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Aplikasi Penentuan UMKM Terbaik Sekabupaten Kepulauan Selayar Sulawesi Selatan Menggunakan Metode Weighted Product Muhammd Faisal; Suardi Hi Baharuddin
Journal of Practical Computer Science Vol. 3 No. 1 (2023): Mei 2023
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v3i1.2368

Merujuk pada Undang-Undang Nomor 20 Tahun 2008 tentang Usaha Mikro, Kecil, dan Menengah, UMKM alias usaha mikro adalah usaha milik perseorangan atau badan usaha perorangan yang produktif dan memenuhi kriteria yang ditulis oleh undang-undang. Tujuan penelitian ini adalah untuk Memanfaatkan peran teknologi dalam pengaplikasian penentuan UMKM terbaik pada DINAS PERIMDAGKUM Kabupaten Kepulauan Selayar. Metode Weighted Produk dapat digunakan dalam proses pengambilan keputusan berbasis multi kriteria. Penerapan metode Weighted Product didalam penentuan kinerja UMKM dengan menggunakan kriteria penilaian berupa jumlah karyawan, aset karyawan omset pertahun, pemodal, terget pasar, sistem pemasaran, karakter produk. Hasil yang dicapai pada penelitian ini adalah membangun sebuah aplikasi sistem pendukung keputusan dalam penentuan status UMKM terbaik yang diterapkan pada DINAS PERIMDAGKUM Kabupaten Kepulauan Selayar secara akuntable dan objektif

Pengembangan Authoring Tools Pembelajaran Bahasa Pascal Menggunakan Teknik Transformasi Bagi Siswa Sekolah Menengah Kejuruan Andi Harmin; Muhammad Faisal
Journal of Practical Computer Science Vol. 3 No. 1 (2023): Mei 2023
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v3i1.2371

Pengembangan perangkat lunak pembelajaran sekarang ini mengalami peningkatan seiring dengan kemajuan teknologi. Kebutuhan alat peraga yang digunakan untuk proses belajar mengajar juga harus berubah sesuai dengan kebutuhan dan perkembangan zaman. Salah satunya adalah pengembangan alat peraga interaktif sebagai fasilitas bagi pengajar maupun peserta didik khusus pada mata kuliah dasar pemrograman. Alat peraga interaktif yang menggunakan teknik transformasi akan lebih efektif dalam menggunakan waktu untuk memberikan materi sebanyak yang dibutuhkan.

Iterative Dichotomiser Three (Id3) Algorithm For Classification Community of Productive and Non-Productive Ida Ida Ida
JURNAL TEKNIK INFORMATIKA Vol 16, No 1 (2023): JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v16i1.28938

One way to tackle poverty is to provide information about productive and non-productive communities in each rural. This is very beneficial for the government, especially in each rural regarding the classification of community data. This research aims to classify productive and non-productive people so that the government can prioritize assistance for people deemed necessary to be more creative in fulfilling their family's economy. The research method used is the Iterative Dichitomiser Three (ID3) algorithm to build a decision tree. The process in the decision tree is changing the shape of the data (table) into a tree (tree) and generating rules based on the highest Entropy and Gain values. The study's conclusion shows that this algorithm can be processed in a shorter time, with shorter decision rules and higher prediction accuracy, by displaying the highest gain value. The parameters used to consist of education, age, income, and employment status, which results in the following rule if higher education and high income, then the result is a productive society, whereas if high school education and low income, then the result is a non-productive society.

ANALISIS KELAYAKAN APP-INVENTOR SEBAGAI BAHAN AJAR MATAKULIAH MOBILE PROGRAMMING MENGGUNAKAN METODE SYSTEM USABILITY SCALE Ida Mulyadi; Muhammad Faisal; Nurul Qalbi; Indra Aditya
PROGRESS Vol 15 No 1 (2023): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v15i1.354

Media in the learning process is a tool or intermediary in the delivery of learning material that can provide more knowledge and experience to students. The advantage of App Inventor lies in the ease of programming, where users do not need to have basic programming knowledge, understand code, or have experience in IT, but the most important thing in making applications using App Inventor is how programmers use logic like when someone puts together a puzzle. . In this research, a feasibility study and analysis was carried out using the System Usability Scale (SUS) method so that it could improve the quality of learning and the novelty of teaching materials in the Makassar Professional STMIK environment. The sampling technique used in this research is random sampling or probability sampling. Based on the results of the recapitulation of the respondents' assessment, the average usability of the system was 72.83, then the grade of the assessment was determined. It was concluded that the results of the Recap of Usability Values showed that all attributes had a usability acceptance value by the user, the average value was above 68.00, namely 72.83. For Android users to be able to use APP-Inventor properly so that it is useful to support special learning activities in the Mobile Programming course.

