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All Journal ILKOM Jurnal Ilmiah Simtek : Jurnal Sistem Informasi dan Teknik Komputer Jambura Journal of Electrical and Electronics Engineering Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Restikom : Riset Teknik Informatika dan Komputer Jurnal Minfo Polgan (JMP) Jurnal Nasional Cosphi Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer (BALOK) Journal Of Informatics And Busisnes Empiris Jurnal Pengabdian Pada Masyarakat (EJPPM) Jurnal Pengabdian Pada Masyarakat Eldimas
Maryam Hasan
Universitas Ichsan Gorontalo
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences

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Rancang Bangun Aplikasi Pencarian Toko Oleh-Oleh Terdekat Berbasis Android Menggunakan Algoritma Floyd Warshall Mahmud, Mohamad An Nafli; Maryam Hasan; Warid Yunus; Syarifah Fitrah Ramadani
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 3 No 1 (2024): Mei 2024
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37195/balok.v3i1.842

Abstract

Abstract- Information technology develops rapidly. The effect can be seen through the increasing use of mobile devices in supporting daily activities in carrying out various activities. With the development of mobile technology, mobile devices offer a variety of advanced computing capabilities known as smartphones. The role of smartphones is to have a good impact if the embedded applications are equipped with good service quality to support users to do or to search for a place or location. Through supporting applications, users can use it more easily, more economically, and more efficiently.  In addition, users can also find out the current developing technology model. The development of souvenir centers depends on tourism industry products regarding the tourism concept and convenience in tourism visits. The tourism sector is also very influential in the socio-cultural field, and of course, in the economic field because it can open up new business opportunities. The design of the nearest souvenir shop search application helps in finding the closest route to the souvenir shop by applying the Floyd Warshall algorithm.  The research results produce a system that can find the nearest souvenir shop and is expected to help the community in finding the nearest souvenir shop in Gorontalo City.   Keywords: nearest location point search application, souvenir shop, Floyd Warshall algorithm
Implementasi Metode XGBoost Dalam Seleksi Atribut Pada Algoritma K-Means Untuk Clustering Masyarakat Penerima Bantuan Langsung Tunai Amiruddin; Maryam Hasan; Muhammad Erdiansyah
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 3 No 2 (2024): November 2024
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37195/balok.v3i2.1193

Abstract

Penelitian ini mengkaji implementasi metode XGBoost dalam seleksi atribut pada algoritma K-Means untuk clustering masyarakat penerima Bantuan Langsung Tunai (BLT). Dalam konteks ini, 14 atribut awal digunakan untuk menggambarkan karakteristik rumah tangga penerima BLT: Luas Lantai, Lantai Rumah, Dinding Rumah, MCK, Sumber Listrik, Sumber Air, Bahan Bakar, Konsumsi, Pakaian, Tidak Sanggup Berobat, Sumber Penghasilan KK, Penghasilan KK, Pendidikan KK, dan Tabungan. Metode XGBoost diaplikasikan untuk menyeleksi atribut yang paling relevan dalam menentukan kelompok penerima BLT. Dari hasil seleksi, ditemukan tiga atribut penting yaitu Luas Lantai, Lantai Rumah, dan Penghasilan KK. Implementasi K-Means clustering dilakukan dua kali, pertama menggunakan seluruh atribut dan kedua menggunakan tiga atribut penting yang telah diseleksi oleh XGBoost. Analisis hasil clustering menunjukkan bahwa sebelum seleksi atribut, nilai Davies-Bouldin Index (DBI) sebesar 1.325. Setelah seleksi atribut penting, nilai DBI menurun menjadi 0.800. Penurunan nilai DBI sebesar 0.525 ini mengindikasikan bahwa hasil clustering menjadi lebih optimal setelah penerapan XGBoost. Dengan demikian, penelitian ini menyimpulkan bahwa penggunaan XGBoost untuk seleksi atribut dapat meningkatkan kinerja K-Means dalam clustering masyarakat penerima BLT, menghasilkan grup yang lebih jelas dan homogen. Temuan ini memiliki implikasi penting untuk meningkatkan efisiensi dan efektivitas program penyaluran BLT dengan mendasarkan keputusan pada atribut yang paling berpengaruh. Kata Kunci: XGBoost, K-Menas, Clustering, Seleksi Atribut, Bantuan Langsung Tunai
INTELLIGENT SYSTEM FOR IDENTIFYING AVOCADO RIPE USING EXTRACTION FEATURES AND K-NEAREST NEIGHBOR METHOD Maryam Hasan
Jurnal RESTIKOM : Riset Teknik Informatika dan Komputer Vol 5 No 3 (2023): Desember
Publisher : Program Studi Teknik Informatika Universitas Nusa Putra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/restikom.v5i3.252

