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Jurnal Penelitian Sistem Informasi
Published by INSTITUT TEKNOLOGI DAN BISNIS SEMARANG
ISSN : 29856310     EISSN : 29857759     DOI : 10.54066
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Sistem Pendukung Keputusan (DSS), Sistem Informasi Geografi (GIS), Perusahaan Skala Sistem Informasi (ERP, EAI, CRM, SCM), E-Commerce, E-Government, Sistem Informasi dari Rumah Sakit, Sistem Informasi Perbankan, Sistem Informasi Industri, Pengambilan Informasi, Keamanan Sistem Informasi, Sistem Informasi Berbasis Web, Sistem Berbasis Pengetahuan, Komputasi Bergerak, Penambangan Data, Basis Data, Gudang Data, Gudang Data, Mutimedia.
Arjuna Subject : Ilmu Pengambilan Keputusan (semua kategori) - Sistem Informasi dan Manajemen
Articles 194 Documents
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Analisis Usability pada SIAPEL-TEGAS dalam Pengurusan KTP-el dengan Menggunakan Metode System Usability Scale (SUS) vita mei fudnia watiningsih; Mochammad Anshori; Ahsanun Naseh Khudori
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 4 No. 3 (2026): Agustus : JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v4i3.4523

Abstract

SIAPEL-TEGAS (Integrated Population Administration Information System) is a digital service provided by the Department of Population and Civil Registration of Malang City that enables citizens to process population administration documents, including electronic identity cards (e-KTP), online. This study aims to analyze the usability level of the SIAPEL-TEGAS application in e-KTP processing services using the System Usability Scale (SUS) method. Data were collected through an online questionnaire distributed to 50 respondents who had previously used the service, employing a purposive sampling technique. The questionnaire consisted of 10 standard SUS statements measured using a 5-point Likert scale. The results showed that the SIAPEL-TEGAS application achieved an average SUS score of 85.35, which falls into the "Acceptable" category with a Grade A rating and an "Excellent" adjective rating. The validity test of all questionnaire items indicated that the calculated correlation coefficients (r-count) were higher than the critical value of r-table (0.2732), confirming that all items were valid. Meanwhile, the reliability test using Cronbach’s Alpha produced a value of 0.738, which is categorized as reliable (acceptable). These findings indicate that the SIAPEL-TEGAS application generally demonstrates an excellent level of usability in terms of effectiveness, efficiency, and user satisfaction. However, several aspects still require improvement to further optimize the user experience.
Penerapan Algoritma Random Forest untuk Prediksi Kelulusan Siswa Smk Al Amanah Tepat Waktu: Studi Kasus Program Studi Teknik Informatika Rajin Nahampun; Muhammad Hafidh Ali Zainal; Vidie Dwi Saputra; Ananda Raffi
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 4 No. 3 (2026): Agustus : JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v4i3.4533

Abstract

On-time graduation is one of the key indicators of academic quality that affects study program accreditation and institutional reputation. Many Informatics Engineering students, however, still complete their studies later than scheduled due to various academic and non-academic factors. This study aims to apply the Random Forest algorithm to build a predictive system that classifies students into “on-time” and “delayed” graduation categories based on academic data such as cumulative grade point average (GPA), number of credits completed per semester, attendance rate, and final project completion status. The research method follows the CRISP-DM framework, covering business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The model was trained using an 80:20 train-test split and evaluated using a confusion matrix along with accuracy, precision, recall, and F1-score metrics. The results show that the Random Forest algorithm achieves a good level of accuracy in classifying student graduation status, with GPA and attendance rate identified as the most influential variables. This model has the potential to be used by study programs as an early-warning system to identify students at risk of delayed graduation so that academic intervention can be carried out sooner.
Analisis Sentimen Pengguna Aplikasi Mobile JKN menggunakan Algoritma Support Vector Machine dan Naive Bayes Muhamad Bahrul Irfan; Herny Februariyanti
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 4 No. 3 (2026): Agustus : JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v4i3.4537

Abstract

The Mobile JKN application serves as the primary digital gateway developed by BPJS Kesehatan, enabling National Health Insurance participants to manage administrative needs and access health-related information remotely. Despite its widespread adoption, persistent user grievances—documented through Google Play Store reviews—signal opportunities for service refinement. This research harvested 20,000 user reviews via automated scraping (August 1–December 15, 2025) and retained 18,729 valid entries following a five-stage preprocessing pipeline encompassing cleaning, normalization, tokenization, stemming, and stopword elimination. Feature representation relied on TF-IDF vectorization, while training-set class imbalance was counteracted through SMOTE oversampling. A head-to-head evaluation pitted LinearSVC against Complement Naive Bayes across three sentiment polarities. LinearSVC emerged as the stronger classifier, registering 81.71% accuracy alongside a weighted F1-score of 0.84—surpassing its probabilistic counterpart at 79.85% accuracy and 0.83 weighted F1-score. Both architectures demonstrated robust positive-class detection (F1=0.92) yet faltered on neutral reviews, where overlapping lexical cues between praise and complaint eroded discriminative power. Wordcloud mapping further exposed recurring dissatisfaction markers ("susah", "sulit", "ribet") juxtaposed with appreciation signals ("bantu", "mudah", "bagus"), offering actionable intelligence for BPJS Kesehatan to target specific service pain points.
Evaluasi Sistem Informasi Administrasi Siswa Menggunakan Metode PIECES serta Rekomendasi Perbaikannya : Studi Kasus: TK Harapan Sejahtera Vira Arif Rakhmatunnisa; Elin Rosliani
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 4 No. 3 (2026): Agustus : JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v4i3.4565

