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All Journal Journal of Innovation Information Technology and Application (JINITA) Teknikom: Teknologi Informasi, Ilmu Komputer dan Manajemen
Singgih Briandoko
STMIK Widya Utama
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics

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Perbandingan Algoritma Conditional Random Field dan Hidden Markov Model pada Pos Tagging Bahasa Indonesia Singgih Briandoko; Atika Ratna Dewi; Muhammad Akbar Setiawan
Jurnal Teknologi Informasi, Ilmu Komputer dan Manajemen Vol 2 No 2 (2018): Teknikom Vol. 2 No. 2 Tahun 2018
Publisher : LPPM STMIK Widya Utama

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Abstract

Twitter is now an alternative source of real timeinformation for the public. Technological developmentscover all aspects of life, one of which is the field of language.Natural Language Processing (NLP) devices developed tosupport those needs are POS Tagger. This research use 10tweets and HMM algorithm get 62,7% accuracy level whileConditional Random Field algorithm get 71%. This showsthat CRF is better for performing POS tagging in Indonesianon Twitter. HMM and CRF can handle tagging of words thatare not in the corpus but the results are not very good.
TEMPERATURE CONTROL AND MONITORING SYSTEM (TCMS) BERBASIS INTERNET OF THINGS DENGAN SMARTPHONE ANDROID PADA AKUARIUM IKAN MOLLY BALON Setiawan, Muhammad Akbar; Andiko, Singgih Setia; Briandoko, Singgih; Kisworini, Rianti Yunita
Jurnal Teknologi Informasi, Ilmu Komputer dan Manajemen Vol 9 No 1 (2024): Vol 9 No 1 (2024): Teknikom Volume 9 Nomor 1 Tahun 2024
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) STMIK Widya Utama

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Abstract— Approximately 363 types of freshwater ornamental fish bred in Indonesia and exported to European countries. Among the many types of freshwater ornamental fish, the focus will be on the Molly fish (Poecilia sphenops). Ornamental fish are well-known to the public as aquarium decorations. The Molly fish (Poecilia sphenops) is one of the ornamental fish with beautiful colors, belonging to the Poecilidae family originating from Mexico, Florida, and Virginia. The maximum size of this fish can reach 12-13 cm states that Molly fish (Poecilia sphenops) are widely cultivated because of their beautiful shape, color, omnivorous nature, and viviparous breeding. The Molly fish typically lives in water temperatures ranging from 15-27°C. They prefer a slightly alkaline pH, ranging from 7 to 8. This temperature and pH monitoring device was developed to address these challenges, making it easier for marble Molly fish farmers to control the temperature and pH levels in tarp ponds. The function of this device is to provide real-time temperature and pH data to the IoT application, which can be accessed by farmers. In addition to monitoring, the device also controls the temperature by sending commands to the heater to adjust to the optimal temperature for raising Molly fish.The performance of this device has been tested based on the Dimension of Quality for Goods, achieving a valid score of 82.26%. According to usability testing, the device achieved the highest performance in terms of usability and efficiency, with a score of 98.75%, indicating that the device is easy to use and efficient.
Construction of an Indonesian Language Corpus for the Evaluation of the JMO Application Using UMUX-Lite Based on Google Play Store User Reviews Vern Rahmah Solehah; Tenia Wahyuningrum; Adnan Purwanto; Singgih Briandoko; Singgih Setia Andiko; Teotino Gomes Soares
Journal of Innovation Information Technology and Application (JINITA) Vol 8 No 1 (2026): JINITA, June 2026
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v8i1.2955

Abstract

The JMO application is a key digital service platform developed by the Social Security Administration for Employment. This public legal entity provides social security protection for all workers in Indonesia, offering them online access. It offers a comprehensive suite of services, including participant registration, Old Age Security benefit simulations, balance checks, same-day claims with Electronic Know Your Customer (e-KYC) verification, and workplace accident reporting. This study aims to evaluate the application's usability by constructing an Indonesian-language corpus from user reviews on the Google Play Store, utilizing the Usability Metric for User Experience-Lite (UMUX-Lite) instrument. The objective is to assess whether the application meets user requirements and delivers a user-friendly experience. A dataset of 2,500 reviews was manually labeled based on two core UMUX-Lite indicators: perceived ease of use (P1) and perceived usefulness (P3). The labeling results were as follows: 35.1% irrelevant, 29.5% relevant to P1, 28.1% relevant to P3, and 7.4% relevant to both P1 and P3. The text underwent preprocessing, including stop word removal, tokenization, and stemming, before being analyzed via word cloud visualization, Term Frequency-Inverse Document Frequency (TF-IDF) weighting, and multiple classification algorithms (Naive Bayes, Random Forest, Support Vector Machine (SVM), Logistic Regression, K-Nearest Neighbors (K-NN), and Decision Tree). To mitigate class imbalance, the Synthetic Minority Oversampling Technique (SMOTE) was applied. Post-oversampling, all classifiers achieved accuracy rates above 80%. The results objectively indicate that users generally perceive the JMO application as easy to use and effective in meeting their needs, validating the proposed evaluation framework. The constructed corpus also serves as a valuable resource for future research on evaluating Indonesian-language mobile applications.
Co-Authors Adnan Purwanto Andiko, Singgih Setia Atika Ratna Dewi Muhammad Akbar Setiawan Rianti Yunita Kisworini, Rianti Yunita Singgih Setia Andiko Tenia Wahyuningrum Teotino Gomes Soares Vern Rahmah Solehah