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All Journal VISIKES Jurnal Transformatika Journal of Information System JOURNAL OF APPLIED INFORMATICS AND COMPUTING Building of Informatics, Technology and Science Jurnal Sistem informasi dan informatika (SIMIKA) Abdimasku : Jurnal Pengabdian Masyarakat MANGGALI
Suharnawi Suharnawi
Program Studi Sistem Informasi Universitas Dian Nuswantoro, Semarang
Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Health Professions Industrial & Manufacturing Engineering Social Sciences

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Penerapan Aplikasi Pengelolaan Data Penduduk Internal Kelurahan (Sipendik) di Kelurahan Panggung Lor Semarang Wibowo, Sasono; Gamayanto, Indra; Suharnawi, Suharnawi; Harini, Harini
Manggali Vol 4 No 1 (2024): Manggali
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat, Universitas Ivet

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31331/manggali.v4i1.3059

Abstract

Kelurahan Panggung Lor Semarang merupakan salah satu Kelurahan yang cukup luas di wilayah kerja Kecamatan Semarang Utara, yaitu dengan luas 123.430 M 2 . Dengan jumlah penduduk 13.233 jiwa yang terbagi ke dalam 3.556 KK, kebutuhan akan system informasi yang berkaitan dengan mutasi ataupun kondisi penduduk sangatlah dibutuhkan mengingat setiap 1 bulan sekali harus membuat laporan mutasi maupun kondisi penduduk tentang perpindahan, kematian, kelahiran, manula, balita ataupun informasi yang lain. SIPENDIK ini dibangun lebih mendasarkan untuk keperluan Kelurahan setempat untuk memudahkan dan mengatasi masalah tersebut diatas. Metode dalam pelaksanaan program PKM ini dimulai dengan identifikassi masalah, alternatif solusi, simulasi, pembuatan dan implementasi system, training, konseling dan evaluasi.
PREDIKSI TINGKAT PERKAWINAN ANAK BERBASIS FUZZY UNTUK MEMINIMALISASI DAMPAK PASCA PERKAWINAN Ashari, Ayu; Setiawan, Aries; Ratnawati, Juli; Wulandari, Fitria; Farida, Ida; Prasetya, Jaka; Suharnawi, Suharnawi; Hallang Lewa, Andi
VISIKES Vol. 23 No. 1 (2024): VISIKES
Publisher : Dian Nuswantoro Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60074/visikes.v23i1.9533

Abstract

Early marriage is a global problem in the world, one of which is Indonesia. Based on data obtained from the Central Statistics Agency in 2020, Central Java is one of the 3 provinces in Indonesia which has the highest child marriage rate, namely 10.85%. Child marriage will have a negative impact on both married teenagers, their families, schools, communities and the country. The government has made efforts to change the legal regulations regarding the minimum age for marriage, namely 19 years, but there are still many teenagers who marry early at less than 19 years with the existence of a marriage dispensation. Efforts are needed to help the government to prevent an increase in child marriage rates and make the RPJMN a success. This research aims to find out accurate predictions about the level of child marriage through a system that can produce accurate data. The methodology used in this research is fuzzy which has been proven to be a good method for carrying out predictive analysis. The accuracy value resulting from trials using the fuzzy method was 90%.
Pembangunan Web untuk Promosi dan Penjualan Online Pengrajin Kerupuk Rambak Kulit Kerbau di Penanggulan Pegandon Kendal Wibowo, Sasono; Suharnawi, Suharnawi; Santoso, Dewi Agustini; Harini, Harini
Manggali Vol 3 No 1 (2023): Manggali
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat, Universitas Ivet

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31331/manggali.v3i1.2438

Abstract

Pengabdian pada masyarakat ini berupa Pembangunan Web untuk promosi dan penjualan OnLine Pengrajin Kerupuk Rambak Kulit Kerbau Di Penanggulan Pegandon Kendal. Tujuan dari pelaksanaan pengabdian ini adalah untuk meningkatkan pemahaman sekaligus ketrampilan para para pengrajin kerupuk rambak kulit kerbau untuk bisa memanfaatkan teknologi informasi dalam menunjang usahanya khususnya dalam promosi dan pelayanan penjualan secara online. Metode yang digunakan dalam pengabdian ini adalah dengan diskusi dan tutorial langsung, dilanjutkan dengan konsultasi yang berkaitan dengan pemanfaatan media internet untuk pelaksanaan penjualan online.
Pembangunan Sistem Informasi Penduduk (Sipenduk) Di Kelurahan Randu Garut Tugu Semarang Wibowo, Sasono; Suharnawi, Suharnawi; Santoso, Dewi Agustini
Manggali Vol 2 No 2 (2022): Manggali
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat, Universitas Ivet

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31331/manggali.v2i2.2212

Abstract

Kelurahan Randu Garut Kecamatan Tugu Semarang merupakan wilayah industri yang cukup besar, dengan jumlah penduduk 2.312 jiwa, juga banyak warga boro maupun kost karena mereka adalah karyawan dari beberapa perusahaan yang ada dikawasan industri setempat. Dan kondisi ini membutuhkan sistem untuk mengelola data penduduk. Dengan solusi pembangunan Sipenduk untuk mengelola dan menyajikan informasi tentang kondisi penduduk dengan mudah, cepat dan akurat. Metode pelaksanaan PKM dengan identifikassi masalah, solusi, simulasi, pembuatan dan implementasi sistem, training, konseling dan evaluasi. Dengan luaran aplikasi sipenduk
Pelatihan Aplikasi Camtasia Dalam Peningkatan Kegiatan Pembelajaran Para Guru SMP Negeri 25 Semarang Wibowo, Sasono; Gamayanto, Indra; suharnawi, suharnawi; Harini, Harini
Manggali Vol 3 No 2 (2023): Manggali
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat, Universitas Ivet