Abstract

Student data management systems in early childhood education institutions often still rely on conventional paper-based approaches, a situation that potentially hampers the overall effectiveness of administrative services. This study aims to evaluate the student information administration system at TK Harapan Sejahtera, Garut, using the PIECES analytical framework encompassing Performance, Information, Economy, Control, Efficiency, and Service dimensions. A descriptive qualitative approach was employed through participatory observation, semi-structured interviews with four teachers who simultaneously perform administrative functions, and documentation study. The findings reveal several interrelated structural barriers: searching data for 46 active students requires 8–12 minutes per transaction due to reliance on physical archives; monthly attendance recapitulation consumes 1–2 hours of teachers' time outside teaching hours; and routine expenditures for administrative consumables reach Rp150,000–Rp250,000 per month. The absence of dedicated administrative staff forces teachers to bear a dual burden that diminishes the quality of lesson preparation. From a data security perspective, there are no adequate backup mechanisms or access controls, leaving physical archives vulnerable to damage and loss. Based on these findings, this study recommends a phased and realistic digitalization approach, including the use of structured spreadsheets, cloud-based storage, digital communication with parents, and technology training for teaching staff. Implementation of these recommendations is projected to reduce data retrieval time by more than 80% and improve the quality of information services to school stakeholders.
Deteksi dan Koreksi Kesalahan Pengetikan Berbasis KBBI Menggunakan Algoritma Peter Norvig Aldi Mawaridi; Rahmalia Syahputri; Muhammad Said Hasibuan
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 4 No. 3 (2026): Agustus : JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v4i3.4577

Abstract

With the advent of the digital age, there has been an explosion in the volume of written material; however, this increase has also been accompanied by an alarmingly high error rate. These typos are serious because they alter the intended meaning of the message and make it appear less credible than it actually is. Therefore, this study aims to design and develop a spelling detection and correction system (spelling checker) for Indonesian text that strictly adheres to the Kamus Besar Bahasa Indonesia (KBBI). The system is built using an architecture that integrates KBBI lexicon matching with probabilistic calculations via Peter Norvig’s algorithm. This integration forms the foundation of the system’s design. Methodologically, the system checks text against the KBBI database and also breaks down irrelevant terms into tokens (tokenizing). To ensure the most accurate correction suggestions are provided when detecting non-standard or misspelled words, Peter Norvig’s method determines the edit distance and the maximum likelihood value. The research results show that this system is capable of detecting spelling errors and providing efficient correction recommendations in real time, as demonstrated through testing on a web interface built using the Laravel framework. Finally, an effective method for preparing Indonesian-language texts while maintaining their scientific quality is provided through the integration of the KBBI database with the flexibility of Peter Norvig’s algorithm.
Sistem Pelayanan Pelanggan Berbasis Customer Relationship Management dengan Pendekatan UX pada Toko Na Roti Masayu Wianda Putri; Aninda Muliani Harahap
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 4 No. 3 (2026): Agustus : JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v4i3.4596

Abstract

Customer service plays an essential role in maintaining customer loyalty in retail businesses. However, customer service processes at Toko Na Roti are still managed conventionally, resulting in inefficient customer data management, promotional activities, transaction history management, and complaint handling. This study aims to develop a Customer Relationship Management (CRM)-based Customer Service Information System using the Laravel Framework and MySQL by implementing the UX Design Process to ensure that the system meets user requirements. The UX Design Process consisted of the Empathize, Define, Ideate, Prototype, and Test stages, which identified user requirements and produced six main system modules, namely customer management, transaction history, promotion management, complaints and feedback, a rule-based chatbot, and an owner analytics dashboard. The system was implemented using the Laravel Framework as the development framework and MySQL as the database management system. Functional testing was conducted using the Blackbox Testing method across 10 test scenarios representing all core system functionalities. The testing achieved a 100% success rate, indicating that all system modules operated according to the predefined functional requirements. The developed system supports more structured customer relationship management, facilitates the digitalization of customer services, and provides data-driven information to support managerial decision-making at Toko Na Roti.
Pengembangan dan Integrasi Sistem Otomasi Perpustakaan Digital Berbasis INLISLite untuk Meningkatan Layanan Informasi di SMA Methodist 3 Palembang Maria Ulfa; Ayu Andira; Evi Yulianingsih; Siti Sauda
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 4 No. 3 (2026): Agustus : JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v4i3.4597