Abstract

So far, farmers in harvesting avocados often experience obstacles, namely farmers are still not precise in determining ripe avocados. The ripeness of avocado when harvested is one of the most important factors in maintaining the quality of the avocado. This is due to fatigue and takes a long time so it is not appropriate to determine which avocados are ripe and which are not. Therefore, a system is needed to find out avocados. This study formulates problems in the form of how to identify avocado identification with the KNN method and how to find out how much accuracy the method obtained. While the objectives achieved in this study can identify avocados based on the KNN method and can measure the accuracy of the method with avocado image data. The results obtained in this study were successful in identifying and using the 80% measurement confusion matrix.
Dampak Ekonomi dan Sosial UMKM Kue Sabongi terhadap Kesejahteraan Masyarakat Desa Motilango Dunggio, Swastiani; Hasan, Maryam; Salihi, Irvan; Abdussamad, Juriko; Gaffar, Gaffar; Abdussamad, Syahrir
Empiris Jurnal Pengabdian Pada Masyarakat Vol. 3 No. 1 (2025): Volume 3 Nomor 1 April 2025
Publisher : Fakultas Ilmu Sosial dan Ilmu Politik Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59713/ejppm.v3i1.1367

Abstract

Kue Sabongi merupakan salah satu produk pangan yang memiliki potensi besar dalam meningkatkan perekonomian masyarakat, khususnya di Motilango. Dalam konteks ini, penting untuk memahami bagaimana pengembangan produk lokal seperti Kue Sabongi dapat memberikan dampak signifikan terhadap kesejahteraan masyarakat. Dengan demikian, pengabdian ini bertujuan untuk mendampingi masyarakat Desa Motilango dalam pengembangan usaha mikro, kecil, dan menengah yang berbasis pada Kue Sabongi, yang tidak hanya mengedepankan aspek produksi tetapi juga pemasaran dan pengemasan. Pendampingan ini diharapkan dapat meningkatkan keterampilan masyarakat dalam memproduksi Kue Sabongi yang memiliki nilai jual tinggi. Metode yang diterapkan dalam pengabdian ini adalah pendekatan partisipatif, di mana masyarakat dilibatkan secara aktif dalam setiap tahap proses produksi. Hasil dari pendampingan ini menunjukkan bahwa masyarakat tidak hanya mampu memproduksi Kue Sabongi secara mandiri, tetapi juga memahami pentingnya aspek pemasaran dan pengemasan yang menarik. Dalam hal ini, pengemasan produk menjadi salah satu faktor kunci yang dapat mempengaruhi keputusan konsumen untuk membeli. Oleh karena itu, dalam pengabdian ini, masyarakat diajarkan cara mendesain kemasan yang menarik serta mencantumkan informasi yang relevan mengenai produk. Dengan demikian, diharapkan produk ini dapat menjadi salah satu sumber pendapatan baru bagi masyarakat Desa Motilango. Selain itu, pengembangan Kue Sabongi juga berpotensi untuk meningkatkan daya saing produk lokal di pasar yang lebih luas. Oleh karena itu, penting bagi masyarakat untuk terus berinovasi dan beradaptasi dengan tren pasar yang berkembang. Sabongi Cake is one of the food products that has great potential in improving the economy of the community, especially in Motilango. In this context, it is important to understand how the development of local products such as Sabongi Cake can have a significant impact on community welfare. Thus, this community service aims to assist the Motilango Village community in developing micro, small, and medium enterprises based on Sabongi Cake, which not only prioritizes production aspects but also marketing and packaging. This assistance is expected to improve community skills in producing Sabongi Cake which has high selling value. The method applied in this community service is a participatory approach, where the community is actively involved in every stage of the production process. The results of this assistance show that the community is not only able to produce Sabongi Cake independently, but also understands the importance of marketing aspects and attractive packaging. In this case, product packaging is one of the key factors that can influence consumer decisions to buy. Therefore, in this community service, the community teaches how to design attractive packaging and include relevant information about the product. Thus, it is hoped that this product can become a new source of income for the Motilango Village community. In addition, the development of Sabongi Cake also has the potential to increase the competitiveness of local products in a wider market. Therefore, it is important for the community to continue to innovate and adapt to developing market trends.
Pemberdayaan Masyarakat Melalui Pelatihan Pembuatan Keripik Pisang Hasan, Maryam; Salihi, Irvan; Dunggio, Swastiani; Abdussamad, Juriko; Gaffar, Gaffar; Abdussamad, Syahrir
ELDIMAS: Jurnal Pengabdian Pada Masyarakat Vol 3 No 1 (2025): Mei - Oktober 2025
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/ejppm.v3i1.39

