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Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Published by Cattleya Darmaya Fortuna
ISSN : -     EISSN : 27211800     DOI : -
Core Subject : Science,
Computer Science & IT
JATILIMA merupakan jurnal yang terbit dua nomor dalam satu volume (tahun), yaitu Peridoe I Bulan April dan Periode II Bulan Oktober. JATILIMA mempublikasikan tulisan-tulisan ilmiah hasil pemikiran, studi literatur, dan penelitian dalam bidang Ilmu Komputer. JATILIMA merupakan jurnal dengan sistem review yang merupakaan aspek penting dalam penyebaran ilmu pengetahuan.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 263 Documents
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Design and Construction of a Pest Repellent Device for Rice Plants Based on Wemos with Motion Detection Using Fuzzy Mamdani Novlianun Daulay; M. Fakhriza
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 8 No. 2 (2026): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v8i2.2688

Abstract

Bird pest attacks on rice plants are one of the main factors causing decreased crop yields with losses that can reach 30–50%. Manual control methods are considered less effective because they require continuous monitoring by farmers. This study aims to design and build an Internet of Things (IoT)-based bird pest repellent using the Wemos D1 Mini ESP8266 and a Passive Infrared (PIR) sensor with the Mamdani Fuzzy method as a decision-making system. The input variables in the system consist of the intensity of movement and frequency of bird appearance, while the output variable is the level of repellent response through a buzzer and servo motor. The inference process uses the Mamdani method with the MIN operator and defuzzification using the centroid method. The results show that the system is able to automatically detect the presence of pests, determine the level of repellent response according to field conditions, and send notifications in real-time via Telegram Bot. The implementation of the Mamdani Fuzzy method produces a more adaptive system than the crisp logic method because it is able to adjust the response based on the detected threat level.
Gated, grounded, and governed: integrating large language models, authorised tool calling, and retrieval-augmented generation into NeoSiakad.com, a multi-tenant academic information SaaS M. Najamudin Ridha
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 07 (2026): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i07.2716

Abstract

Large language models (LLMs) are attractive front-ends for academic information systems, yet a campus assistant must not invent grades, expose other students’ records, or drift into general chat paid from the institution’s budget. This study reports the design and empirical evaluation of an LLM assistant embedded in NeoSiakad.com, a multi-tenant academic information system delivered as software as a service to Indonesian higher-education institutions. Following a design science approach, the artefact combines four controls: a master control plane that provisions one gateway key with a USD ceiling per tenant, a fail-closed intent gate that classifies every message before the main model is called, read-only tool calling that executes canonical academic queries under the caller’s own permissions and tenancy, and retrieval-augmented generation (RAG) with mandatory citations and an abstain rule. Because RAG is not yet deployed, it was simulated on a 36-chunk academic guideline corpus. Evaluation used the public demo tenant, production telemetry, and seven language models accessed through the OpenRouter gateway. The intent gate reached 90.0 to 100 percent accuracy across models; the cheapest model let no disallowed message through at USD 0.04 per thousand calls. On the live tenant, 16 of 17 value-bearing turns reproduced the exact figures returned by the canonical resolvers, two cross-user probes were refused, and four disallowed prompts were rejected in 0.9 to 2.3 s without a main-model call. Retrieval reached Recall@3 of 1.00 for all five embedding models, and RAG raised fully correct answers from 0 to 14 percent (closed book) to 96 to 100 percent with 100 percent valid citations, while at most one of seven unanswerable questions was answered instead of declined. Moving chat turns to a queue worker cut the median turn latency from 40.9 s to 13.5 s on shared hosting. The results show that an LLM assistant can be made accurate, authorisation-bound, and cost-bounded on commodity infrastructure.
Comparative Analysis of Feature Extraction Techniques for Clustering YouTube Comments on Electric Vehicles in Indonesia Afian Rizki; M Najamudin Ridha; Dwi Agung Wibowo
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 07 (2026): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i07.2717

Abstract

This study compares TF-IDF, TF-IDF with chi-square feature selection, and BERT Sentence Transformer representations for clustering Indonesian electric-vehicle discourse in YouTube comments. A dataset of 2,601 comments from nine relevant videos published by official news accounts was preprocessed through punctuation and whitespace removal, case folding, stemming, and edit-distance correction of non-standard words. K-means was evaluated using WCSS, the elbow method, Silhouette, Calinski-Harabasz, and Davies-Bouldin indices. TF-IDF with chi-square achieved the strongest overall internal validity at k=3, with Silhouette 0.9157 and Davies-Bouldin 0.5470.

Page 27 of 27 | Total Record : 263

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