ANALISIS KELAYAKAN APP-INVENTOR SEBAGAI BAHAN AJAR MATAKULIAH MOBILE PROGRAMMING MENGGUNAKAN METODE SYSTEM USABILITY SCALE Ida Mulyadi; Muhammad Faisal; Nurul Qalbi; Indra Aditya
PROGRESS Vol 15 No 1 (2023): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v15i1.354

Media in the learning process is a tool or intermediary in the delivery of learning material that can provide more knowledge and experience to students. The advantage of App Inventor lies in the ease of programming, where users do not need to have basic programming knowledge, understand code, or have experience in IT, but the most important thing in making applications using App Inventor is how programmers use logic like when someone puts together a puzzle. . In this research, a feasibility study and analysis was carried out using the System Usability Scale (SUS) method so that it could improve the quality of learning and the novelty of teaching materials in the Makassar Professional STMIK environment. The sampling technique used in this research is random sampling or probability sampling. Based on the results of the recapitulation of the respondents' assessment, the average usability of the system was 72.83, then the grade of the assessment was determined. It was concluded that the results of the Recap of Usability Values showed that all attributes had a usability acceptance value by the user, the average value was above 68.00, namely 72.83. For Android users to be able to use APP-Inventor properly so that it is useful to support special learning activities in the Mobile Programming course.

SOSIALISASI PENGENALAN APP INVENTOR BERBASIS MOBILE PROGRAMMING Muhammad Faisal; Ida Ida; Muhammad Khaiyyir; Adnan Ahsan
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 7, No 3 (2023): September
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v7i3.17153

ABSTRAKSMA Ittihad adalah salah satu sekolah swasta yang berdiri sejak tahun 1983, beralamat di jalan G. Lokon No. 44, Kecamatan Makassar, Kota Makassar, Sulawesi Selatan 90145. Minimnya pengetahuan siswa siswi mengenai penggunaan software khususnya bahasa pemrograman berbasis mobile programming. Perlu adanya pemberian pemahaman dan gambaran terkait cara pembuatan aplikasi mobile tanpa menggunakan pengkodean program. Keunggulan App Inventor terletak pada kemudahan pemrograman, dimana pengguna tidak perlu memiliki pengetahuan pemrograman dasar, memahami kode, atau memiliki pengalaman di bidang IT, namun yang terpenting dalam membuat aplikasi menggunakan App Inventor adalah bagaimana programmer menggunakan logika seperti saat seseorang menyusun teka-teki. Pelatihan pengenalan App Inventor berbasis mobile programming menjadi salah satu solusi untuk meningkatkan minat dan pengetahuan serta kemampuan Siswa siswi SMA Ittihad Makassar dalam membuat sebuah aplikasi tanpa menuliskan coding dari program tersebut. Tujuan pelatihan ini adalah meningkatkan pengetahuan siswa dalam pembuatan aplikasi mobile tanpa menggunakan pengkodean. Pelatihan dilakukan dengan metode presentasi, demonstrasi, serta praktik langsung. Untuk mengukur pencapaian maka dilakukan pengisian kuesioner sebelum dan sesudah pelatihan. Hasil kuesioner menunjukkan adanya peningkatan pengetahuan peserta pelatihan terkait penggunaan app inventor. Mengalami peningkatan menjadi rata-rata sebesar 68,25% setelah diberi pelatihan. Kata kunci: app inventor; pelatihan; system usability scale. ABSTRACTSMA Ittihad is one of the private schools established since 1983, located at Jalan G. Lokon No. 44, Makassar District, Makassar City, South Sulawesi 90145. The lack of knowledge of students about the use of software, especially mobile programming-based programming languages. It is necessary to provide understanding and overview related to how to make mobile applications without using program coding. The advantage of App Inventor lies in the ease of programming, where users do not need to have basic programming knowledge, understand code, or have experience in the IT field, but the most important thing in creating applications using App Inventor is how programmers use logic like when someone puts together a puzzle. Mobile programming-based App Inventor introduction training is one solution to increase the interest and knowledge and ability of Ittihad Makassar High School students in making an application without writing down the coding of the program. The purpose of this training is to increase students' knowledge in making mobile applications without using coding. Training is carried out by presentation, discussion, and direct practice. To measure achievement, questionnaires were filled out before and after training. The results of the questionnaire showed an increase in training participants' knowledge regarding the use of app inventors. Increased to an average of 68,25% after being given training. Key Word: app inventor; training; system usability scale.

