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Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika
Published by Universitas Ibn Khaldun Bogor
ISSN : 26545535     EISSN : 26545519     DOI : 10.32832/inovatif
Core Subject : Science, Education,
Computer Science & IT Other
Perkembangan ilmu Bidang Teknologi Informasi dan Informatika sudah banyak memberikan manfaat bagi peningkatan efektifitas dan efisiensi dalam berbagai kegiatan berbagai bidang ilmu. Jurnal INOVA-TIF (Inovasi Teknologi Informasi dan Informatika) ialah jurnal yang berisi artikel-artikel ilmiah yang meliputi bidang keilmuan tersebut yang memiliki turunan dalam topik Sistem Informasi, Geo Informatika, Net Centric Computing, dan Rekayasa Perangkat lunak. Jurnal ini dikhususkan untuk mengedepankan teknologi terapan dalamnya. Diharapkan Jurnal INOVA-TIF dapat menjadi sebuah sarana diseminasi hasil penelitian yang berkaitan dengan bidang teknologi Infomasi dan Informatika.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 40 Documents
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E-Voting Management System for Beginners Voters Berlina Wulandari; Fitrah Satrya Fajar Kusumah; Nadia Amanda Febrianti
Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika Vol. 8 No. 1 (2025)
Publisher : Universitas Ibn Khaldun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/inovatif.v8i1.2652

Abstract

Elections at the beginner voter level are still mostly done manually. This manual method is considered lacking in efficiency and is still considered conventional because it does not take advantage of technological advances. Based on this statement, several discussions emerged regarding the process of modernizing voting, namely the election process using e-voting. The e-voting system provides convenience for both voters and the executive committee. The implementation of the election by e-voting requires a system to regulate matters relating to the implementation of the election because in its implementation each agency that uses e-voting has different election data. Therefore, this study makes an e-voting management system for novice voters. This e-voting management system can manage election data such as agency profiles, election schedules, and candidates, up to the Permanent Voters List (DPT). The data used in this study were obtained from agencies that use e-voting. The method used is the waterfall model which consists of system analysis, system design, coding, and testing. Based on the test results, this system is running well according to its function. The e-voting management system makes it easier for the organizers and the implementing committee, before the election and in the post-election process.
A Decision Support System Using a Simple Additive Weighting Method to Make the Production Division of PT. Indofood Fortuna Makmur's Employee Selection Process More Simple M. Subchan; Partono Siswosuharjo; Rizky Yulia
Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika Vol. 8 No. 1 (2025)
Publisher : Universitas Ibn Khaldun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/inovatif.v8i1.2653

Abstract

At PT Indofood Fortuna Makmur, the information system still runs manually, especially when it comes to the program for choosing exceptional staff. Results of the examination are less precise and effective. The system must be developed by switching to a computer-based information system in order to prevent errors. With a calculation utilizing the SAW technique, an application that uses the PHP programming language and a MySQL database are used to design and build a decision-support system for choosing exceptional personnel. This application is in accordance with the issues at PT. Indofood Fortuna Makmur; the results are accurate because they are based on field assessments rather than biased assessments, and as a result of this assessment, employees at PT. Indofood Fortuna Makmur will be motivated to compete to become model workers.
Clusterization Of Non-Communicable Diseases Using The K-Means Algorithm Based On Surveillance Data Lhokseumawe City Health Department Victoria Ferdina; Umar Zaky
Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika Vol. 9 No. 1 (2026)
Publisher : Universitas Ibn Khaldun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/inovatif.v9i1.3082

Abstract

This study aims to compare the performance of K-Means, Fuzzy C-Means, and Hierarchical Clustering algorithms for non-communicable disease (NCD) surveillance data from the Lhokseumawe City Health Office, and to implement the best-performing algorithm into a web-based application. The dataset consisted of 3,421 records with 15 attributes collected in 2025. Data preprocessing included missing value checking and Min-Max normalization, while the optimal number of clusters was determined using the Elbow method, resulting in four clusters. Clustering performance was evaluated using the Silhouette Score, Davies-Bouldin Index, and Calinski-Harabasz Index. The results show that K-Means achieved the best performance, with a Silhouette Score of 0.8456, a Davies-Bouldin Index of 0.8005, and a Calinski-Harabasz Index of 2489.5630, outperforming Fuzzy C-Means and Hierarchical Clustering. The four resulting clusters showed distinct characteristics based on case frequency, dominant disease type, age group, and reporting period. K-Means was then implemented into a web-based application supporting dataset upload, filtering, clustering, and interactive visualization, which was validated through black box testing with all functions running successfully. This application is expected to help the Health Office analyze non-communicable disease patterns and support data-driven decision-making.
Handling Imbalanced Laboratory Result Data Using the SMOTE Method for Predicting Hypertension and Diabetes Ami Andriani; Umar Zaky
Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika Vol. 9 No. 1 (2026)
Publisher : Universitas Ibn Khaldun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/inovatif.v9i1.3096