Abstract

Desa Motilango memiliki potensi sumber daya alam berupa pisang pagata yang melimpah. Namun, pemanfaatannya masih terbatas pada penjualan sebagai bahan mentah, sehingga tidak memberikan nilai tambah yang signifikan. Untuk mengatasi hal ini, dilakukan kegiatan pengabdian masyarakat melalui pelatihan pembuatan keripik pisang guna meningkatkan nilai ekonomi produk lokal. Kegiatan ini menerapkan metode partisipatif yang melibatkan ibu-ibu Dasawisma sebagai mitra lokal dalam seluruh tahapan, mulai dari observasi kondisi desa, pelatihan pembuatan keripik, pendampingan produksi, hingga pelatihan pengemasan dan pemasaran. Hasil kegiatan menunjukkan peningkatan keterampilan masyarakat dalam menghasilkan keripik pisang dalam tiga varian rasa, serta kemampuan dalam pengemasan dan pemasaran produk. Beberapa peserta bahkan telah berhasil memasarkan produknya di pasar lokal. Kegiatan ini diharapkan mampu meningkatkan pendapatan masyarakat dan mendorong pertumbuhan UMKM berbasis potensi lokal. Motilango Village has abundant natural resource potential in the form of pagata bananas. However, its utilization is still limited to sales as raw materials, so it does not provide significant added value. To overcome this, community service activities were carried out through banana chip making training to increase the economic value of local products. This activity applies a participatory method that involves Dasawisma mothers as local partners in all stages, starting from observing village conditions, chip making training, production assistance, to packaging and marketing training. The results of the activity showed an increase in community skills in producing banana chips in three flavors, as well as the ability to package and market products. Several participants have even succeeded in marketing their products in the local market. This activity is expected to increase community income and encourage the growth of MSMEs based on local potential.
Penerapan Metode Apriori Pada Transaksi Penjualan Spare Parts Mobil Maryam Hasan; Sudirman S Panna; Siska Udilawati; Almer Hassan Ali
Journal Of Informatics And Busisnes Vol. 3 No. 2 (2025): Juli - September
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v3i2.3093

Abstract

Until now, commercial vehicle manufacturers continue to innovate their products. One of the manufacturers is PT Nenggapratama Prima Nusantara, engaged in trade and services, namely HINO brand vehicles, spare parts, and services in direct collaboration with PT. Hino Motors Indonesia. The high demand and various types of spare parts certainly drive PT. Nenggapratama Prima Nusantara to maximize existing stock. It aims to ensure that there is no accumulation or shortage of goods. It is important to know the purchasing behavior of customers about which spare parts they buy together. One of the data processing methods usable for this problem is data mining with association analysis using Apriori algorithm. It is a data mining technique that produces rules to determine consumer habits in buying goods simultaneously at once. Based on the results of research using the Apriori method, the largest value (Support x Confidence) is obtained at 0.33. The biggest possibility is that if you buy the Dutro E-4 Fuel Strainer Kit, you will also buy Element Sub Assy Oil with a value of 0.33. Therefore, it can be seen that related spare parts can be arranged simultaneously.
Application of the K-Medoids Clustering Algorithm to Determine the Nutritional Status of Toddlers Betrisandi, Betrisandi; Hasan, Maryam; Bahrin, Bahrin
Jambura Journal of Electrical and Electronics Engineering Vol 7, No 1 (2025): Januari - Juni 2025
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v7i1.27523