A hybrid hue saturation lightness, gray level co-occurrence matrix, and k-nearest neighbour for palm-sugar classification Jumarlis, Mila; Mulyadi, Ida; Mirfan, Mirfan; Imawati, Irmawati; Mardiah, Mardiah; Faisal, Muhammmad; Anisa, Hairin
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp2934-2945

In recent years, there has been an increasing demand for high-quality raw materials driven by consumers and the food industry. This study aims to build a model to predict the type of palm sugar using a hybrid method of hue-saturation-lightness (HSL), gray level co-occurrence matrix (GLCM), and K-nearest neighbor (KNN). The price of palm sugar is determined based on the type and ingredients used. However, due to the lack of public knowledge in distinguishing the types of palm sugar, there is the potential for price manipulation that can harm the community. The accuracy rate of 97.6% of the palm sugar type prediction results shows that the model that was built has worked very well. The results have practical implications, such as developing automated systems to classify palm species in specific industries to benefit economics and operational efficiency. Future research directions may explore the integration of advanced machine-learning techniques and real-time image processing for further improving classification performance and scalability in industrial applications.

A hybrid hue saturation lightness, gray level co-occurrence matrix, and k-nearest neighbour for palm-sugar classification Jumarlis, Mila; Mulyadi, Ida; Mirfan, Mirfan; Imawati, Irmawati; Mardiah, Mardiah; Faisal, Muhammmad; Anisa, Hairin
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp2934-2945

In recent years, there has been an increasing demand for high-quality raw materials driven by consumers and the food industry. This study aims to build a model to predict the type of palm sugar using a hybrid method of hue-saturation-lightness (HSL), gray level co-occurrence matrix (GLCM), and K-nearest neighbor (KNN). The price of palm sugar is determined based on the type and ingredients used. However, due to the lack of public knowledge in distinguishing the types of palm sugar, there is the potential for price manipulation that can harm the community. The accuracy rate of 97.6% of the palm sugar type prediction results shows that the model that was built has worked very well. The results have practical implications, such as developing automated systems to classify palm species in specific industries to benefit economics and operational efficiency. Future research directions may explore the integration of advanced machine-learning techniques and real-time image processing for further improving classification performance and scalability in industrial applications.

A hybrid hue saturation lightness, gray level co-occurrence matrix, and k-nearest neighbour for palm-sugar classification Jumarlis, Mila; Mulyadi, Ida; Mirfan, Mirfan; Imawati, Irmawati; Mardiah, Mardiah; Faisal, Muhammmad; Anisa, Hairin
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp2934-2945

In recent years, there has been an increasing demand for high-quality raw materials driven by consumers and the food industry. This study aims to build a model to predict the type of palm sugar using a hybrid method of hue-saturation-lightness (HSL), gray level co-occurrence matrix (GLCM), and K-nearest neighbor (KNN). The price of palm sugar is determined based on the type and ingredients used. However, due to the lack of public knowledge in distinguishing the types of palm sugar, there is the potential for price manipulation that can harm the community. The accuracy rate of 97.6% of the palm sugar type prediction results shows that the model that was built has worked very well. The results have practical implications, such as developing automated systems to classify palm species in specific industries to benefit economics and operational efficiency. Future research directions may explore the integration of advanced machine-learning techniques and real-time image processing for further improving classification performance and scalability in industrial applications.

A hybrid hue saturation lightness, gray level co-occurrence matrix, and k-nearest neighbour for palm-sugar classification Jumarlis, Mila; Mulyadi, Ida; Mirfan, Mirfan; Imawati, Irmawati; Mardiah, Mardiah; Faisal, Muhammmad; Anisa, Hairin
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp2934-2945

In recent years, there has been an increasing demand for high-quality raw materials driven by consumers and the food industry. This study aims to build a model to predict the type of palm sugar using a hybrid method of hue-saturation-lightness (HSL), gray level co-occurrence matrix (GLCM), and K-nearest neighbor (KNN). The price of palm sugar is determined based on the type and ingredients used. However, due to the lack of public knowledge in distinguishing the types of palm sugar, there is the potential for price manipulation that can harm the community. The accuracy rate of 97.6% of the palm sugar type prediction results shows that the model that was built has worked very well. The results have practical implications, such as developing automated systems to classify palm species in specific industries to benefit economics and operational efficiency. Future research directions may explore the integration of advanced machine-learning techniques and real-time image processing for further improving classification performance and scalability in industrial applications.

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