Abstract

Hypertension and diabetes are non-communicable diseases whose prevalence continues to increase, making them major public health concerns in Indonesia. Perawas Community Health Center has a substantial amount of patient laboratory data; however, the data are still used mainly as examination archives. This study aims to develop a hypertension and diabetes prediction system using the Random Forest algorithm combined with the Synthetic Minority Oversampling Technique (SMOTE). The dataset consists of 1,722 patient records and 14 optimal features selected through feature selection. The test results show that the Decision Tree model achieved an accuracy of 81.74% before SMOTE and 73.62% after SMOTE, while Random Forest achieved an accuracy of 84.35% before SMOTE and 81.74% after SMOTE. The Random Forest model with SMOTE was then implemented in a web-based application to support the disease prediction process. The findings indicate that the Random Forest algorithm and SMOTE can support rapid, data-driven early detection of hypertension and diabetes based on patient laboratory data.
Multi-Disease Clustering Framework for Regional Health Surveillance: Case Studies in Yogyakarta, Indonesia Muhammad Zakariyah; Afna Fajrininda; Sya'ahna Nur Jannah; Diska Eklin Maulina; Lusiani; Rega Dharmawan
Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika Vol. 9 No. 1 (2026)
Publisher : Universitas Ibn Khaldun Bogor

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

Abstract

Routine disease-surveillance data combine heterogeneous clinical, demographic, spatial, and programmatic variables that cannot be represented adequately by a single clustering technique. This study developed a shared analytical framework and applied it to three datasets from the Yogyakarta Special Region Health Office: 20,660 HIV visits, 663 valid dengue cases aggregated into 14 district profiles, and 307 malaria records. Disease-specific preprocessing was followed by K-Prototypes clustering for mixed-type HIV data, Ward agglomerative hierarchical clustering for district-level dengue profiles, and K-Means clustering for malaria records. Candidate solutions were evaluated using elbow behavior, Silhouette Score, Davies-Bouldin Index, epidemiological interpretability, and operational usefulness. The analyses produced four HIV clusters with distinct demographic and clinical profiles, three dengue surveillance zones including four high-priority districts, and three malaria profiles differentiated by age, occupation, residency, imported-case status, and temperature. The selected configurations represented practical compromises between internal validity and actionable interpretation. Prototype black-box testing passed all documented HIV, dengue, and malaria scenarios. The framework enables consistent multi-disease surveillance while preserving disease-appropriate analytical choices, although external and prospective validation remains necessary.
Sentiment Analysis of Customer Experience Based on Wordcloud Visualization at Kampung Inggris Bandung EPLC sulistyo dwi sancoko; Muhammad Rafi Al Basyari
Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika Vol. 9 No. 1 (2026)
Publisher : Universitas Ibn Khaldun Bogor

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Abstract

Information technology has significantly influenced various sectors, including education, where it is increasingly used to evaluate and improve teaching systems. However, traditional evaluation methods often yield superficial feedback that lacks specific, actionable insights. This study aims to deeply analyze the sentiment of the teaching system evaluation at Kampung Inggris Bandung EPLC and present the findings intuitively through visual analytics. Data were gathered from student feedback during the 79th learning period, collected via Google Forms between January 7 and January 26, 2025. A total of 2,590 raw data entries were preprocessed through rigorous Natural Language Processing (NLP) techniques and analyzed using the K-Nearest Neighbor (KNN) algorithm paired with Term Frequency-Inverse Document Frequency (TF-IDF) feature extraction. The classification resulted in 1,171 positive sentiments and 111 negative sentiments. The model evaluation demonstrated high effectiveness, achieving an accuracy of 90.66%, precision of 82.19%, recall of 90.66%, and an F1-score of 86.22%. Furthermore, data visualization using Wordclouds successfully mapped student response patterns across various class categories (Rookie, Speaking, Grammar, and TOEFL), highlighting institutional strengths in engaging teaching methods and pinpointing specific facility-related areas for improvement.
A Hybrid Fuzzy Multiple Criteria Decision-Making (FMCDM) Approach for Evaluating Quality Management Success Factors in SMEs in Bantul sulistyo dwi sancoko; Sanjaya Fadil Indra; Kalifia Anna Dina; Artika Selfi
Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika Vol. 9 No. 1 (2026)
Publisher : Universitas Ibn Khaldun Bogor

