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All Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi
Arvianto, Ramdani
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Computer Science & IT Economics, Econometrics & Finance

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Analisis Tingkat Kepuasan Mahasiswa dalam Kegiatan UKM di Stikom CKI Menggunakan Algoritma Naive Bayes Arvianto, Ramdani; Tundo, Tundo; Tresia, Eflin; Januarsyah, Firly
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp206-214

Abstract

The main problem in increasing the level of student satisfaction in UKM activities at STIKOM CKI is caused by various factors, including the rare frequency of meetings and the multiplication of material without significant development. This dissatisfaction can reduce students' interest in actively participating in UKM activities, which should be a source of positive experiences and skills development. Well-managed SME activities can be an important means of developing soft skills such as leadership, team collaboration and communication skills. However, when these activities are not managed well, the results can be counterproductive, causing frustration and dissatisfaction among students. Based on these problems, an application of the Naive Bayes algorithm will be carried out to determine the satisfaction level of STIKOM CKI students with 80 training data and 6 test data. After calculating, an accuracy rate of 83.33%, recall of 33.33%, and precision are obtained. 100%. Therefore, it is important to manage student satisfaction levels to avoid being counterproductive. One of the appropriate data mining algorithms to solve the case above is to use the Naive Bayes algorithm.
Analisis Tingkat Kepuasan Mahasiswa dalam Kegiatan UKM di Stikom CKI Menggunakan Algoritma Naive Bayes Arvianto, Ramdani; Tundo, Tundo; Tresia, Eflin; Januarsyah, Firly
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp206-214

Abstract

The main problem in increasing the level of student satisfaction in UKM activities at STIKOM CKI is caused by various factors, including the rare frequency of meetings and the multiplication of material without significant development. This dissatisfaction can reduce students' interest in actively participating in UKM activities, which should be a source of positive experiences and skills development. Well-managed SME activities can be an important means of developing soft skills such as leadership, team collaboration and communication skills. However, when these activities are not managed well, the results can be counterproductive, causing frustration and dissatisfaction among students. Based on these problems, an application of the Naive Bayes algorithm will be carried out to determine the satisfaction level of STIKOM CKI students with 80 training data and 6 test data. After calculating, an accuracy rate of 83.33%, recall of 33.33%, and precision are obtained. 100%. Therefore, it is important to manage student satisfaction levels to avoid being counterproductive. One of the appropriate data mining algorithms to solve the case above is to use the Naive Bayes algorithm.
Implementasi Sistem Pakar Menggunakan Metode Certainty Factor Dalam Mendiagnosa Penyakit Pencernaan Arvianto, Ramdani
JATISI Vol 12 No 4 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i4.13372

Abstract

Digestive disorders are common health problems in society. However, many individuals choose to ignore the symptoms they experience for various reasons, such as fear of a serious diagnosis, concern that stress may worsen the condition, or the hope that the symptoms will resolve on their own. On the other hand, limited access to medical services also poses a challenge in early treatment. Meanwhile, the similarity of symptoms across different digestive diseases also makes self-diagnosis challenging. This study developed a web-based expert system to assist in identifying diseases based on symptoms experienced. The system was developed using the Waterfall model with the Python programming language and the Certainty Factor method in the diagnostic process. Symptom, disease, and solution data were obtained from the Halodoc, Alodokter, Klikdokter, and HelloSehat websites, then validated through interviews with experts. Black-box testing results showed that all features functioned as expected, while expert validation demonstrated good accuracy and system reliability. The system is capable of providing diagnosis results based on symptom input quickly, accurately, and easily, thereby assisting users in conducting initial self-diagnosis of digestive diseases.
Co-Authors Januarsyah, Firly Tresia, Eflin Tundo, Tundo