Ahmad Ilham

• Master of Computer Science
• Lecturer at Universitas Muhammadiyah Semarang

Genting Village, Semarang, has great potential for mushroom cultivation thanks to geographical and climatic conditions that favour healthy mushroom growth. Although farm women have been actively involved in mushroom cultivation in this village, they often face obstacles in terms of access to resources, knowledge, and marketing of mushroom-based pro...

In this study, we address the intricate challenge of classifying fetal health risks in pregnant women using cardiotocography (CTG) datasets. Our proposed method, CFCM-SMOTE, is tailored to handle outlier issues and imbalanced data, enhancing the accuracy of fetal health assessment. By employing this approach during data preprocessing, we achieved s...

Tindak kecurangan presensi sering kali ditemukan adanya kehadiran palsu dari mahasiswa. Untuk mengatasi hal tersebut, kami menerapkan metode Haar-Like Feature Cascade sebagai dasar dalam membangun sistem presensi wajah berbasis Cognitive Internet of Things (CIoT). System yang diusulkan bekerja dengan merepresentasikan pola intensitas lokal pada cit...

There is a significant imbalanced class in the village development index (called IDM - Indeks Desa Membangun) dataset, marked by the number of self-supporting classes more than the disadvantaged class. The traditional classifiers are able to achieve high accuracy (ACC) by training all cases of the majority class but forsaking the minority class, so...

Madrasah Ibtidaiyah (MI) Duren Village and Sabilul Huda Jimbaran Bandungan District Semarang Regency want to produce quality graduates. However, the competence of teachers is still conventional learning aids so the learning process is not optimal. To answer this problem, the Department of Informatics, Faculty of Engineering at Universitas Muhammadi...

[ID] Buku ini membahas mengenai Pengertian Penelitian dan Tahapannya; Partisipan dan Etika Penelitian; Mereview Literatur; Penelitian Ethnography; Interviu dan Observasi sebagai Metode Pengambilan Data; Kuesioner dan Dokumen sebagai Metode Pengambilan Data.

Sejak zaman dahulu, literasi sudah menjadi bagian dari kehidupan dan perkembangan manusia, dari zaman prasejarah hingga zaman modern. Pada zaman prasejarah manusia hanya membaca tanda-tanda alam untuk berburu dan mempertahankan diri. Dalam konteks pembelajaran, literasi digital memungkinkan siapapun yang menguasainya sehingga dapat memperoleh penge...

One of the oldest known predictive analytics techniques is time series prediction. The target in time series prediction is use historical data about a specific quantity to predicts value of the same quantity in the future. Multivariate time series (MTS) data has been widely used in time series prediction research because it is considered better tha...

Rainfall which is occurred in an area explain the Onset Rainy Season (ORS). ORS is a characteristic of the rainy season which is important to know, but the characteristics of the rain itself is very difficult to predict. We use the method of Fuzzy Inference System (FIS) to predict ORS. Unfortunately, FIS is weak to determine parameters so that infl...

The kidneys are one of the most important organs including the excretion system in humans. The kidneys are responsible for maintaining blood concentrations to remain constant (homeostatic) and help to control blood pressure (BP). If the task of the kidney is not functioning properly it will cause kidney failure. In the past decade, data mining meth...

Clustering is one of the major roles in data mining that is widely application in pattern recognition and image segmentation. Fuzzy C-means (FCM) is the most used clustering algorithm that proven efficient, fast and easy to implement, however, FCM uses the Euclidean distance that often leads to clustering errors, especially when handling multidimen...

Determining the cluster number in k-means is problematic since it affects the quality of cluster for numerous applications in the data mining. The automatic clustering differential evolution (ACDE) is one of the most used clustering methods that are able to determine the cluster number automatically. However, ACDE still makes use of the manual stra...

The initial centroid is a fairly challenging problem in the k-means method because it can affect the clustering results. In addition, choosing the starting centroid of the cluster is not always appropriate, especially, when the number of groups increases.

Penentuan jumlah klaster k-Means adalah masalah utama yang paling popular di kalangan peneliti data mining karena sulitnya menentukan informasi dari data secara apriori akibatnya dimungkinkan hasil klaster tidak optimal dan cepat terjebak ke dalam minimum lokal. Metode pengklasteran otomatis dengan pendekatan evolutionary computation (EC) dapat men...

The initial centroid is a fairly challenging problem in the k-means method because it can affect the clustering results. In addition, choosing the starting centroid of the cluster is not always appropriate, especially, when the number of groups increases. The random technique is often used to overcome this problem, but it produces a variety of solu...

Berkah Mart is one of the new minimarkets in Pekanbaru city which began to develop as a retail business to meet the needs of the community. In his operation, Berkah Mart still uses the traditional store management perception that the placement of product layout on sale shelves has not been through sales analysis. Existing products have not been rev...

Recent studies of attribute independent assumptions on Naïve Bayes (NB) typically generate data sets, methods and frameworks that enable researchers to focus on development activities in terms of finding solutions to attribute independent issues, thereby enhancing the quality of NB classification and better utilizing resources. Many data sets deal...

Saat ini data real dari berbagai sumber sangat banyak mengandung data dengan kelas tidak seimbang. Masalah data kelas tidak seimbang dapat menimbulkan efek buruk pada metode klasifikasi untuk ketepatan prediksi pada data. Untuk menangani masalah ini, telah banyak penelitian sebelumnya menggunakan algoritma klasifikasi menangani masalah data kelas t...

ABSTRAK Masalah data kelas tidak seimbang memiliki efek buruk pada ketepatan prediksi data. Untuk menangani masalah ini, telah banyak penelitian sebelumnya menggunakan algoritma klasifikasi menangani masalah data kelas tidak seimbang. Pada penelitian ini akan menyajikan teknik under-sampling dan over-sampling untuk menangani data kelas tidak seimba...