Abstract

The development of information technology in the digital era has influenced various aspects of life, including library services. Along with these technological advancements, libraries are required to develop technology-based services through the implementation of digital library automation systems such as INLISLite to improve the quality of information services.This research was conducted at the library of SMA Methodist 3 Palembang, which still used a manual system for managing borrowing, returning, searching, and cataloging books. As a result, delays and data recording errors frequently occurred. In addition, unstructured data storage made library management less efficient. Therefore, the development and integration of an INLISLite-based digital library automation system were carried out to assist in managing book collections, member data, borrowing and returning transactions, fines, and library reports in a more effective and structured manner.The benefit of this research is to support the creation of a library that continuously adapts to technological developments and provides better services to its users. This study employed the Research and Development (R&D) method, consisting of data collection, planning, development, testing, and product refinement stages. The results of this research are expected to improve the effectiveness, efficiency, and quality of information services in the school library
Perancangan Sistem Informasi Peminjaman dan Pengembalian Alat Berbasis Web pada Bengkel PLAT H@ AUTO STATION Semarang Dimas Bagus Prasetyo; Novita Mariana
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 4 No. 3 (2026): Agustus : JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v4i3.4606

Abstract

The management of tool borrowing and returning at PLAT H@ AUTO STATION Workshop in Semarang is currently carried out manually using record books. This process often leads to various problems, including difficulties in identifying the last mechanic who borrowed a tool, monitoring unreturned tools, searching transaction records, and preparing reports efficiently. These limitations reduce the effectiveness of inventory management and increase the risk of recording errors. This study aims to design and develop a web-based information system for tool borrowing and returning to improve the management of workshop equipment. The system was developed using the Waterfall software development method, which consists of requirements analysis, system design, implementation, testing, and maintenance. The application was built using the Glide Apps platform and provides integrated features for tool inventory management, borrowing and returning transactions, monitoring unreturned tools, recording tool conditions, and maintaining transaction history. System functionality was evaluated using the Black Box Testing method, and the results indicate that all features operated according to the specified requirements. The proposed system improves the accuracy and efficiency of inventory management by providing integrated data processing, simplifying transaction recording, enabling real-time monitoring of tool availability, and supporting faster access to inventory information. Therefore, the implementation of this system is expected to assist warehouse administrators in managing workshop equipment more effectively and to enhance the overall operational performance of PLAT H@ AUTO STATION Workshop.
Smart Web-Based Kos Management dengan Automated Reminder menggunakan Metode Waterfall Fahmil Ulum; Aang Alim Murtopo; Syefudin Syefudin
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 4 No. 3 (2026): Agustus : JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v4i3.4639

Abstract

The rapid development of digital technology has encouraged various activities that were previously carried out manually to shift toward digital-based systems, including boarding house management. However, in practice, many boarding house owners still manage tenant records, payment transactions, and room management manually, which often leads to problems such as unorganized data, recording errors, and payment delays that are difficult to monitor. This condition results in low operational efficiency and limited access to information for boarding house owners. This study aims to design and develop a web-based boarding house management information system that can facilitate more structured, accurate, and efficient data management. The developed system is equipped with features for managing tenant data, room data, payment transaction records, payment status monitoring, and automatic reminder notifications through the WhatsApp Gateway to address payment delays. The research method used is software engineering with the Waterfall development model, which consists of the stages of analysis, design, implementation, and testing. Data collection techniques were conducted through observation, interviews, and literature studies. The results of testing using the black-box testing method showed that all system features, including payment management, tenant data management, and WhatsApp Gateway notifications, functioned according to their intended purposes. The black-box testing results indicated that 95% of the features functioned according to the specified requirements.
Pembuatan Model Machine Learning untuk Klasifikasi Risiko Pinjaman Perbankan Menggunakan Random Forest dan XGboost Zacki Ferdinansyah; Rahmat Budiarsa
JURNAL PENELITIAN SISTEM INFORMASI (JPSI) Vol. 4 No. 3 (2026): Agustus : JURNAL PENELITIAN SISTEM INFORMASI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jpsi.v4i3.4644

Abstract

Credit risk is one of the major challenges in managing loan portfolios in the banking sector, highlighting the need for approaches capable of identifying loan risk patterns and factors associated with problematic loans based on historical data. This study aims to develop and compare the performance of Random Forest and Extreme Gradient Boosting (XGBoost) algorithms in classifying loan risk patterns and to identify the features that contribute to the classification results. The study uses a historical loan dataset processed through exploratory data analysis, categorical data transformation, an 80:20 training and testing data split, and class imbalance handling using Random Under Sampling and SMOTE. Model optimization was performed through hyperparameter tuning using GridSearchCV, while model performance was evaluated based on accuracy, precision, recall, and F1-score. Model interpretation was conducted using Feature Importance, SHAP (SHapley Additive Explanations), and decision tree visualization. The results show that XGBoost with preprocessing and the second hyperparameter tuning achieved the best performance, with an accuracy of 98%, precision of 97%, recall of 85%, and F1-score of 90%, outperforming Random Forest on the dataset used. Interpretability analysis indicates that recoveries, total_rec_prncp, out_prncp, last_pymnt_amnt, and funded_amnt are among the features that contribute substantially to the classification results. These findings indicate that preprocessing, class imbalance handling, and parameter optimization can improve classification performance while providing insights into the factors contributing to loan risk patterns based on historical data.

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