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Abstract

Quality Management (QM) plays an important role in improving product quality in handicraft SMEs. However, the implementation of QM in small and medium-scale handicraft businesses is still relatively low. Therefore, this study aims to evaluate the Critical Success Factors (CSFs) of QM in handicraft SMEs in Bantul by using a Hybrid Fuzzy Multiple Criteria Decision-Making (FMCDM) approach. The primary criteria for evaluating QM CSFs were obtained through a literature survey and then processed through the FDM approach by industry and academic experts. Through this approach, the importance of QM CSFs was categorized into three main factors and 16 sub-factors. Two fuzzy MCDM methods were applied, namely fuzzy AHP and TOPSIS, to produce priority rankings for each factor and sub-factor. The results showed that the human factor was ranked first among the three perspectives evaluated. Meanwhile, quality control became the most important sub-factor among the 16 sub-factors. This case study provides useful insights for handicraft SME entrepreneurs to improve the quality of their products. The FMCDM method used in this study can serve as a reference for future research in the field of quality management in SMEs. It is hoped that the results of this study can contribute to improving the quality of products in handicraft SMEs in Bantul and surrounding areas.
Web-Based Smart Attendance System with QR Code, Geolocation, and WhatsApp Integration M.H. Faais Al Furqoon; Handaru Jati
Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika Vol. 9 No. 1 (2026)
Publisher : Universitas Ibn Khaldun Bogor

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Abstract

Manual attendance recording in vocational high schools is still slow, vulnerable to proxy attendance, and provides parents with no timely information. This study developed a web-based student attendance system integrating QR Code scanning, geolocation validation, and automatic WhatsApp notification, and evaluated its user experience at SMK Negeri 1 Seyegan, Yogyakarta. The Research and Development approach was applied through the five stages of the Waterfall model. The system was built on the Laravel framework with a Model-View-Controller architecture and a MySQL database, while notifications were delivered through a third-party WhatsApp application programming interface. Functional verification used black box testing with eleven test cases, and user experience was measured with the standard User Experience Questionnaire of 26 items on six scales, completed by 35 respondents consisting of one homeroom teacher, one administrative staff member, and 33 students selected purposively. The data were processed with the UEQ Data Analysis Tool and compared with an international benchmark. All eleven test cases passed, giving a success rate of 100%. Five scales reached the Excellent category, namely Attractiveness 2.20, Perspicuity 2.26, Efficiency 2.32, Dependability 2.04, and Stimulation 1.98, while Novelty reached 1.51 in the Good category. Efficiency and transparency of attendance information were therefore attained at the highest quality level.
Optimization Of Outgoing Product Selection In A Warehouse Information System Using The First Expired First Out Method Tegar Mallisa; Umar Zaky
Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika Vol. 8 No. 2 (2025)
Publisher : Universitas Ibn Khaldun Bogor

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Abstract

A Bambu Runcing Petshop is a pet shop that provides animal needs such as food, vitamins, and medicines. This store faces obstacles in determining outgoing products, especially products that have an expiration date. The absence of a system that prioritizes issuance based on expiration date risks causing expired products to remain issued. For this reason, a Warehouse Information System was developed using the First Expired First Out (FEFO) method to optimize the determination of outgoing products. System development uses the Waterfall approach with data collected through observation, interviews, and literature studies. The test results show that the application of the FEFO method in the warehouse information system was successfully run with a 100% success rate in 5 test scenarios using the black box method, where the system automatically selects and releases products based on the nearest expiration date. Thus, the warehouse information system is able to support the determination of outgoing products to be more optimal and can reduce the risk of loss due to expired products.
Determening Determining Learning Interest Directions of Students with Special Needs Using the Analytic Hierarchy Process (AHP) and Profile Matching: A Case Study at SLB Bangunputra Bantul: Penentuan Arah Minat Belajar Siswa Berkebutuhan Khusus Menggunakan Analytic Hierarchy Process (AHP) dan Profile Matching: Studi Kasus di SLB Bangunputra Bantul. Anna Kalifia; Sulistyo Dwi Sancoko Sancoko
Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika Vol. 8 No. 2 (2025)
Publisher : Universitas Ibn Khaldun Bogor

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Abstract

Determining the appropriate learning interest direction for students with special needs is a challenging process because each student has different characteristics, behaviors, communication patterns, and learning needs. At SLB Bangunputra Bantul, the determination of students’ learning interests still requires teachers to consider various aspects of student characteristics, making the decision process relatively subjective and dependent on the teacher’s experience. This study proposes a decision support approach to assist teachers in determining the learning interest direction of students with special needs by integrating the Analytic Hierarchy Process (AHP) and Profile Matching methods. AHP is applied to determine the relative weights of the assessment criteria, while Profile Matching is used to compare the actual student profile with the ideal profile for each learning interest direction through gap analysis. The criteria considered in the assessment include student behavior, daily activities, communication patterns, eye contact, and responses to situations encountered during learning activities. The combination of these methods provides a structured mechanism for processing student characteristics and generating recommendations for learning interest directions. The resulting decision support system is intended to assist teachers in making more consistent and objective decisions while still considering the individual characteristics of each student. The proposed approach can therefore serve as a supporting tool for teachers in identifying appropriate learning interest directions and facilitating the development of students’ potential according to their individual characteristics.

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