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All Journal Jurnal Teknologi Informasi Cyberku Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer (BALOK) KETIK : Jurnal Informatika
Andi Kamaruddin
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science

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DETEKSI API MENGGUNAKAN BACKGROUND SUBSTRACTION DAN ARTIFICIAL NEURAL NETWORK UNTUK REAL TIME MONITORING Andi Kamaruddin; Vincent Suhartono; Ricardus Anggi Pramunendar
Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 12 No 1 (2016): Jurnal Teknologi Informasi CyberKU Vol. 12, no 1
Publisher : Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (410.01 KB)

Abstract

The most important initial step in the detection and localization of the fire is to detect fire quickly and reliably. Video-based surveillance is one of the most promising solutions for automatic fire detection with the ability to monitor a large area and ease of reading an alarm to the operator through the monitorSupervision, unfortunately, the main drawback of video-based fire monitoring system that uses optic is a false alarm caused by an Error detection (Error detection), for it is then in this study using the feature extraction GLCM (Gray level Coocurance Matrix) as input spectral classification of Neural network to detect fire, the approach can reduce the Average Error detection with Error detection rate Average is 7%
Prediksi Jumlah Persediaan Telur Ayam Menggunakan Metode K-Neares Neighbor: - baguna, filda; Husdi, Husdi; Taliki, Sunarto; Kamaruddin, Andi
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 2 No 2 (2023): November 2023
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37195/balok.v2i2.119

Abstract

Abstract - UD. Unggas Karya Mandiri is one of the production areas producing chicken eggs in Banggai Laut Regency, with the existence of UD Unggas Karya Mandiri Banggai Laut which has the aim of increasing the number and types of employment opportunities for Banggai Laut Regency in particular. Based on the results of research at UD Unggaas Karya Mandiri Banggai Laut, this is the result of fluctuating chicken egg production or unstable production which is caused by several things, namely lack of availability of feed ingredients, anti-biotic drugs, vaccinations and so on. The aim of this research is to obtain better accuracy in predicting the number of chicken egg supplies at UD Unggas Karya Mandiri Banggai Laut by applying the K-Nearest Neighbor method. Based on the prediction results with existing data, it was obtained using the K-Nearest Neighbor method. This application was able to predict the number of chicken egg supplies at UD Unggas Karya Mandiri. It can be seen that the prediction application for the number of chicken egg supplies at UD Unggas Karya Mandiri Banggai Laut can be applied with an accuracy of 96.98% of the prediction results obtained.. Keywords: Prediction, Eggs, Accuracy, Inventory, K-Nearest Neighbor
Algoritma Linear Regresi Untuk Prediksi Ketimpangan Pendapatan Berdasarkan Gini Ratio Di Provinsi Gorontalo Husdi; Kamaruddin, Andi
KETIK : Jurnal Informatika Vol. 2 No. 03 (2025): Januari
Publisher : Faatuatua Media Karya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70404/ketik.v2i03.130

Abstract

Ketimpangan pendapatan antar kelompok dapat diukur dengan menggunakan Indeks Gini (Gini Ratio). Indeks Gini dapat bernilai antara 0 hingga 1, dimana semakin kecil/ semakin angka indeks mendekati 0 berarti pendapatan antar kelompok semakin kecil (pemerataan sempurna), sedangkan semakin besar angka indeks/semakin angka indeks mendekati 1 berarti semakin tinggi disparitas pendapatan penduduk di wilayah tersebt. Dalam kurun waktu 5 tahun terakhir, angka indeks gini di Provinsi Gorontalo cenderung stabil pada angka 0,406–0,418. Indeks Gini sempat meningkat pada tahun 2022 namun kembali menurun di tahun 2023 pada angka 0,417. Permasalahan dalam penelitian ini adalah bagaimana cara mengetahui (Gini Ratio) di Provinsi Gorontalo untuk tahun Berikutnya. Penelitian ini menggunakan metode penelitian jenis experimen dengan Subjek penelitian ini adalah prediksi Ketimpangan Pendapatan Antar Kelompok Di Provinsi Gorontalo. Metode Regresi Linear Sederhaan dapat digunakan untuk memprediksi Ketimpangan Pendapatan Berdasarkan Gini Rasio Antar Kelompok Di Provinsi Gorontalo secara tepat dan akurat, hal ini berdasrkan dari hasil pengujian dan mendapatkan nilai MAPE 0,83 % dengan interpretase mape kategori Sangat tepat/ kemampuan peramalan Sangat baik
Co-Authors baguna, filda Husdi Ricardus Anggi Pramunendar Sunarto Taliki Vincent Suhartono