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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal Informatika Jurnal Teknik Komputer AMIK BSI Paradigma Bina Insani ICT Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Information System for Educators and Professionals : Journal of Information System JIEET (Journal of Information Engineering and Educational Technology) Informatics for Educators and Professional : Journal of Informatics Jurnal Teknik Informatika UNIKA Santo Thomas Journal of Information System, Applied, Management, Accounting and Research JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Kajian Ilmiah Jurnal Sistem Informasi Bulletin of Computer Science Research Journal of Students‘ Research in Computer Science (JSRCS) Jurnal Teknik Informatika Unika Santo Thomas (JTIUST)
Entin Sutinah, Entin
Universitas Bina Sarana Informatika
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Social Sciences Other

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Optimasi Rute Distribusi Spare Part Motor Menggunakan Ant Colony Optimization untuk Efisiensi Jarak Tempuh Nani Agustina; Entin Sutinah; Martini Martini
Journal of Information System Research (JOSH) Vol 7 No 4 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i4.9620

Abstract

Logistics efficiency in goods distribution has become a major challenge for distribution companies in reducing operational costs. This study aims to optimize the distribution routes of motorcycle spare parts at PD. Tri Jaya Motor using the Ant Colony Optimization (ACO) algorithm. The main issue faced by the company is the use of unsystematic manual route determination, which results in inefficient travel distances. The methodology employed in this research involves modeling the Traveling Salesman Problem (TSP) across six distribution points using parameters of alpha = 1, beta = 1, and rho = 0.1. The simulation results demonstrate that the ACO algorithm successfully identified the optimal route with a total distance of 206.6 km, resulting in significant savings compared to the initial route. This study contributes by providing a metaheuristic-based decision-making strategy for medium-scale distribution systems.
Penerapan Algoritma Decision Tree Untuk Memprediksi Pengelolaan Inventaris Sarana Pembelajaran Kampus Martini Martini; Nani Agustina; Entin Sutinah
Bulletin of Computer Science Research Vol. 6 No. 1 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v6i1.889

Abstract

UBSI as an educational institution that has learning support facilities must be able to manage campus inventory effectively. This study aims to determine the management of asset management that needs to be done, both in the form of routine maintenance and updating of goods. The UBSI Jatiwaringin branch campus only makes reports on the condition of inventory items, so it cannot determine whether the reported inventory data is updated or repaired, so far it is not known which items are prioritized based on their level of importance. The data will then be followed up by the main campus to check the inventory data report. The method used to determine inventory predictions is the Decision Tree Algorithm which has priority, location, condition, frequency, and prediction attributes. As targets in the decision tree are prediction attributes that have maintenance or renewal classes. Determination of inventory data predictions by calculating the entropy, gain, gain info, and gain ratio values ??of each attribute and resulting in the Priority attribute being the root node in the formed decision tree. This indicates that the priority attribute has a strong influence in determining whether an item is included in the maintenance or renewal class. Based on testing results using RapidMiner software with the K-Fold Cross Validation method, the Decision Tree algorithm can generate a decision model with an average accuracy of 86.67% in campus inventory management. The results of this study are expected to be useful for Jatiwaringin Campus administrators to conduct initial inspections without waiting for repairs from the main campus.
Pendekatan Fuzzy Servqual Untuk Mengevaluasi Tingkat Kepuasan Pasien di Praktik Dokter Karunia Lina Rosina Limbong; Entin Sutinah; Nani Agustina
Journal of Students‘ Research in Computer Science Vol. 5 No. 2 (2024): November 2024
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/0hw26s38

Abstract

Measuring patient satisfaction is one of the main indicators of measuring the quality of service in health facilities. Health service providers have difficulty measuring patient satisfaction, problems that are often complained about based on patient perceptions include late arrival of doctors at the clinic, lack of toilet cleanliness, long examination times, and the attitude of some nurses who are not friendly. The purpose of the study was to evaluate the level of satisfaction of patients who were treated at the Karunia Doctor's Practice using the Fuzzy Servqual method. Service quality was analyzed through five dimensions in the Servqual framework, namely tangible evidence, reliability, responsiveness, assurance, and empathy. The results of the study showed that the gap value of the five dimensions was negative, indicating that the quality of service provided did not meet the expectations of patients who were treated at the Karunia Doctor's Practice. The dimension with the highest gap value was tangible evidence with a value of -0.77, while the lowest gap value was in the reliability dimension. Thus, it can be concluded that the tangible evidence dimension requires special attention to improve service quality.
Optimalisasi Pemilihan Laptop Kerja Terbaik dengan Pendekatan Metode AHP dan TOPSIS Sya’Roni; Entin Sutinah; Nani Agustina
Journal of Students‘ Research in Computer Science Vol. 6 No. 1 (2025): Mei 2025
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/ev7t4c98

Abstract

The components found in laptops are generally the same as those in personal computers (PCs), but they are designed to be smaller, lighter, and more energy-efficient. As technology has advanced, laptops have also undergone many improvements, including in design, processor speed, memory capacity, feature additions, and efficiency in terms of time and space. Additionally, the prices of laptops today are relatively affordable. PT. Varsindo Kimia Abadi is a company engaged in the chemical industry. Currently, the company is facing a challenge in selecting the right laptop for new employees, considering the many brands and specifications available. Therefore, the author aims to provide the best recommendations for laptop selection. In the data analysis process of this research, two methods are adopted: AHP (Analytic Hierarchy Process) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). The research results indicate that the best choice for a work laptop is the Asus X441MA with a score of 0.6717, followed by the Lenovo Ideapad IP V130 with a score of 0.5913, and the Asus X407MA as the third alternative with a score of 0.5458.
Co-Authors Achmad Baroqah Pohan Andi Setiawan Andre Gusti Hermawan Anwar , Rian Septian Aryo Tunjung Kusumo Asmoro, Randi Ashar Azima, Gustiyasyah Nurul Bangkit Anugrah Putra Barkah, Novalia Budiman Budiman Eni Heni H Eni Heni Hermaliani Giffari Ahmad Fakhriza Gustiyasyah Nurul Azima Ibnu Alfarobi Imaduddin, Encep Fahmi Khoirun Nisa Lina Rosina Limbong Martini Martini Martini Martini Martini Mega Priyanto Moch.Arif Wicaksono Muhammad Fahri Revansa Nani Agustina Nico Hermanto Novalia Barkah Odilia Rosdiana Simamora Randi Ashar Asmoro Rayhan Fadhilah Redi Nurhidayat Reza Trimahardhika Rian Septian Anwar Riza Syahrial Rizal Gustiar Sandra Regina Syarif Hidayatulloh Sya’Roni