Abstract

Stunting is a chronic malnutrition problem due to a lack of nutritional intake in the body for a long time, as a result of which there is a growth disorder in children, namely the child's height becomes shorter or dwarfed than the standard age. The problem of malnutrition in toddler is a major concern in various countries. Based on the data from the Ministry of Health of the Republic of Indonesia in 2018, 30.8% of Indonesian toddlers were malnourished. Malnutrition in toddlers is very influential on physical and mental growth such as intellectual intelligence, speaking, walking, learning, immune system and low body immune system. The purpose of thisstudy is to classify the nutritional status of toddler into five cluster namely cluster 0 poor, cluster 1 undernourished, cluster 2 good nutrition, cluster 3 over nutrition and cluster 4 obesity by using the K-Medoids Algorithm method. K-Medoids Algorithmis one of the Algorithm used in data and mining. K-Medoids Algorithm is relatively fast and simple, making it easier to find Medoids in a group (cluster). Based on the data on toddlers there are 74 toddlers, the results of clustering are obtained from grouping, cluster 0 is 13 toddlers with bad nutrition, cluster 1 is undernutrition 15 toddlers, cluster 2 is good nutrition 21 toddlers, cluster 3 is over nutrition 23 toddlers and cluster 4 is obesity totaling 2 toddlers.Stunting merupakan masalah kurang gizi kronis karena kurangnya asupan gizi pada tubuh dalam waktu yang cukup lama akibatnya terjadi gangguan pertumbuhan pada anak-anak yakni tinggi badan anak menjadi lebih pendek atau kerdil dari standar usianya. Masalah kurang gizi padakelompok balita menjadi perhatian utama diberbagai negara. Berdasarkan data Kemenkes RI tahun 2018 sebanyak 30,8 % balita Indonesia mengalami gizi buruk. Gizi kurang pada balita sangat berpengaruh pada pertumbuhan fisik maupun mental seperti kecerdasan intelektual, berbicara, berjalan, belajar, daya tahan tubuh serta sistem imun tubuh rendah. Adapun tujuan dari penelitian ini adalah untuk mengelompokkan status gizi balita ke dalam 5 cluster yaitu cluster 0 gizi buruk, cluster 1 gizi kurang, cluster 2 gizi baik, cluster 3 gizi lebih dan cluster 4 obesitas dengan menggunakan metode Algoritma K-Medoids. Algoritma K-Medoids merupakan salah satu algoritma yang digunakan dalam data mining. Algoritma K-medoids relatif cepat dan sederhana sehingga memudahkan menemukan medoids dalam sebuah kelompok (cluster). Berdasarkan data balita yang ada sejumlah 74 balita maka didapatkan hasil clustering dari pengelompokkan dengan cluster 0 yaitu gizi Buruk berjumlah 13 balita, cluster 1 yaitu gizi kurang berjumlah 15 balita, cluster 2 yaitu gizi baik sejumlah 21 balita, cluster 3 yaitu gizi lebih berjumlah 23 balita dan cluster 4 obesitas berjumlah 2 balita. 
Grouping of Areas Based on Flood Disaster Level Using K-Means Clustering Algorithm Hasan, Maryam; Panna, Sudirman S.; Haba, Abd. Rahmat Karim; Alhamad, Apriyanto
Jambura Journal of Electrical and Electronics Engineering Vol 8, No 1 (2026): Januari - Juni 2026
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v8i1.33145