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31331/manggali.v3i2.2740

Abstract

SMP N 25 Semarang merupakan Sekolah berstandar Nasional, yang harus selalu mengembangkan proses pembelajaran, sejalan dengan dunia pendidikan dan perkembangan teknologi informasi, maka pihak Sekolah dan Guru termotivasi untuk bisa memanfaatkan teknologi informassi tersebut dalam memajukan dan meningkatkan kualitas Pendidikan, terutama dalam proses pembelajaran yang bisa dilakukan secara online, dalam bentuk media video. Kegiatan PKM ini berupa tutorial pembuatan video pembelajaran dengan aplikasi Camtasia untuk kemudian diupload di Drive yang ada, untuk bisa diunduh Siswa setiap saat, sehingga pembelajaran tetap bisa diikuti Siswa disaat Guru berhalangan untuk tatap muka.
Optimization of Early Diagnosis Prediction Models for Acute Respiratory Infections (ARI) in Children Using Decision Tree, Random Forest, and Resampling Techniques Firdaus, Caesario Gumilang; Rohmani, Asih; Suharnawi, Suharnawi
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11558

Abstract

Acute Respiratory Tract Infections (ARI) are the leading cause of childhood morbidity in Indonesia, with challenges in early detection due to limited medical personnel and diagnostic data imbalance, where LRTI cases are far fewer than URTI cases. This study developed and optimized an ARI classification prediction model (URTI and LRTI) based on machine learning with resampling techniques to address imbalance. An explanatory quantitative design was used with secondary data from the Mijen Community Health Center, Semarang (2020–2025, 12.177 valid data), with preprocessing including outlier handling (Winsorizing, IQR), stratified split (70:30), and RobustScaler on the training data. Three resampling techniques (SMOTE, ADASYN, SMOTE-ENN) were applied, then tested using Decision Tree and Random Forest with GridSearchCV and 5-fold cross-validation, focusing on Recall and AUC-PR evaluation for minority classes. The results showed that Random Forest with SMOTE-ENN provided the best performance, increasing the LRTI recall from 0.02 to 0.37 and F1-macro to 0.54, while Decision Tree with SMOTE-ENN produced the highest AUC-PR of 0.31. Despite this significant improvement, a recall of 0.37 is still low for clinical applications because the risk of false negatives remains high, potentially delaying patient treatment Future implementation requires the integration of clinical symptom data (e.g., respiratory rate) to achieve clinically acceptable sensitivity. These findings confirm that resampling can improve model capabilities, but additional feature exploration is needed to achieve adequate diagnostic sensitivity in the context of healthcare analytics.
Data-Driven K-Means Clustering Analysis for Stunting Risk Profiling of Pregnant Women Nazella, Desvita Dian; Hadi, Heru Pramono; Al Zami, Farrikh; Ashari, Ayu; Kusumawati, Yupie; Suharnawi, Suharnawi; Megantara, Rama Aria; Naufal, Muhammad
Building of Informatics, Technology and Science (BITS) Vol 7 No 3 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i3.8415

Abstract

Stunting in children is influenced by maternal health conditions during pregnancy. This study aims to classify pregnant women to prevent stunting based on clinical, demographic, and environmental factors using the K-Means Clustering algorithm. A total of 229 data from the Primadona application (Disdalduk KB Kota Semarang) were analyzed using 14 normalized variables. The optimal number of clusters was determined using the Elbow Method and validated using the Silhouette Score, Davies-Bouldin Index, and Calinski-Harabasz Index. The Kruskal-Wallis test was performed to verify differences between clusters. This study resulted in seven clusters with different profiles, with a Silhouette Score of 0.134, Davies-Bouldin Index of 1.509, and Calinski-Harabasz Index of 29.54. These values ​​indicate that the cluster structure is formed and reflects the variation in risk for pregnant women, although there is overlap due to differences in characteristics between individuals. The clustering successfully differentiated pregnant women with low to high risk, influenced by health and environmental factors. This study proves the effectiveness of K-Means in identifying stunting risk patterns in pregnant women and supports more targeted interventions, such as nutritional counseling, disease risk monitoring, education on cigarette smoke exposure, and referrals. Limitations of this study include the unbalanced distribution of data between and the use of cross-sectional data. Future research is recommended to improve pre-processing and compare other clustering methods such as K-Medoids or DBSCAN for more precise stunting risk analysis.
Co-Authors Acun Kardianawati Afif, Rizal Naufal Agus Prayitno Agus Winarno, Agus Al zami, Farrikh Aminah Rizkia Puspita Sari, Raden Ayu Andika, Arditya Dian Ashari, Ayu Asih Rohmani, Asih Candra Irawan Caturkusuma, Resha Meiranadi Dewi Agustini Santoso Fahmi Amiq Firdaus, Caesario Gumilang Fitria Wulandari Hadi, Heru Pramono Hallang Lewa, Andi Harini Harini Hariyadi, Guruh Taufan Ida Farida Imam Nuryanto Indra Gamayanto Jaka Prasetya Juli Ratnawati Karis Widyatmoko karmila karmila Kusumawati, Yupie Lalang Erawan Lewa, Andi Hallang Megantara, Rama Aria Muhammad Naufal, Muhammad Muslih Muslih Nazella, Desvita Dian Neni Kurniawati Pamungkas, Natalinda Prawitasari, Dian Prihandono, Adi Puji Purwatiningsih, Aris Ramadhan Rakhmat Sani Rifa’i, Muhammad Nabhan Safitri, Maria Sasono Wibowo Setiarso, Ichwan Setiawan, Aries Umi Rosyidah Zaenal Arifin