), which categorizes the analysis results into two main categories: sarcasm and non-sarcasm. The proposed classification model demonstrates performance with an Accuracy of 98.14%, Sensitivity of 96.13%, Specificity of 100%, and MCC of 0.9645, indicating a strong ability to distinguish between sarcastic and non-sarcastic language. This research aims to enhance users' understanding of song lyrics, especially on social media, to reduce misunderstandings related to sarcasm. It is hoped that this research can contribute to the development of technology for understanding sarcastic language in song lyrics.
Kajian Metode Analisis Spektral Pada Peramalan Curah Hujan Zega, Putri May Sari; Mardiningsih, Mardiningsih
Journal of Information System Research (JOSH) Vol 6 No 3 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i3.6694

Abstract

Rainfall is an important element in climate research, and its analysis requires appropriate approaches to reveal seasonal patterns and periodicity. This research aims to explore the application of the spectral analysis method in rainfall forecasting using monthly rainfall data from Serdang Bedagai Regency for 10 years (January 2014 – December 2023) totaling 120 data. The method used is harmonic analysis, a Fourier approach to extracting frequency information from time series data. This research began with data visualization, stationarity testing using the Phillips-Perron test, to spectral analysis involving calculations of Fourier coefficients and periodograms to detect dominant frequencies. The results show that the data has a periodic component with the highest frequency at 0.524, which is equivalent to a 12 month period. These results indicate the existence of seasonal patterns in rainfall data, which is relevant to support more accurate climate forecasting models. The implications of this research include the use of spectral analysis as a reliable method for identifying periodicity and building seasonal pattern-based forecasting models, which can be applied in various studies related to climate change and its mitigation.
Perancangan dan Implementasi Sistem Keamanan Pada Brankas Menggunakan Paralel Fingerprint dan Keypad Berbasis Arduino Al Rafif, Muhammad Roid; Paniran, Paniran; Wiriasto, Giri Wahyu
Journal of Information System Research (JOSH) Vol 6 No 3 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i3.6787

Abstract

Safe security plays an important role in protecting valuable assets from unauthorized access. Designing and implementing a security system on a safe using a parallel combination of two fingerprint sensors and a keypad. This is to increase the level of security by ensuring that both fingerprint sensors verify the fingerprint simultaneously before the user enters the code via the keypad to open the safe. The system controller uses an Arduino Mega as the main microcontroller, which connects two fingerprint sensors, a 4x4 keypad, a 16x2 LCD to display information, a 1 channel relay to drive the solenoid door lock as an actuator, and a buzzer as a warning indicator. The system testing scenario consists of three stages, namely, Electronic relay testing is carried out to ensure that the relay functions properly in controlling the solenoid door lock, so that the locking and opening mechanisms of the safe can run according to command. Testing on parallel fingerprints aims to evaluate the accuracy and speed of the sensor in reading two fingerprints simultaneously and ensuring that only registered fingerprints can access the system. Furthermore, keypad testing is carried out to verify the accuracy in reading the access code and testing the warning system in the event of an input error or unauthorized access attempt. The implementation results show that the system has a fingerprint authentication success rate of 98%, with an average response time of 1.2 seconds. The keypad reading accuracy reaches 99%, while the safe locking and opening mechanism functions with a 100% success rate. With these results, the developed system is proven to work reliably and provide additional protection compared to conventional methods.
Aplikasi Pengelola Keuangan Pribadi Berbasis Android dengan Pendekatan User Centered Design (UCD) Triwidadi, Kurniawan Adhisukma; Widodo, Tri
Journal of Information System Research (JOSH) Vol 6 No 3 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i3.6841

