Jurnal CoSciTech (Computer Science and Information Technology)

Analysis of academic service information systems on the satisfaction of Sukarobot partners using the Servqual method

Retno Sabrila Rahma, Falentino Sembiring, Sihabudin Sihabudin — Mon, 17 Aug 2026 00:00:00 +0700

The development of information technology has significantly impacted the improvement of service quality in the education sector, particularly in academic services. Sukarobot utilizes an academic service information system to support its service delivery to partners. However, several obstacles have been encountered in its implementation, such as occasional system errors, delayed service responses, and suboptimal service quality that meets user expectations. Therefore, this study aims to analyze the quality of the academic service information system and its impact on Sukarobot partner satisfaction using the SERVQUAL method.

This study employed a quantitative approach, with data collection techniques involving the distribution of questionnaires to Sukarobot partners. The SERVQUAL method measures service quality based on five dimensions: tangibles, reliability, responsiveness, assurance, and empathy. Data were analyzed using validity tests, reliability tests, Likert scale analysis, and gap analysis between user perceptions and expectations.

The results showed that all questionnaire items were valid, as their calculated r values were greater than the tabulated r values of 0.2133. Furthermore, the reliability test results showed that all variables had Cronbach's Alpha values above 0.60, thus declaring the research instrument reliable. Based on the SERVQUAL analysis, all dimensions had negative gap values, indicating that the service quality of Sukarobot's academic information system has not fully met user expectations. The assurance dimension had the smallest gap value of -0.34, while the reliability and responsiveness dimensions had the largest gap values of -0.40, making them a top priority for improvement

Design and Development of a Smart Flood Gate Prototype Based on Mamdani Fuzzy Logic and Multiple Sensors

Annisa Siti Farikha Ramlan, Trisiani Dewi Hendrawati — Mon, 17 Aug 2026 00:00:00 +0700

This study aims to design and implement a prototype of an adaptive automatic flood gate system based on Mamdani fuzzy logic using multi-sensor input, developed as part of a Capstone Design course. The system employs an ultrasonic sensor to measure water level, a rain sensor, and a temperature sensor as inputs, while a servo motor acts as the gate actuator. Mamdani fuzzy logic is applied to determine gate conditions classified into safe, alert, and danger levels. Experimental results show that the ultrasonic sensor achieves an average measurement error of ±1.2 cm compared to manual measurements. The system responds to water level changes with an average response time of 1.8 seconds. The flood gate operates correctly according to fuzzy rules with a 100% success rate across 15 test scenarios. Furthermore, the system demonstrates a decision accuracy of 93.3% in classifying flood conditions. The system can also be monitored in real time using the Blynk application.These results indicate that the proposed prototype performs effectively as a laboratory-scale flood gate control system and has potential for further development toward real-world implementation.

Desain Model Jaringan IP Combat Management System pada Kapal Perang Republik Indonesia Menggunakan GNS3

Randika Prathama Adibrata, Erpan Sahiri — Thu, 13 Aug 2026 00:00:00 +0700

The modernization of the Primary Weapon Systems (Alutsista) on the Republic of Indonesia Warships (KRI) demands an integrated Combat Management System (CMS). The main problem faced is the shift of military communication systems toward Internet Protocol (IP)-based systems and Indonesia's dependence on foreign-made CMS technology. To overcome these problems, this research aims to design a new IP network architecture specifically tailored for KRI CMS operations and to test its functionality. The proposed solution is the design of a hybrid physical topology, combining the advantages of a star topology at the internal level of the Central Server Cabinet (CSC) and a partial mesh topology between cabinets. Additionally, data communication management is logically optimized using Virtual Local Area Networks (VLAN). The problem-solving method is conducted through modeling in the Graphical Network Simulator 3 (GNS3), followed by functional validation testing. The network simulation proves the seamlessness of comprehensive data exchange, indicated by successful inter-device connectivity across all test scenarios. The implementation of VLAN segmentation is proven successful in isolating data paths, ensuring that real-time tactical command flows can be distributed without being disrupted by high-capacity video loads. Overall, this network architecture design is proven to be robust and efficient in meeting operational standards that require redundancy, eliminating the risk of a single point of failure, and providing scalability for future upgrades. This architectural design is expected to serve as a solid blueprint for the domestic industry to support self-reliance in national defense technology.

Sistem informasi tabungan dan manajemen kelompok kurban berbasis responsive web menggunakan metode rapid application development (RAD)

Aryanto Aryanto, Wide Mulyana Mulyana — Thu, 13 Aug 2026 00:00:00 +0700

The implementation of the qurban worship is often hampered by the readiness of community cash funds that must be paid in one lump sum close to the day of the event [1]. On the other hand, qurban managers at the mosque level generally still rely on manual recording based on physical books or spreadsheets, which has the potential to trigger recording errors (human error), data loss, and difficulties in mapping participant groupings (pooling) of 7 people per cow [1], [2]. This study aims to design and build a responsive web-based qurban savings information system that facilitates a periodic installment scheme and automates participant grouping [2], [3]. System development was carried out using the Rapid Application Development (RAD) method to accelerate the software engineering cycle through iteration and intensive user feedback [4], [5]. The test results show that the system built using responsive web design successfully makes it easier for the congregation to monitor savings balances and group status transparently through various devices, as well as assisting the committee in managing financial administration and group automation accurately [1], [6], [8].

Analisis Komparatif Decision Tree dan Random Forest untuk Klasifikasi Tingkat Obesitas

Yulisman Yulisman, Akhmad Zulkifli, Edriyansyah Edriyansyah, M.Riscky Firdaus — Tue, 18 Aug 2026 00:00:00 +0700

Abstrak

Obesitas merupakan salah satu masalah kesehatan global yang terus mengalami peningkatan dan berkontribusi terhadap berbagai penyakit tidak menular, seperti diabetes melitus, hipertensi, dan penyakit kardiovaskular. Faktor gaya hidup, pola konsumsi makanan, serta aktivitas fisik memiliki peran penting dalam menentukan tingkat obesitas seseorang. Perkembangan teknologi machine learning memungkinkan pengembangan model prediksi yang dapat membantu mengidentifikasi tingkat obesitas berdasarkan karakteristik individu. Penelitian ini bertujuan untuk membandingkan kinerja algoritma Decision Tree dan Random Forest dalam klasifikasi tingkat obesitas berdasarkan faktor gaya hidup dan kondisi fisik. Dataset yang digunakan terdiri atas 2.111 data dengan 17 atribut yang mencakup informasi demografi, kebiasaan makan, aktivitas fisik, konsumsi air, penggunaan perangkat teknologi, serta riwayat keluarga. Tahapan penelitian meliputi prapemrosesan data, transformasi atribut kategorikal, pembagian data latih dan data uji, pelatihan model, serta evaluasi menggunakan metrik accuracy, precision, recall, dan F1-score. Hasil penelitian menunjukkan bahwa algoritma Random Forest memperoleh performa terbaik dengan nilai accuracy sebesar 95,27%, sedangkan Decision Tree memperoleh accuracy sebesar 91,73%. Selain itu, analisis feature importance menunjukkan bahwa atribut Weight, Height, Age, FCVC, dan Gender merupakan faktor yang memberikan kontribusi terbesar dalam proses klasifikasi tingkat obesitas. Hasil penelitian menunjukkan bahwa pendekatan ensemble learning pada Random Forest mampu meningkatkan kualitas klasifikasi dibandingkan model pohon keputusan tunggal.