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All Journal JOIN (Jurnal Online Informatika) Jurnal Sisfokom (Sistem Informasi dan Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Algoritma Jurnal Ilmiah MEA (Manajemen, Ekonomi, dan Akuntansi)
Nurlatifah, Eva
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education

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HASIL PERBANDINGAN PENERAPAN METODE PERAMALAN DALAM MENENTUKAN TINGKAT INFLASI PENDIDIKAN DI KOTA BANDUNG Nurlatifah, Eva; Fahrudin, Tora; Rochmawati, Rochmawati
Jurnal Ilmiah Manajemen, Ekonomi, & Akuntansi (MEA) Vol 7 No 3 (2023): Edisi September - Desember 2023
Publisher : LPPM STIE Muhammadiah Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31955/mea.v7i3.3292

Abstract

Inflasi menjadi salah satu masalah yang krusial bagi perekonomian suatu negara. Inflasi dapat terjadi ketika nilai mata uang mengalami penurunan terhadap barang atau jasa. Sektor yang mengalami inflasi pun beragam untuk setiap kurun waktunya. Pemodelan tingkat inflasi pada suatu kota dipandang perlu untuk memberikan informasi perkiraan laju inflasi di masa yang akan datang. Prediksi dibuat dengan dilakukannya perbandingan beberapa metode peramalan yaitu Naïve Approach, Exponential Smoothing dan Trend Linier yang mana nantinya aplikasi dapat membaca data dengan rumus-rumus tersebut berdasarkan data laju inflasi kota Bandung tahun 2011-2017, sebagai acuan untuk melakukan prediksi laju inflasi tahun 2018, dan dilakukannya perbandingan dengan Situs Web Badan Pusat Statistik. Proses peramalan dilakukan dengan menggunakan bahasa pemrograman python menggunakan function sktime yaitu forecasting. Dari bebereapa metode peramalan yang digunakan hasil pengujian menunjukan bahwa metode naïve approach dengan strategi drift dengan nilai MSE 1.169, MAE 0.663, MAPE 1730. menjadi metode yang memiliki selisih paling kecil dari data rill inflasi pendidikan tahun 2018 dibandingkan dengan metode peramalan Exponential Smoothing dan Trend Linier yang memiliki selisih jauh lebih besar dari data rill.
Game and Application Purchasing Patterns on Steam using K-Means Algorithm Aulia, Salman Fauzan Fahri; Gerhana, Yana Aditia; Nurlatifah, Eva
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 13 No. 3 (2024): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i3.2214

Abstract

Online games are visual games that utilize the internet or LAN networks. With the growth of the gaming industry, platforms like Steam offer a wide variety of games, making it challenging for users to decide which game to play. This study employs the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology to address this issue by understanding user preferences. The k-means algorithm clusters game data based on similar characteristics, helping users and developers identify the most popular game types. Data sourced from Kaggle, obtained through the Steam API and Steamspy, consists of 85,103 entries. A normalization process is applied to enhance calculation accuracy. The elbow method determines the optimal number of clusters, resulting in three clusters from the k-means algorithm. The evaluation includes the silhouette coefficient, which measures the proximity between variables, and precision purity, which compares labels by assigning a value of 1 (actual) or 0 (false). The study finds an average silhouette coefficient of 0.345 and a precision purity value of 0.734, indicating that the k-means algorithm performs optimally based on the precision purity metric. The findings reveal that free-to-play games are the most popular among users, while the "Animation & Modelling" category is the most expensive based on price comparisons
Chatbot Edukasi Pra-Nikah berbasis Telegram Menggunakan Bidirectional Encoder Representations From Transformers (BERT) Fatonah, Fany Risti; Maylawati, Dian Sa'adillah; Nurlatifah, Eva
Jurnal Algoritma Vol 21 No 2 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-2.1657

Abstract

Tingginya angka perceraian dan penurunan minat untuk menikah di Indonesia memunculkan kebutuhan akan pendekatan baru dalam edukasi pranikah. Dengan memanfaatkan teknologi Natural Language Processing, penelitian ini bertujuan untuk mengembangkan mesih chatbot menjadi solusi dalam edukasi pre-nikah yang dengan memberikan informasi efektif dan efisien kepada pasangan calon pengantin secara realtime. Penelitian ini menggunakan model Bidirectional Encoder Representations from Transformers (BERT) dengan chatbot berupa konteks dari website Kementerian Agama dan buku edukasi pernikahan. Model ini diimplementasikan ke dalam chatbot melalui platform Telegram dan pengujiannya menggunakan pengujian Non-Respon-Rate dan metriks BERTScore. Hasil pengujian Non-Respon-Rate menunjukkan akurasi chatbot edukasi pranikah berbasis BERT sebesar 76,92% dengan akurasi tertinggi 92%. Sedangkan pengujian menggunakan BERTScore menunjukkan bahwa chatbot tersebut mencapai nilai precision 86%, recall 83%, dan F1-score 84%.
Klasifikasi Pengenalan Huruf Hijaiyah Pada Bahasa Isyarat Arab Menggunakan Transfer Learning EfficientNetB1 Putri, Diani Eka; Jumadi, Jumadi; Nurlatifah, Eva
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.6174