Abstract

Financial management plays a very important role in everyday life. Proper management can help one in organizing and controlling expenses. In the process of financial management, people should prioritize basic needs first. However, it is often difficult to distinguish between primary, secondary, and additional needs, which ultimately risks creating a consumptive culture, which is the habit of buying things that are not really needed. One solution to overcome this is to design an application that can help manage finances, equipped with features that limit spending if it exceeds the balance of income or if non-primary expenses exceed 20% of total income. In this research, the approach used is User Centered Design (UCD) which focuses on meeting the needs of users in using the application. The application was also tested using the Black Box method and obtained a 100% success percentage. The features of classifying and recording needs greatly facilitate users in managing finances. The results of the study can provide benefits for users in managing finances, especially in managing primary needs, so that they can manage finances more effectively.
Analisis Perbandingan Metode Random Forest dan Adaptive Boosting Untuk Prediksi Leukemia dengan Data Microarray Heremba, Juleha Irianti; Suhendra, Christian Dwi; Sanglise, Marlinda
Journal of Information System Research (JOSH) Vol 6 No 3 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i3.6898

Abstract

Cancer is the uncontrolled growth of cells that spread to other parts of the body. There are different types of cancer that are named after the organ they originate from. One of them is blood cancer or leukemia, which is bone marrow cancer caused by genetic mutations. According to data from Global Cancer Statistics in 2020, there were an estimated 19.3 million new cancer cases and 10 million cancer deaths, and it is estimated that by 2040 it will increase globally by 47% from 19.3 million to 28.4 million new cancer cases. Leukemia is one type of cancer with the ninth rank in Indonesia in 2020, there are 14,979 new cases and 11,530 cases of death caused by leukemia. One of the efforts to prevent leukemia can be done by diagnosing the acute leukemia category using DNA and genetic information. The purpose of this study is to analyze the comparative performance between Random Forest and Adaptive Boosting methods in predicting leukemia types using microarray datasets to determine which method is more effective in performing classification. In this study, the dataset used is gene expression in bone marrow and blood consisting of two categories of acute leukemia, namely Acute Myeloid Leukemia (AML) and Acute Lymphoblastic Leukemia (ALL) obtained with DNA microarray technology. These genes will be classified using Random Forest and Adaboost methods to predict acute leukemia categories. The results of the analysis process show that the random forest method is a better method for predicting acute leukemia with an Area Under Curve value of 100%, Accuracy 92.9%, Precision 93.7%, Recall 92.9%, and F1-Score 92.7% compared to the AdaBoost method with an Area Under Curve value of 83.3%, Accuracy 85.7%, Precision 88.6%, Recall 85.7%, and F1-Score 85.1%.
Klasifikasi Siswa Slow Learner Menggunakan Algoritma C4.5 Dalam Optimalisasi Pembelajaran di Sekolah Menengah Pertama Gloria, Bela Priska; Hidayati, Rahmi; Hasfani, Hirzen
Journal of Information System Research (JOSH) Vol 6 No 3 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i3.6932

Abstract

Education is a learning process aimed at enhancing students' abilities in the school environment. SMP Negeri 12 Sungai Ambawang is one of the educational institutions located in Sungai Ambawang District. In the learning process, each student has a different level of understanding of the material being taught. Some students struggle to grasp lessons at the same pace as their peers, which categorizes them as slow learners. Lack of awareness about slow learners can hinder the teaching and learning process, as teachers must repeatedly explain the material. Therefore, this study aims to identify and classify slow learners using the C4.5 machine learning algorithm to help schools design more effective and adaptive learning strategies. The classification of slow learners is divided into four categories: normal, mild, moderate, and severe. The dataset consists of 135 data points, including 81 training samples and 54 testing samples. The attributes used include scores from subjects such as Civics (PKN), Indonesian Language, Mathematics, Natural Sciences (IPA), Social Sciences (IPS), and English. The C4.5 algorithm generates a decision tree with Natural Sciences (IPA) as the root node attribute. Testing using the Confusion Matrix shows an accuracy of 91%, precision of 54%, recall of 68%, and an error rate of 9%. The classification results indicate that 9% of students fall into the normal category, 24% into the mild category, 62% into the moderate category, and 0% into the severe category. These results demonstrate that the C4.5 algorithm is effective in classifying slow learners.
Penerapan Data Mining Menggunakan K-Means Clustering Dalam Mengelompokkan Tingkat Kesulitan Mata Pelajaran Fauji, Fahrul; Farokhah, Lia
Journal of Information System Research (JOSH) Vol 6 No 3 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i3.6959