Abstract

The Province of Gorontalo is highly vulnerable to flood disasters due to its geographical conditions, high rainfall, and uncontrolled land-use changes. This study aims to apply the K-Means Clustering algorithm to classify regions based on flood impact levels to support disaster mitigation and decision-making processes by the National Search and Rescue Agency (BNPP) Gorontalo. The dataset comprises 405 disaster incident records obtained from related institutions, including the number of affected, injured, deceased, and missing individuals. The analysis process involves data collection, preprocessing, distance calculation using the Euclidean Distance method, and the formation of two clusters based on impact levels. The iteration process stopped at the second iteration, indicating that a stable (convergent) condition had been achieved. The results revealed that Cluster 1 (C1) includes areas significantly affected by floods such as Imana, Iloheluma, and Tudi villages, while Cluster 2 (C2) represents unaffected areas like Wapalo, Ilomata, Motihelumo, and others. The implementation of the K-Means algorithm proved effective in identifying disaster-prone regions objectively and data-driven, thus supporting more efficient disaster response planning.
PREDIKSI TINGKAT KELANCARAN PEMBAYARAN KREDIT BANK MENGGUNAKAN ALGORITMA NAÏVE BAYES BERBASIS FORWARD SELECTION Hasan, Maryam
ILKOM Jurnal Ilmiah Vol 9, No 3 (2017)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v9i3.163.317-324

Abstract

Tujuan dari Penelitian ini adalah Mengoptimalkan algoritma Naïve Bayes dengan seleksi fitur Forward Selection untuk dapat meningkatkan hasil akurasi atau tingkat keberhasilan yang didapatkan dari prediksi pembayaran kredit.Data yang akan digunakan dalam penelitian ini berasal dari Bank XY yang berada di Gorontalo. Data yang diperoleh berkaitan dengan semua aspek dari nasabah kredit termasuk informasi pribadi dari nasabah. Desain eksperimen dalam penelitian ini menggunakan dataset nasabah kredit.sedangkan analisi yang digunakan adalah Model algoritma Naïve Bayes dengan seleksi fitur Forward Selection. Prediksi tingkat kelancaran pembayaran kredit menggunakan algoritma Naïve Bayes berbasis Forward Selection mampu memprediksi kelancaran pembayaran kredit ke depannya hal ini terbukti dengan perolehan nilai akurasi Naive bayes berbasis Forward Selection mampu mencapai nilai akurasi 71,97 %.
Local Binary Pattern untuk Pengenalan Jenis Daun Tanaman Obat menggunakan K-Nearest Neighbor Lamasigi, Zulfrianto Y; Hasan, Maryam; Lasena, Yulianti
ILKOM Jurnal Ilmiah Vol 12, No 3 (2020)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i3.667.208-218

Abstract

Tanaman obat tradisional merupakan jenis tanaman yang mengandung zat aktif yang berfungsi mengobati ataupun mencegah dari berbagai macam penyakit. Oleh karena itu dilakukan penelitian untuk menguji metode Local Binary Pattern untuk ektraksi ciri dari setiap tanaman obat tradisional dan K-Nearest Neighbor pada proses klasifikasi setelah dilakukan ektraksi dari metode Local Binary Pattern. Dari pengujian menggunakan metode Local Binary Pattern dan K-Nearest Neighbor mampu menghasilkan akurasi yang cukup baik yaitu sebesar 96.67%, nilai akurasi tersebut didapat dari perhitungan manual convusion matrix dengan nilai k=9. Sementara itu hasil akurasi terendah ada pada nilai k=1 yaitu 0%. Hasil ektraksi dan klasifikasi dari metode Local Binary Pattern dan K-Nearest Neighbor menggunakan 120 dataset yang dibagi menjadi 90 data training dengan 6 jenis daun tanaman obat yang terdiri dari 15 daun bayam duri, 15 daun binahong, 15 daun jarak, 15 daun afrika, dan 15 daun sirih dengan percobaan 30 data testing.
Co-Authors Almer Hassan Ali Amiruddin Bengnga Apriyanto Alhamad Bahrin Bahrin Betrisandi, Betrisandi Gaffar, Gaffar Haba, Abd. Rahmat Karim Husdi Ismail S Manto Juriko Abdussamad Mahmud, Mohamad An Nafli Muhammad Erdiansyah Muhammad Faisal Panna, sudirman S. Pelangi, Kartika Candra Ramadhani, Syarifah Fitrah Rifdah Rofifah Faruk Abdullah Salihi, Irvan Siska Udilawati Sudirman S Panna Swastiani Dunggio Syahrir Abdussamad Warid Yunus Yulianti Lasena Zulfrianto Yusrin Lamasigi