Abstract

Individu Muslim dengan gangguan pendengaran sering menghadapi tantangan dalam mempelajari Al-Qur'an, terutama karena kurangnya sistem pendukung untuk pembelajaran bahasa isyarat Arab. Bahasa isyarat memainkan peran penting dalam memfasilitasi komunikasi yang efektif bagi mereka yang mengalami kesulitan pendengaran. Untuk mengatasi masalah ini, penelitian ini bertujuan untuk mengembangkan sistem pengenalan Bahasa Isyarat Arab (ArSL) dengan menggunakan Convolutional Neural Network (CNN) dan pendekatan Transfer Learning menggunakan model pre-trained EfficientNetB1. Sistem ini dirancang untuk mengidentifikasi gerakan bahasa isyarat Arab dari dataset yang terdiri dari 28 huruf Hijaiyah, dengan masing-masing huruf memiliki 100 citra. Pengujian dilakukan pada model dengan empat skenario berbeda untuk menemukan konfigurasi yang paling optimal. Hasil penelitian menunjukkan bahwa dengan membekukan 30% lapisan awal model selama fine-tuning menghasilkan akurasi 98.95% pada data train dan 99.52% pada data validation. Pada data pengujian, model mencapai performa terbaik dengan accuracy, precision, recall, dan f1-score masing-masing sebesar 100%.
Game and Application Purchasing Patterns on Steam using K-Means Algorithm Aulia, Salman Fauzan Fahri; Gerhana, Yana Aditia; Nurlatifah, Eva
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 13 No. 3 (2024): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i3.2214

Abstract

Online games are visual games that utilize the internet or LAN networks. With the growth of the gaming industry, platforms like Steam offer a wide variety of games, making it challenging for users to decide which game to play. This study employs the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology to address this issue by understanding user preferences. The k-means algorithm clusters game data based on similar characteristics, helping users and developers identify the most popular game types. Data sourced from Kaggle, obtained through the Steam API and Steamspy, consists of 85,103 entries. A normalization process is applied to enhance calculation accuracy. The elbow method determines the optimal number of clusters, resulting in three clusters from the k-means algorithm. The evaluation includes the silhouette coefficient, which measures the proximity between variables, and precision purity, which compares labels by assigning a value of 1 (actual) or 0 (false). The study finds an average silhouette coefficient of 0.345 and a precision purity value of 0.734, indicating that the k-means algorithm performs optimally based on the precision purity metric. The findings reveal that free-to-play games are the most popular among users, while the "Animation & Modelling" category is the most expensive based on price comparisons
Reducing Free Riding Behaviour in Collaborative Work with Computer Supported Tools Kloppenburg, Wieger; Nurlatifah, Eva; Spijkerboer, Christian; Yasmin, Fitri Almira
JOIN (Jurnal Online Informatika) Vol 3 No 1 (2018)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v3i1.180

Abstract

Free riding behaviour is a problem that has been around for many years. With all the new technological advances, there is much more collaborative work supported by online tools. These developments make it easier for individuals to become a free rider. This research carried out a literature study, to find the best method to reduce free-riding behaviour. Besides the methods, this study also elaborates some factors that trigger free riders in a group. The methods which are highlighted in this research are the implementation of assessments, group awareness tools, sufficient group size and enhancing team morale. However, the study found that none of the methods cover all the aspects of free-riding behaviour. It is suggested by this research to combine and improve various methods, to a new method that can effectively reduce free-riding behaviour in collaborative work with computer-supported tools.
Co-Authors Aulia, Salman Fauzan Fahri Fatonah, Fany Risti Jumadi Jumadi Kloppenburg, Wieger Maylawati, Dian Sa'adillah Putri, Diani Eka Rochmawati, Rochmawati Spijkerboer, Christian Tora Fahrudin Yana Aditia Gerhana, Yana Aditia Yasmin, Fitri Almira