Abstract

SMA Kertanegara Malang is committed to providing and improving the quality of education to its students. One of the main challenges that is often faced is that there are certain subjects that students consider difficult. Difficult subjects often become an obstacle for students to achieve satisfactory grades. One approach that can be taken is Data Mining. The analysis technique used is the K-Means algorithm, Clustering method. The Elbow method helps in determining the right number of clusters for the data that has been processed. The results of the Elbow method in this research are the most optimal cluster value, namely K= 3 based on the Within-Cluster Sum Of Square value of 104.5298167. The data used are the report cards of class The aim of this research is to determine what groups of subjects are considered difficult. The research results after 163 data were transformed into 30 data obtained 3 optimal clusters using the Elbow method, namely Cluster_1 with a difficult subject category containing 8 subjects. Cluster_2 with the medium difficulty level lesson category contains 10 subjects. Cluster_3 with the easy lesson category contains 12 subjects. The results of this grouping can be used by teachers at SMA Kertanegara Malang to provide more assistance to students, especially in subjects that are categorized as difficult.
Sistem Informasi Manajemen Jemaat Berbasis Web Untuk Meningkatkan Efisiensi Pelayanan Gereja Pantekosta Serikat di Indonesia Oktavianus, Yohanes; Riadi, Aditya Akbar; Evanita, Evanita
Journal of Information System Research (JOSH) Vol 6 No 3 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i3.6961

Abstract

Managing congregation data and church activity schedules manually often leads to errors or possibly data loss such as, limited access to information, and potential recording errors. The purpose of this research is to develop a custom-made web-based congregation and church schedule management information system to support service efficiency at GPSDI Juwana. The system includes the ability to manage church data, activity schedules, and real-time reports that can be accessed by administrators and authorized users. The system was developed using the “waterfall” development methodology through the phases of requirements analysis, design, implementation and testing. The test results show that the system can improve administrative efficiency, minimize data entry errors, and make information more accessible to all parties involved. The developed system can also reduce church administrators' errors when managing church data by 70%. The system aims to be an innovative solution that supports the digitalization of church worship today.
Penerapan Profile Matching Dalam Sistem Pendukung Keputusan (SPK) Pemilihan Lokasi Strategis untuk Pembukaan Cabang Usaha Darmansah, Darmansah; Harman, Rika; Amrizal, Amrizal
Journal of Information System Research (JOSH) Vol 6 No 3 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i3.6994

Abstract

Batam is one of the cities with rapid economic growth supported by business, trade, and attractions. Many businesses are currently trying to expand their business by opening new branches. However, strategic locations for opening new branches are still a big challenge. Many entrepreneurs only rely on intuition or personal experience when making decisions, without considering strategic factors systematically, which risks business failure. Therefore, a system is needed to assist in decision making when choosing the best location. The purpose of this study is to apply the Profile Matching method in a Decision Support System (DSS) to assist business owners in choosing strategic locations in Batam. This method is used to compare ideal location criteria with field conditions based on 5 factors, such as population density, accessibility, level of competition, rental prices, and community purchasing power. The results of the study indicate that the Profile Matching method is able to identify the best location by comparing the weights between the ideal location profile and actual location data. The most strategic places for opening a business are Nagoya, Lubuk Baja and Batam Center with the highest total scores of 4.00, 3.50 and 2.00. With the Profile Matching-based SPK, business actors can reduce the risk of errors in choosing a location and increase the chances of their business success in Batam.

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